Medical image fusion: A survey of the state of the art

Information Fusion

Volumn 19, Issue 1, 2014, Pages 4-19

  James, Alex Pappachen ^a   Dasarathy, Belur V ^b  

^a NAZARBAYEV UNIVERSITY   (Kazakhstan)

^b Information Fusion Consultant ^*  (United States)

Author keywords

Diagnostics; Image fusion; Medical image analysis; Medical imaging

Indexed keywords

DIAGNOSIS; MEDICAL IMAGING; PLASMA DIAGNOSTICS; RELIABILITY ANALYSIS;

IMAGE FUSION METHODS; IMAGING MODALITY; IMAGING QUALITY; MEDICAL DIAGNOSTICS; MULTIPLE IMAGE; MULTIPLE IMAGING MODALITY; SCIENTIFIC DISCIPLINE; STATE OF THE ART;

IMAGE FUSION;

EID: 84897986730     PISSN: 15662535     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.inffus.2013.12.002     Document Type: Article

References (320)

1. B.V. Dasarathy A special issue on natural computing methods in bioinformatics Inform. Fus. 10 3 2009 209
2. B.V. Dasarathy Editorial: information fusion in the realm of medical applications - a bibliographic glimpse at its growing appeal Inform. Fus. 13 1 2012 1 9
3. B.V. Dasarathy A special issue on biologically inspired information fusion Inform. Fus. 11 1 2010 1
4. M.C. Casey, and R.I. Damper Editorial: special issue on biologically-inspired information fusion Inform. Fus. 11 1 2010 2 3
5. J. Navarra, A. Alsius, S.S. Faraco, and C. Spence Assessing the role of attention in the audiovisual integration of speech Inform. Fus. 11 1 2010 4 11
6. C.E. Hugenschmidt, S. Hayasaka, A.M. Peier, and P.J. Laurienti Applying capacity analyses to psychophysical evaluation of multisensory interactions Inform. Fus. 11 1 2010 12 20
7. J. Greensmith, U. Aickelin, and G. Tedesco Information fusion for anomaly detection with the dendritic cell algorithm Inform. Fus. 11 1 2010 21 34
8. J. Twycross, and U. Aickelin Information fusion in the immune system Inform. Fus. 11 1 2010 35 44
9. S. Wuerger, G. Meyer, M. Hofbauer, C. Zetzsche, and K. Schill Motion extrapolation of auditory-visual targets Inform. Fus. 11 1 2010 45 50
10. T.D. Dixon, S.G. Nikolov, J.J. Lewis, J. Li, E.F. Canga, J.M. Noyes, T. Troscianko, D.R. Bull, and C.N. Canagarajah Task-based scanpath assessment of multi-sensor video fusion in complex scenarios Inform. Fus. 11 1 2010 51 65
11. J.-B. Lei, J.-B. Yin, H.-B. Shen, Feature fusion and selection for recognizing cancer-related mutations from common polymorphisms, in: 2010 Chinese Conference on Pattern Recognition (CCPR), IEEE, 2010, pp. 1-5.
12. S. Tsevas, D. Iakovidis, Dynamic time warping fusion for the retrieval of similar patient cases represented by multimodal time-series medical data, in: 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB), 2010, IEEE, 2010, pp. 1-4.
13. H. Müller, and J.K. Cramer The image CLEF medical retrieval task at ICPR 2010 - information fusion to combine visual and textual information Recog. Patt. Sig., Speech, Images Videos 2010 Springer 99 108
14. Z.R. Mnatsakanyan, H.S. Burkom, M.R. Hashemian, and M.A. Coletta Distributed information fusion models for regional public health surveillance Inform. Fus. 13 2 2012 129 136
15. S. Marshall, G. Matsopoulos, Morphological data fusion in medical imaging, in: IEEE Winter Workshop on Nonlinear Digital Signal Processing, 1993, IEEE, 1993, pp. 6-1.
16. K. Mikoajczyk, J. Owczarczyk, and W. Recko A test-bed for computer-assisted fusion of multi-modality medical images Comput. Anal. Images Patt. 1993 Springer 664 668
17. G. Matsopoulos, S. Marshall, and J. Brunt Multiresolution morphological fusion of MR and CT images of the human brain IEE Proc. Vis., Image Signal Process. vol. 141 1994 IET 137 142
18. H. Li, R. Deklerck, B. De Cuyper, A. Hermanus, E. Nyssen, and J. Cornelis Object recognition in brain CT-scans: knowledge-based fusion of data from multiple feature extractors IEEE Trans. Med. Imag. 14 2 1995 212 229
19. G.L. Rogova, and P.C. Stomper Information fusion approach to microcalcification characterization Inform. Fus. 3 2 2002 91 102
20. W. Dou, S. Ruan, Q. Liao, D. Bloyet, J.-M. Constans, Knowledge based fuzzy information fusion applied to classification of abnormal brain tissues from MRI, in: Proceedings of the Seventh International Symposium on Signal Processing and its Applications, 2003, vol. 1, IEEE, 2003, pp. 681-684.
21. M. Raza, I. Gondal, D. Green, and R.L. Coppel Classifier fusion to predict breast cancer tumors based on microarray gene expression data Knowledge-Based Intelligent Information and Engineering Systems 2005 Springer 866 874
22. Y. Wu, J. Zhang, C. Wang, S. C. Ng, Linear decision fusions in multilayer perceptrons for breast cancer diagnosis, in: 17th IEEE International Conference on Tools with Artificial Intelligence, 2005, ICTAI 05, IEEE, 2005, p. 2.
23. S. Radhouani, J.K. -Cramer, S. Bedrick, B. Bakke, and W. Hersh Using media fusion and domain dimensions to improve precision in medical image retrieval Multilingual Information Access Evaluation II - Multimedia Experiments 2010 Springer 223 230
24. J.R. Jensen, and W.R. Hersh Manual query modification and data fusion for medical image retrieval Accessing Multilingual Information Repositories 2006 Springer 673 679
25. D. Racoceanu, C. Lacoste, R. Teodorescu, and N. Vuillemenot A semantic fusion approach between medical images and reports using UMLS Information Retrieval Technology 2006 Springer 460 475
26. R. Kapoor, A. Dutta, D. Bagai, T. S. Kamal, Fusion for registration of medical images-a study, in: Proceedings of the 32nd Applied Imagery Pattern Recognition Workshop, 2003, IEEE, 2003, pp. 180-185.
27. Q. Zhang, W. Tang, L. Lai, W. Sun, K. Wong, Medical diagnostic image data fusion based on wavelet transformation and self-organising features mapping neural networks, in: Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004, vol. 5, IEEE, 2004, pp. 2708-2712.
28. Q. Zhang, M. Liang, W. Sun, Medical diagnostic image fusion based on feature mapping wavelet neural networks, in: Proceedings of the Third International Conference on Image and Graphics, 2004, IEEE, 2004, pp. 51-54.
29. K. Yuanyuan, L. Bin, T. Lianfang, M. Zongyuan, Multi-modal medical image fusion based on wavelet transform and texture measure, in: Chinese Control Conference, 2007, CCC 2007, IEEE, 2007, pp. 697-700.
30. B. Alfano, M. Ciampi, and G.D. Pietro A wavelet-based algorithm for multimodal medical image fusion Semantic Multimedia 2007 Springer 117 120
31. S. Kor, U. Tiwary, Feature level fusion of multimodal medical images in lifting wavelet transform domain, in: 26th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, 2004, IEMBS'04, vol. 1, IEEE, 2004, pp. 1479-1482.
32. S. Garg, K. U. Kiran, R. Mohan, U. Tiwary, Multilevel medical image fusion using segmented image by level set evolution with region competition, in: 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005, IEEE-EMBS 2005, IEEE, 2006, pp. 7680-7683.
33. L. Bin, T. Lianfang, K. Yuanyuan, Y. Xia, Parallel multimodal medical image fusion in 3D conformal radiotherapy treatment planning, in: The 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008, ICBBE 2008, IEEE, 2008, pp. 2600-2604.
34. M. Ciampi, Medical image fusion for color visualization via 3D RDWT, in: 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB), 2010, IEEE, 2010, pp. 1-6.
35. J. Montagner, V. Barra, J. Boire, Synthesis of a functional information with anatomical landmarks by multiresolution fusion of brain images, in: 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE, 2006, pp. 6547-6550.
36. S.-H. Lai, M. Fang, Adaptive medical image visualization based on hierarchical neural networks and intelligent decision fusion, in: Proceedings of the 1998 IEEE Signal Processing Society Workshop on Neural Networks for Signal Processing VIII, 1998, IEEE, 1998, pp. 438-447.
37. S. Constantinos, M. S. Pattichis, E. M.Tzanakou, Medical imaging fusion applications: an overview, in: Conference Record of the Thirty-Fifth Asilomar Conference on Signals, Systems and Computers, 2001, vol. 2, IEEE, 2001, pp. 1263-1267.
38. H. Szu, I. Kopriva, P. Hoekstra, N. Diakides, M. Diakides, J. Buss, J. Lupo, Early tumor detection by multiple infrared unsupervised neural nets fusion, in: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2003, vol. 2, IEEE, 2003, pp. 1133-1136.
39. W. Li, and X.-f. Zhu A new algorithm of multi-modality medical image fusion based on pulse-coupled neural networks Advances in Natural Computation 2005 Springer 995 1001
40. L. Xiaoqi, Z. Baohua, G. Yong, Medical image fusion algorithm based on clustering neural network, in: The 1st International Conference on Bioinformatics and Biomedical Engineering, 2007, ICBBE 2007, IEEE, 2007, pp. 637-640.
41. Y.-P. Wang, J.-W. Dang, Q. Li, S. Li, Multimodal medical image fusion using fuzzy radial basis function neural networks, in: International Conference on Wavelet Analysis and Pattern Recognition, 2007, ICWAPR'07, vol. 2, IEEE, 2007, pp. 778-782.
42. Z. Wang, and Y. Ma Medical image fusion using m-PCNN Inform. Fus. 9 2 2008 176 185
43. J. Teng, S. Wang, J. Zhang, X. Wang, Neuro-fuzzy logic based fusion algorithm of medical images, in: 3rd International Congress on Image and Signal Processing (CISP), 2010, vol. 4, IEEE, 2010, pp. 1552-1556.
44. Y. Wu, C. Wang, S.C. Ng, A. Madabhushi, and Y. Zhong Breast cancer diagnosis using neural-based linear fusion strategies Neural Information Processing 2006 Springer 165 175
45. D. Lederman, B. Zheng, X. Wang, X.H. Wang, and D. Gur Improving breast cancer risk stratification using resonance-frequency electrical impedance spectroscopy through fusion of multiple classifiers Ann. Biomed. Eng. 39 3 2011 931 945
46. M. S. B. Sehgal, I. Gondal, L. Dooley, Support vector machine and generalized regression neural network based classification fusion models for cancer diagnosis, in: Fourth International Conference on Hybrid Intelligent Systems, 2004, HIS'04, IEEE, 2004, pp. 49-54.
47. C. Barillot, D. Lemoine, L.L. Briquer, F. Lachmann, and B. Gibaud Data fusion in medical imaging: merging multimodal and multipatient images, identification of structures and 3D display aspects Euro. J. Radiol. 17 1 1993 22 27
48. V. Barra, and J.-Y. Boire A general framework for the fusion of anatomical and functional medical images NeuroImage 13 3 2001 410 424
49. I. Bloch, O. Colliot, O. Camara, and T. Geraud Fusion of spatial relationships for guiding recognition, example of brain structure recognition in 3D MRI Patt. Recog. Lett. 26 4 2005 449 457
50. W. Dou, S. Ruan, Y. Chen, D. Bloyet, and J.-M. Constans A framework of fuzzy information fusion for the segmentation of brain tumor tissues on MR images Image Vision Comput. 25 2 2007 164 171
51. R. Wasserman, R. Acharya, C. Sibata, K. Shin, A data fusion approach to tumor delineation, in: Proceedings of the International Conference on Image Processing, 1995, vol. 2, IEEE, 1995, pp. 476-479.
52. V. Barra, and J.-Y. Boire Automatic segmentation of subcortical brain structures in MR images using information fusion IEEE Trans. Med. Imag. 20 7 2001 549 558
53. C.-H. Huang, J.-D. Lee, Improving MMI with enhanced-FCM for the fusion of brain MR and SPECT images, in: Proceedings of the 17th International Conference on Pattern Recognition, 2004, ICPR 2004, vol. 3, IEEE, 2004, pp. 562-565.
54. A. Villeger, L. Ouchchane, J.-J. Lemaire, and J.-Y. Boire Data fusion and fuzzy spatial relationships for locating deep brain stimulation targets in magnetic resonance images Advanced Concepts for Intelligent Vision Systems 2006 Springer 909 919
55. W. Dou, S. Ruan, Q. Liao, D. Bloyet, J.-M. Constans, and Y. Chen Fuzzy information fusion scheme used to segment brain tumor from MR images Fuzzy Logic and Applications 2006 Springer 208 215
56. X. Tai, W. Song, An improved approach based on FCM using feature fusion for medical image retrieval, in: Fourth International Conference on Fuzzy Systems and Knowledge Discovery, 2007, FSKD 2007, vol. 2, IEEE, 2007, pp. 336-342.
57. W. Song, T. Hua, Analytic implementation for medical image retrieval based on FCM using feature fusion with relevance feedback, in: The 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008, ICBBE 2008, IEEE, 2008, pp. 2590-2595.
58. Y. Na, H. Lu, Y. Zhang, Content analysis based medical images fusion with fuzzy inference, in: Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008, FSKD'08, vol. 3, IEEE, 2008, pp. 37-41.
59. A. Das, M. Bhattacharya, Evolutionary algorithm based automated medical image fusion technique: comparative study with fuzzy fusion approach, in: World Congress on Nature & Biologically Inspired Computing, 2009, NaBIC 2009, IEEE, 2009, pp. 269-274.
60. A. Assareh, L. G. Volkert, Fuzzy rule base classifier fusion for protein mass spectra based ovarian cancer diagnosis, in: IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2009, CIBCB'09, IEEE, 2009, pp. 193-199.
61. Q. Guihong, Z. Dali, and Y. Pingfan Medical image fusion by wavelet transform modulus maxima Optics Exp. 9 4 2001 184 190
62. L. X. Mei, L. Jin, W. S. Hui, New medical image fusion algorithm based on second generation wavelet transform, in: IMACS Multiconference on Computational Engineering in Systems Applications, IEEE, 2006, pp. 1460-1464.
63. W. Li, X. Zhu, S. Wu, A novel approach to fast medical image fusion based on lifting wavelet transform, in: The Sixth World Congress on Intelligent Control and Automation, 2006, WCICA 2006, vol. 2, IEEE, 2006, pp. 9881-9884.
64. A. Wang, H. Sun, Y. Guan, The application of wavelet transform to multi-modality medical image fusion, in: Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control, 2006, ICNSC'06, IEEE, 2006, pp. 270-274.
65. H. Zhang, L. Liu, N. Lin, A novel wavelet medical image fusion method, in: International Conference on Multimedia and Ubiquitous Engineering, 2007, MUE'07, IEEE, 2007, pp. 548-553.
66. W. Anna, L. Dan, C. Yu, et al., Research on medical image fusion based on orthogonal wavelet packets transformation combined with 2v-SVM, in: IEEE/ICME International Conference on Complex Medical Engineering, 2007, CME 2007, IEEE, 2007, pp. 670-675.
67. X. Li, X. Tian, Y. Sun, and Z. Tang Medical image fusion by multi-resolution analysis of wavelets transform Wavelet Analysis and Applications 2007 Springer 389 396
68. C. Shangli, H. Junmin, L. Zhongwei, Medical image of PET/CT weighted fusion based on wavelet transform, in: The 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008, ICBBE 2008, IEEE, 2008, pp. 2523-2525.
69. Y. Licai, L. Xin, Y. Yucui, Medical image fusion based on wavelet packet transform and self-adaptive operator, in: The 2nd International Conference on Bioinformatics and Biomedical Engineering, 2008, ICBBE 2008, IEEE, 2008, pp. 2647-2650.
70. Z. Wencang, C. Lin, Medical image fusion method based on wavelet multi-resolution and entropy, in: IEEE International Conference on Automation and Logistics, 2008, ICAL 2008, IEEE, 2008, pp. 2329-2333.
71. B. Yang, Z. Jing, Medical image fusion with a shift-invariant morphological wavelet, in: IEEE Conference on Cybernetics and Intelligent Systems, 2008, IEEE, 2008, pp. 175-178.
72. R. Singh, M. Vatsa, A. Noore, Multimodal medical image fusion using redundant discrete wavelet transform, in: Seventh International Conference on Advances in Pattern Recognition, 2009, ICAPR'09, IEEE, 2009, pp. 232-235.
73. Z. Xiao, C. Zheng, Medical image fusion based on an improved wavelet coefficient contrast, in: 3rd International Conference on Bioinformatics and Biomedical Engineering, IEEE, 2009, pp. 1-4.
74. L. Chiorean, M.-F. Vaida, Medical image fusion based on discrete wavelet transform using java technology, in: Proceedings of the ITI 2009 31st International Conference on Information Technology Interfaces, 2009, ITI'09, IEEE, 2009, pp. 55-60.
75. X. Zhang, Y. Zheng, Y. Peng, W. Liu, C. Yang, Research on multi-mode medical image fusion algorithm based on wavelet transform and the edge characteristics of images, in: 2nd International Congress on Image and Signal Processing, 2009, CISP'09, IEEE, 2009, pp. 1-4.
76. Y. Liu, J. Yang, J. Sun, PET/CT medical image fusion algorithm based on multiwavelet transform, in: 2nd International Conference on Advanced Computer Control (ICACC), 2010, vol. 2, IEEE, 2010, pp. 264-268.
77. Y. Yang, Multimodal medical image fusion through a new DWT based technique, in: 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), 2010, IEEE, 2010, pp. 1-4.
78. B. Li, L. Tian, S. Ou, Rapid multimodal medical image registration and fusion in 3D conformal radiotherapy treatment planning, in: 4th International Conference on Bioinformatics and Biomedical Engineering, 2010, IEEE, 2010, pp. 1-5.
79. M. Agrawal, P. Tsakalides, A. Achim, Medical image fusion using the convolution of meridian distributions, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2010, IEEE, 2010, pp. 3727-3730.
80. W. Xue-jun, M. Ying, A medical image fusion algorithm based on lifting wavelet transform, in: 2010 International Conference on Artificial Intelligence and Computational Intelligence (AICI), vol. 3, IEEE, 2010, pp. 474-476.
81. S. Rajkumar, S. Kavitha, Redundancy discrete wavelet transform and contourlet transform for multimodality medical image fusion with quantitative analysis, in: 3rd International Conference on Emerging Trends in Engineering and Technology (ICETET), 2010, IEEE, 2010, pp. 134-139.
82. C. Kavitha, C. Chellamuthu, Multimodal medical image fusion based on integer wavelet transform and neuro-fuzzy, in: 2010 International Conference on Signal and Image Processing (ICSIP), IEEE, 2010, pp. 296-300.
83. S. Vekkot Wavelet based medical image fusion using filter masks Trends in Intelligent Robotics 2010 Springer 298 305
84. J. Teng, X. Wang, J. Zhang, S. Wang, and P. Huo A multimodality medical image fusion algorithm based on wavelet transform Advances in Swarm Intelligence 2010 Springer 627 633
85. C. Kok, Y. Hui, T. Nguyen, Medical image pseudo coloring by wavelet fusion, in: Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1996, Bridging Disciplines for Biomedicine, vol. 2, IEEE, 1996, pp. 648-649.
86. Z. Cui, G. Zhang, J. Wu, Medical image fusion based on wavelet transform and independent component analysis, in: International Joint Conference on Artificial Intelligence, 2009, JCAI'09, IEEE, 2009, pp. 480-483.
87. F. Masulli, and S. Mitra Natural computing methods in bioinformatics: a survey Inform. Fus. 10 3 2009 211 216
88. J. K. Avor, T. Sarkodie-Gyan, An approach to sensor fusion in medical robots, in: IEEE International Conference on Rehabilitation Robotics, 2009, ICORR 2009, IEEE, 2009, pp. 818-822.
89. G.N. Brock, W.D. Beavis, and L.S. Kubatko Fuzzy logic and related methods as a screening tool for detecting gene regulatory networks Inform. Fus. 10 3 2009 250 259
90. R.K. De, and A. Ghosh Linguistic recognition system for identification of some possible genes mediating the development of lung adenocarcinoma Inform. Fus. 10 3 2009 260 269
91. J. Teng, S. Wang, J. Zhang, X. Wang, Fusion algorithm of medical images based on fuzzy logic, in: Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2010, vol. 2, IEEE, 2010, pp. 546-550.
92. M. Bhattacharya, and A. Das Multimodality medical image registration and fusion techniques using mutual information and genetic algorithm-based approaches Software Tools and Algorithms for Biological Systems 2011 Springer 441 449
93. V.D. Calhoun, and T. Adali Feature-based fusion of medical imaging data IEEE Trans. Inform. Technol. Biomed. 13 5 2009 711 720
94. W. Hao-quan, X. Hao, Multi-mode medical image fusion algorithm based on principal component analysis, in: International Symposium on Computer Network and Multimedia Technology, 2009, CNMT 2009, IEEE, 2009, pp. 1-4.
95. N. Al-Azzawi, H. A. M. Sakim, A. W. Abdullah, H. Ibrahim, Medical image fusion scheme using complex contourlet transform based on PCA, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009, EMBC 2009, IEEE, 2009, pp. 5813-5816.
96. N.A. Al-Azzawi, H. Mat Sakim, A.W. Abdullah, An efficient medical image fusion method using contourlet transform based on PCM, in: IEEE Symposium on Industrial Electronics & Applications, 2009, ISIEA 2009, vol. 1, IEEE, 2009, pp. 11-14.
97. C. He, Q. Liu, H. Li, and H. Wang Multimodal medical image fusion based on IHS and PCA Proc. Eng. 7 2010 280 285
98. C. Wang, and Z. Ye First-order fusion of volumetric medical imagery IEE Proc. - Vis., Image Sig. Process. 153 2 2006 191 198
99. T. Chung, X. Liu, C. Chen, X. Sun, N. Chiu, J. Lee, Intermodality registration and fusion of liver images for medical diagnosis, in: Proceedings of the Intelligent Information Systems, 1997, IIS'97, IEEE, 1997, pp. 42-46.
100. J. Phegley, K. Perkins, L. Gupta, and J.K. Dorsey Risk-factor fusion for predicting multifactorial diseases IEEE Trans. Biomed. Eng. 49 1 2002 72 76
101. B.E. -Ramirez The hermite transform as an efficient model for local image analysis: an application to medical image fusion Comput. Elect. Eng. 34 2 2008 99 110
102. Z. Zhang, J. Yao, S. Bajwa, and T. Gudas Automatic multimodal medical image fusion Proceedings of the 16th IEEE Conference on Computer-Based Medical Systems 2003 IEEE Computer Society 42 49
103. L. Yang, B. Guo, and W. Ni Multimodality medical image fusion based on multiscale geometric analysis of contourlet transform Neurocomputing 72 1 2008 203 211
104. Y. Wei, Y. Zhu, F. Zhao, Y. Shi, T. Mo, X. Ding, J. Zhong, Implementing contourlet transform for medical image fusion on a heterogenous platform, in: International Conference on Scalable Computing and Communications; Eighth International Conference on Embedded Computing, 2009, SCALCOM-EMBEDDEDCOM'09, IEEE, 2009, pp. 115-120.
105. V. Barra, J.-Y. Boire, Quantification of brain tissue volumes using MR/MR fusion, in: Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2000, vol. 2, IEEE, 2000, pp. 1451-1454.
106. L. Gupta, B. Chung, D. L. Molfese, Multichannel fusion models for the parametric classification of multicategory differential brain activity, in: 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004, IEMBS'04, vol. 1, IEEE, 2004, pp. 940-943.
107. I. Dimou, G. Manikis, M. Zervakis, Classifier fusion approaches for diagnostic cancer models, in: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, EMBS'06, IEEE, 2006, pp. 5334-5337.
108. M. Raza, I. Gondal, D. Green, R. L. Coppel, Classifier fusion using dempster-shafer theory of evidence to predict breast cancer tumors, in: 2006 IEEE Region 10 Conference TENCON 2006, IEEE, 2006, pp. 1-4.
109. N. Zhang, Q. Liao, S. Ruan, S. Lebonvallet, Y. Zhu, Multi-kernel SVM based classification for tumor segmentation by fusion of MRI images, in: IEEE International Workshop on Imaging Systems and Techniques, 2009, IST'09, IEEE, 2009, pp. 71-75.
110. M.M. Rahman, B.C. Desai, and P. Bhattacharya Medical image retrieval with probabilistic multi-class support vector machine classifiers and adaptive similarity fusion Computer. Med. Imag. Graph. 32 2 2008 95 108
111. Y. Huang, J. Zhang, Y. Zhao, D. Ma, Medical image retrieval with query-dependent feature fusion based on one-class SVM, in: IEEE 13th International Conference on Computational Science and Engineering (CSE), 2010, IEEE, 2010, pp. 176-183.
112. G. Pavesi, and G. Valentini Classification of co-expressed genes from DNA regulatory regions Inform. Fus. 10 3 2009 233 241
113. L. Palopoli, S.E. Rombo, G. Terracina, G. Tradigo, and P. Veltri Improving protein secondary structure predictions by prediction fusion Inform. Fus. 10 3 2009 217 232
114. J.Y. Njiwa, R. Goutte, Use of quaternionic signals representation for analysis and fusion of multi-components 2D medical images, in: 9th International Conference on Signal Processing, 2008, ICSP 2008, IEEE, 2008, pp. 733-736.
115. V.D. Calhoun, and T. Adali ICA for fusion of brain imaging data Signal Processing Techniques for Knowledge Extraction and Information Fusion 2008 Springer 221 240
116. P. Viswanathan, P.V. Krishna, Text fusion watermarking in medical image with semi-reversible for secure transfer and authentication, in: International Conference on Advances in Recent Technologies in Communication and Computing, 2009, ARTCom'09, IEEE, 2009, pp. 585-589.
117. T. Kauppi, J.-K. Kamarainen, L. Lensu, V. Kalesnykiene, I. Sorri, H. Kalviainen, H. Uusitalo, and J. Pietila Fusion of multiple expert annotations and overall score selection for medical image diagnosis Image Analysis 2009 Springer 760 769
118. H. Zhou, Q. Cheng, M. Zargham, Fast fusion of medical images based on Bayesian risk minimization and pixon map, in: International Conference on Computational Science and Engineering, 2009, CSE'09, vol. 2, IEEE, 2009, pp. 1086-1091.
119. G. Bhatnagar, Q. Wu, and Z. Liu Directive contrast based multimodal medical image fusion in NSCT domain IEEE Trans. Multimedia 15 5 2013 1014 1024
120. H. G. Hosseini, A. Alizad, M. Fatemi, Fusion of vibro-acoustography images and X-ray mammography, in: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, EMBS'06, IEEE, 2006, pp. 2803-2806.
121. L. Kronberger Jr., R. Nicoletti, G. Ranner, E. Graif, R. Stollberger, R. Einspieler, M. Wiltgen, G. Fueger, F. Ebner, and P. Steindorfer Computed fusion of MRI and anti-cea immunoscintigraphy in the follow up of operated rectal cancer Euro. J. Can. 29 1993 S97
122. A.T. -Ahmed, and L. Gautier On information fusion to improve segmentation of MRI sequences Inform. Fus. 3 2 2002 103 117
123. M. Aguilar, J. R. New, Fusion of multi-modality volumetric medical imagery, in: Proceedings of the Fifth International Conference on Information Fusion, 2002, vol. 2, IEEE, 2002, pp. 1206-1212.
124. M. Vermandel, N. Betrouni, G. Palos, J.-Y. Gauvrit, C. Vasseur, and J. Rousseau Registration, matching and data fusion in 2D/3D medical imaging: Application to DSA and MRA Medical Image Computing and Computer-Assisted Intervention-MICCAI 2003 2003 Springer 778 785
125. A.-S. Capelle, O. Colot, and C.F. -Maloigne Evidential segmentation scheme of multi-echo MR images for the detection of brain tumors using neighborhood information Inform. Fus. 5 3 2004 203 216
126. Y.-M. Zhu, and S.M. Cocho An object-oriented framework for medical image registration, fusion, and visualization Comput. Meth. Prog. Biomed. 82 3 2006 258 267
127. O. Tanaka, S. Hayashi, M. Matsuo, M. Nakano, H. Uno, K. Ohtakara, S. Okada, H. Hoshi, and T. Deguchi 4043 Poster effect of edema on postimplant dosimetry in prostate brachytherapy using CT/MRI fusion Euro. J. Can. Suppl. 5 4 2007 292
128. S.F. Nemec, P. Peloschek, M.T. Schmook, C.R. Krestan, W. Hau, C. Matula, and C. Czerny CT-MR image data fusion for computer-assisted navigated surgery of orbital tumors Euro. J. Radiol. 73 2 2010 224 229
129. S. Daneshvar, and H. Ghassemian MRI and PET image fusion by combining IHS and retina-inspired models Inform. Fus. 11 2 2010 114 123
130. 11C-choline PET/CT of human prostate cancer using multi-modality fusion techniques Acad. Radiol. 17 5 2010 614 623
131. E. Faliagka, G. Matsopoulos, A. Tsakalidis, J. Tsaknakis, and G. Tzimas Registration and fusion techniques for medical images: Demonstration and evaluation Biomedical Engineering Systems and Technologies 2011 Springer 15 28
132. B. Hentschel, W. Oehler, D. Straus, A. Ulrich, and A. Malich Definition of the CTV prostate in CT and MRI by using CT-MRI image fusion in IMRT planning for prostate cancer Strahlentherapie und Onkologie 187 3 2011 183 190
133. C. Tsien, W. Parker, D. Parmar, D. Hristov, L. Souhami, and C. Freeman 81 the role of MRI fusion in radiotherapy planning of pediatric CNS tumors Int. J. Rad. Oncol. Biol. Phys. 45 3 1999 188 189
134. J. Julow, T. Major, M. Emri, I. Valalik, S. Sagi, L. Mangel, G. Nemeth, L. Tron, G. Varallyay, and D. Solymosi et al. The application of image fusion in stereotactic brachytherapy of brain tumours Acta Neurochirurgica 142 11 2000 1253 1258
135. R. Gorniak, E. Kramer, G.Q. Maguire Jr, M.E. Noz, C. Schettino, and M.P. Zeleznik Evaluation of a semiautomatic 3D fusion technique applied to molecular imaging and MRI brain/frame volume data sets J. Med. Syst. 27 2 2003 141 156
136. J.-D. Lee, B.-R. Huang, C.-H. Huang, A surface-projection MMI for the fusion of brain MR and SPECT images, in: IEEE Region 10 Conference, 2004, TENCON 2004, IEEE, 2004, pp. 179-182.
137. S. David, M. Back, R. Mukherjee, K. Lim, and J. Liade Interclinican variability in delineation of tumour volumes for glioblastomas with the assistance of MRI fusion Euro. J. Can. 3 2 2005 400 401
138. R.A. Heckemann, J.V. Hajnal, P. Aljabar, D. Rueckert, and A. Hammers Multiclassifier fusion in human brain MR segmentation: modeling convergence Medical Image Computing and Computer-Assisted Intervention-MICCAI 2006 2006 Springer 815 822
139. J. A. Marquez, A. Gastellum, M. A. Padilla, Image-fusion operators for 3D anatomical and functional analysis of the brain, in: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, EMBS 2007, IEEE, 2007, pp. 833-835.
140. M.C. Dastjerdi, A. Karimian, H. Afarideh, and A. Mohammadzadeh FMDIB: a software tool for fusion of MRI and DHC-SPECT images of brain World Congress on Medical Physics and Biomedical Engineering, September 7-12, 2009, Munich, Germany 2009 Springer 741 744
141. S.A. Kuhn, B. Romeike, J. Walter, R. Kal, and R. Reichart Multiplanar MRI-CT fusion neuronavigation-guided serial stereotactic biopsy of human brain tumors: proof of a strong correlation between tumor imaging and histopathology by a new technical approach J. Can. Res. Clin. Oncol. 135 9 2009 1293 1302
142. H. Lee, J. Lee, G. Kim, and Y.G. Shin Efficient hybrid registration method using a shell volume for PET and high resolution MR brain image fusion World Congress on Medical Physics and Biomedical Engineering, September 7-12, 2009, Munich, Germany 2010 Springer 2326 2329
143. F. Forbes, S. Doyle, D. G.-Lorenzo, C. Barillot, M. Dojat, Adaptive weighted fusion of multiple MR sequences for brain lesion segmentation, in: IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010, IEEE, 2010, pp. 69-72.
144. S. P. Awate, H. Zhang, T. J. Simon, J. C. Gee, Multivariate segmentation of brain tissues by fusion of MRI and DTI data, in: 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008, ISBI 2008, IEEE, 2008, pp. 213-216.
145. S. Martin, M. Baumann, V. Daanen, J. Troccaz, MR prior based automatic segmentation of the prostate in TRUS images for MR/TRUS data fusion, in: IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010, IEEE, 2010, pp. 640-643.
146. S. Ahmed, K.M. Iftekharuddin, and A. Vossough Efficacy of texture, shape, and intensity feature fusion for posterior-fossa tumor segmentation in MRI IEEE Trans. Inform. Technol. Biomed. 15 2 2011 206 213
147. K. Kagawa, W.R. Lee, T.E. Schultheiss, M.A. Hunt, A.H. Shaer, and G.E. Hanks Initial clinical assessment of CT-MRI image fusion software in localization of the prostate for 3D conformal radiation therapy Int. J. Rad. Oncol. Biol. Phys. 38 2 1997 319 325
148. I. Kaplan, E. Holupka, and M. Morrissey MRI-ultrasound image fusion for 125I prostate implant treatment planning Int. J. Rad. Oncol. Biol. Phys. 42 1 1998 294
149. V. Servois, L. Chauveinc, C. El Khoury, A. Lantoine, L. Ollivier, T. Flam, J. Rosenwald, J. Cosset, and S. Neuenschwander Comparaison de deux méthodes de recalage d'images de scanographie et d'IRM en curiethérapie prostatique Cancer/Radiotherapie 7 1 2003 9 16
150. J. Crook, M. McLean, I. Yeung, T. Williams, and G. Lockwood MRI-CT fusion to assess postbrachytherapy prostate volume and the effects of prolonged edema on dosimetry following transperineal interstitial permanent prostate brachytherapy Brachytherapy 3 2 2004 55 60
151. B. Fei, Z. Lee, D.T. Boll, J.L. Duerk, J.S. Lewin, and D.L. Wilson Image registration and fusion for interventional MRI guided thermal ablation of the prostate cancer Medical Image Computing and Computer-Assisted Intervention-MICCAI 2003 2003 Springer 364 372
152. B. Fei, Z. Lee, D.T. Boll, J.L. Duerk, D.B. Sodee, J.S. Lewin, and D.L. Wilson Registration and fusion of SPECT, high-resolution MRI, and interventional MRI for thermal ablation of prostate cancer IEEE Trans. Nucl. Sci. 51 1 2004 177 183
153. D. Taussky, L. Austen, A. Toi, I. Yeung, T. Williams, S. Pearson, M. McLean, G. Pond, and J. Crook Sequential evaluation of prostate edema after permanent seed prostate brachytherapy using CT-MRI fusion Int. J. Rad. Oncol. Biol. Phys. 62 4 2005 974 980
154. O. Tanaka, S. Hayashi, M. Matsuo, K. Sakurai, M. Nakano, S. Maeda, K. Kajita, T. Deguchi, and H. Hoshi Comparison of MRI-based and CT/MRI fusion-based postimplant dosimetric analysis of prostate brachytherapy Int. J. Rad. Oncol. Biol. Phys. 66 2 2006 597 602
155. I. Yeung, S. Chen, Y. Cho, D. Taussky, A.B. Ardakani, and J. Crook 2786: Finite element modeling of prostate edema and seed dynamic post LDR prostate brachytherapy using CT-MRI fusion Int. J. Rad. Oncol. Biol. Phys. 66 3 2006 S649 S650
156. O. Tanaka, S. Hayashi, K. Sakurai, M. Matsuo, M. Nakano, S. Maeda, H. Hoshi, and T. Deguchi Importance of the CT/MRI fusion method as a learning tool for CT-based postimplant dosimetry in prostate brachytherapy Radioth. Oncol. 81 3 2006 303 308
157. 11C-acetate positron emission tomography imaging and image fusion with computed tomography and magnetic resonance imaging in patients with recurrent prostate cancer J. Clin. Oncol. 24 16 2006 2513 2519
158. O. Tanaka, S. Hayashi, M. Matsuo, M. Nakano, H. Uno, K. Ohtakara, T. Miyoshi, T. Deguchi, and H. Hoshi Effect of edema on postimplant dosimetry in prostate brachytherapy using CT/MRI fusion Int. J. Rad. Oncol. Biol. Phys. 69 2 2007 614 618
159. A. Venkatesan, J. Kruecker, S. Xu, J. Locklin, P. Pinto, A. Singh, N. Glossop, and B. Wood Abstract no. 155: early clinical experience with real time ultrasound-MRI fusion-guided prostate biopsies J. Vasc. Interven. Radiol. 19 2 2008 S59 S60
160. J. Pouliot, A.J. Cunha, G.D. Reed, S.M. Noworolski, J. Kurhanewicz, I. Hsu, and J. Chow Multi-image fusions and their role in inverse planned high-dose-rate prostate brachytherapy for dose escalation of dominant intraprostatic lesions defined by combined MRI/MRSI Brachytherapy 8 2 2009 113 114
161. 125I prostate brachytherapy post implant dosimetry Brachytherapy 8 2 2009 124
162. M. Aoki, A. Yorozu, and T. Dokiya Evaluation of interobserver differences in postimplant dosimetry following prostate brachytherapy and the efficacy of CT/MRI fusion imaging Japan. J. Radiol. 27 9 2009 342 347
163. J. Kruecker, S. Xu, B. Turkbey, P. Choyke, A. Rastinehad, J. Locklin, S. Gates, P. Pinto, and B. Wood Trus/MRI fusion-targeted prostate biopsy results correlate with MRI suspicion level J. Vasc. Interven. Radiol. 21 2 2010 S25 S26
164. P. Acher, S. Puttagunta, K. Rhode, S. Morris, J. Kinsella, A. Gaya, P. Dasgupta, C. Deehan, R. Beaney, and R. Popert et al. An analysis of intraoperative versus post-operative dosimetry with CT, CT-MRI fusion and xmr for the evaluation of permanent prostate brachytherapy implants Radioth. Oncol. 96 2 2010 166 171
165. A. Mesa, L. Chittenden, J. Lizarde, J. Lee, M. Nelson, J. Lane, A. Spitz, and K. Tokita A gold fiducial based CT/MRI fusion method for prostate treatment planning Int. J. Rad. Oncol. Biol. Phys. 78 3 2010 S375
166. S. Kadoury, P. Yan, S. Xu, N. Glossop, P. Choyke, B. Turkbey, P. Pinto, B.J. Wood, and J. Kruecker Realtime TR U S/MR I fusion targeted-biopsy for prostate cancer: a clinical demonstration of increased positive biopsy rates Prostate Cancer Imaging, Computer-Aided Diagnosis, Prognosis, and Intervention 2010 Springer 52 62
167. A. Rastinehad, J. Kruecker, C. Benjamin, P. Chung, B. Turkbey, S. Xu, J. Locklin, S. Gates, C. Buckner, and M. Linehan et al. 846 MRI/US fusion prostate biopsies: cancer detection rates J. Urol. 185 4 2011 e340
168. O. Ukimura, M. Desai, M. Aron, A. Hung, A. Berger, S. Valencerina, S. Palmer, and I. Gill 2131 Elastic registration of 3D prostate biopsy trajectory by real-time 3D TRUS with MR/TRUS fusion: pilot phatom study J. Urol. 185 4 2011 e853
169. D. Weber, G. Dipasquale, M. Rouzaud, and R. Miralbell A comparison of gross tumor volumes segmented on diagnostic MRI and planning CT with or without post-operative open low-field MR1 fusion for 3-D conformal radiotherapy of glioblastomas EJC Suppl. 3 2005 405
170. H. Xie, G. Li, H. Ning, C. Menard, C. N. Coleman, R. W. Miller, 3D voxel fusion of multi-modality medical images in a clinical treatment planning system, in: Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems, 2004, CBMS 2004, IEEE, 2004, pp. 48-53.
171. R.J. Amdur, D. Gladstone, K.A. Leopold, and R.D. Harris Prostate seed implant quality assessment using MR and CT image fusion Int. J. Rad. Oncol. Biol. Phys. 43 1 1999 67 72
172. A. Polo, F. Cattani, A. Vavassori, D. Origgi, G. Villa, H. Marsiglia, M. Bellomi, G. Tosi, O. De Cobelli, and R. Orecchia MR and CT image fusion for postimplant analysis in permanent prostate seed implants Int. J. Rad. Oncol. Biol. Phys. 60 5 2004 1572 1579
173. K.L. Maletz, R.D. Ennis, J. Ostenson, A. Pevsner, A. Kagen, and I. Wernick Comparison of CT and MR-CT fusion for prostate post-implant dosimetry Int. J. Rad. Oncol. Biol. Phys. 82 5 2012 1912 1917
174. B. Hadaschik, T. Kuru, C. Tulea, D. Teber, J. Huber, V. Popeneciu, S. Pahernik, H.-P. Schlemmer, and M. Hohenfellner 2304 Stereotactic prostate biopsy with pre-interventional MRI and live us fusion J. Urol. 185 4 2011 e924
175. Z.-S. Xiao, C.-X. Zheng, Medical image fusion based on the structure similarity match measure, in: International Conference on Measuring Technology and Mechatronics Automation, 2009, ICMTMA'09, vol. 1, IEEE, 2009, pp. 491-494.
176. A. M. Eldeib, S. M. Yamany, A. Farag, Multi-modal medical volumes fusion by surface matching, in: Proceedings of the Fifth International Symposium on Signal Processing and its Applications, 1999, ISSPA'99, vol. 1, IEEE, 1999, pp. 439-442.
177. A.A. Farag, S.M. Yamany, J. Nett, T. Moriarty, A. El-Baz, S. Hushek, and R. Falk Medical image registration: theory, algorithm, and case studies in surgical simulation, chest cancer, and multiple sclerosis Handbook of Biomedical Image Analysis 2005 Springer 1 46
178. M.C. Erie, C.H. Chu, and R.D. Sidman Visualization of the cortical potential field by medical imaging data fusion Visual Information and Information Systems 1999 Springer 815 822
179. M. Uematsu, A. Shioda, A. Suda, K. Tahara, T. Kojima, Y. Hama, M. Kono, J.R. Wong, T. Fukui, and S. Kusano Intrafractional tumor position stability during computed tomography (CT)-guided frameless stereotactic radiation therapy for lung or liver cancers with a fusion of CT and linear accelerator (focal) unit Int. J. Rad. Oncol. Biol. Phys. 48 2 2000 443 448
180. C.P. Behrenbruch, K. Marias, P.A. Armitage, M. Yam, N. Moore, R.E. English, and J.M. Brady MRI-mammography 2D/3D data fusion for breast pathology assessment Medical Image Computing and Computer-Assisted Intervention-MICCAI 2000 2000 Springer 307 316
181. K. G. Baum, K. Raerty, M. Helguera, E. Schmidt, Investigation of PET/MRI image fusion schemes for enhanced breast cancer diagnosis, in: Nuclear Science Symposium Conference Record, 2007, NSS'07, vol. 5, IEEE, 2007, pp. 3774-3780.
182. G.M. Duarte, G.H. Telles, S.T. Bianchessi, S.R. Segala, M.d.C.L. de Lima, E.C.S. de Camargo Etchebehere, and E. Tinois et al. Fusion of magnetic resonance and scintimammography images for breast cancer evaluation: a pilot study Ann. Surg. Oncol. 14 10 2007 2903 2910
183. D. Dey, D.G. Gobbi, P.J. Slomka, K.J. Surry, and T.M. Peters Automatic fusion of freehand endoscopic brain images to three-dimensional surfaces: creating stereoscopic panoramas IEEE Trans. Med. Imag. 21 1 2002 23 30
184. A. W. Wetzel, G. L. Nieder, G. Durka-Pelok, T. R. Gest, S. M. Pomerantz, D. Nave, S. Czanner, L. Wagner, E. Shirey, D. W. Deerfield, Photo-realistic representation of anatomical structures for medical education by fusion of volumetric and surface image data, in: Proceedings of the 32nd Applied Imagery Pattern Recognition Workshop, 2003, IEEE, 2003, pp. 131-138.
185. M. Aguilar, J. R. New, E. Hasanbelliu, Advances in the use of neurophysiologycally-based fusion for visualization and pattern recognition of medical imagery, in: Proceedings of the Sixth International Conference on Information Fusion, vol. 2, 2003, pp. 860-867.
186. C.-H. Huang, C.-F. Jiang, W.-H. Sung, Medical image registration and fusion with 3D CT and MR data of head, in: 19th IEEE International Symposium on Computer-Based Medical Systems, 2006, CBMS 2006, IEEE, 2006, pp. 401-404.
187. C.-C. Tsai, C.-S. Tsai, K.-K. Ng, C.-H. Lai, S. Hsueh, P.-F. Kao, T.-C. Chang, J.-H. Hong, and T.-C. Yen The impact of image fusion in resolving discrepant findings between FDG-PET and MRI/CT in patients with gynaecological cancers Euro. J. Nucl. Med. Mole. Imag. 30 12 2003 1674 1683
188. E. Zacharaki, G. Matsopoulos, K. Nikita, G. Stamatakos, An application of multimodal image registration and fusion in a 3D tumor simulation model, in: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2003, vol. 1, IEEE, 2003, pp. 686-689.
189. T. Nishioka, H. Shirato, T. Karo, Y. Watanabe, A. Yamazaki, K. Ohmori, H. Aoyama, T. Shiga, E. Sukamoto, S. Hashimoto, K. Tsuchiya, and K. Miyasaka Impact of 18FDG-PET and CT/MRI image fusion in radiotherapy planning of head-and-neck tumors Int. J. Rad. Oncol. Biol. Phys. 48 3 2000 260 261
190. W. Birkfellner, E. Schwameis, F. Vorbeck, R. Hanel, W. Greimel, J. Hummel, M. Figl, F. Kainberger, H. Imhof, and R. Kotz et al. Fusion of MR and CT scans of the pelvis in cases of malignant bone tumors International Congress Series vol. 1230 2001 Elsevier 1207 1208
191. M. Ghilezan, D. Yan, D. Lockman, D. Jaray, M. Oldham, F. Vicini, R. Matter, J. Wong, and A. Martinez Can the anatomical location of the prostatic neurovascular bundle and the penile bulb be reliably determined for the purpose of online nerve-sparing image-guided radiation therapy in prostate cancer? An MR-CT 3D fusion imaging study Int. J. Rad. Oncol. Biol. Phys. 57 2 2003 S332
192. T. Coyne, P. Silburn, R. Cook, P. Silberstein, G. Mellick, F. Sinclair, G. Fracchia, D. Wasson, and P. Stanwell Rapid subthalamic nucleus deep brain stimulation lead placement utilising CT/MRI fusion, microelectrode recording and test stimulation Advances in Functional and Reparative Neurosurgery 2006 Springer 49 50
193. S.F. Nemec, M.A. Donat, S. Mehrain, K. Friedrich, C. Krestan, C. Matula, H. Imhof, and C. Czerny CT-MR image data fusion for computer assisted navigated neurosurgery of temporal bone tumors Euro. J. Radiol. 62 2 2007 192 198
194. K. Ohtakara, O. Tanaka, S. Hayashi, M. Matsuo, M. Nakano, H. Uno, S. Okada, T. Deguchi, and H. Hoshi Effect of edema on postimplant dosimetry in prostate brachytherapy using CT/MRI fusion Int. J. Rad. Oncol. Biol. Phys. 69 3 2007 S730
195. J. Hao, Y. Shen, H. Xu, J. Zou, Generalized local priority based medical image fusion scheme, in: Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009, IIH-MSP'09, IEEE, 2009, pp. 969-972.
196. S.V. Miranda, M. Carrasco, and J. Pachon Procedure of high precision fusion of CT-MRI images for head-neck cancer with new antenna frame Radioth. Oncol. 98 2011 S41
197. A.L. Grosu, W.A. Weber, M. Franz, S. Stark, M. Piert, R. Thamm, H. Gumprecht, M. Schwaiger, M. Molls, and C. Nieder Reirradiation of recurrent high-grade gliomas using amino acid PET (SPECT)/CT/MRI image fusion to determine gross tumor volume for stereotactic fractionated radiotherapy Int. J. Rad. Oncol. Biol. Phys. 63 2 2005 511 519
198. V. Megalooikonomou, and D. Kontos Medical data fusion for telemedicine Eng. Med. Biol. Magaz., IEEE 26 5 2007 36 42
199. S.-K. Kim, H.J. Choi, S.-Y. Park, H.-Y. Lee, S.-S. Seo, C.W. Yoo, D.C. Jung, S. Kang, and K.-S. Cho Additional value of MR/PET fusion compared with PET/CT in the detection of lymph node metastases in cervical cancer patients Euro. J. Can. 45 12 2009 2103 2109
200. N. Tomura, O. Watanabe, K. Omachi, I. Sakuma, S. Takahashi, T. Otani, H. Kidani, and J. Watarai Image fusion of thallium-201 SPECT and MR imaging for the assessment of recurrent head and neck tumors following flap reconstructive surgery Euro. Radiol. 14 7 2004 1249 1254
201. O. Israel, Z. Keidar, G. Iosilevsky, L. Bettman, J. Sachs, and A. Frenkel The fusion of anatomic and physiologic imaging in the management of patients with cancer Seminars in nuclear medicine vol. 31 2001 Elsevier 191 205
202. C. Beneder, F. Fuechsel, T. Krause, A. Kuhn, and M. Mueller The role of 3D fusion imaging in sentinel lymphadenectomy for vulvar cancer Gynecol. Oncol. 109 1 2008 76 80
203. M. Infanger, V. Meyer, W. Jaeck, H. Steinert, and G.V. Schulthess Positron emission-tomography (PET) with 18-flurodeoxy-d-glucose (FDP) for staging desmiod tumours (MRI/PET image fusion) J. Hand Surg. British & European 22 Suppl. 1 1997 48
204. A. Malesci, L. Balzarini, A. Chiti, and G. Lucignani Pancreatic cancer or chronic pancreatitis? an answer from PET/MRI image fusion Euro. J. Nucl. Med. Mol. Imag. 31 9 2004 1352
205. H. Lee, and H. Hong Hybrid surface-and voxel-based registration for MR-PET brain fusion Image Analysis and Processing-ICIAP 2005 2005 Springer 930 937
206. Y. Nakamoto, K. Tamai, T. Saga, T. Higashi, T. Hara, T. Suga, T. Koyama, and K. Togashi Clinical value of image fusion from MR and PET in patients with head and neck cancer Mole. Imag. Biol. 11 1 2009 46 53
207. K. Yuan, W. Liu, S. Jia, P. Xiao, Fusion of MRI and DTI to assist the treatment solution of brain tumor, in: Second International Conference on Innovative Computing, Information and Control, 2007, ICICIC'07, IEEE, 2007, pp. 620-620.
208. F. Lindseth, S. Ommedal, J. Bang, G. Unsgard, and T. Nagelhus Hernes Image fusion of ultrasound and MRI as an aid for assessing anatomical shifts and improving overview and interpretation in ultrasound-guided neurosurgery International Congress Series vol. 1230 2001 Elsevier 254 260
209. R. Narayanan, L. Li, J. Kurhanewicz, K. Shinohara, N. Nadkar, D. Crawford, A. Barqawi, A. Simoneau, and J. Suri Improved prostate biopsy planning with MRI/TRUS fusion Euro. Urol. Suppl. 8 4 2009 353
210. M. Uematsu, A. Shioda, H. Taira, Y. Hama, A. Suda, J. Wong, and S. Kusano Interfractional movements of the prostate detected by daily computed tomography (CT)-guided precise positioning system with a fusion of CT and linear accelerator (focal) unit Int. J. Rad. Oncol. Biol. Phys. 54 2 2002 13
211. H. Fukunaga, I. Higuchi, M. Yasui, I. Seshimo, and O. Takayama Fusion image of positron emission tomography and computed tomography for the diagnosis of local recurrence of rectal cancer Ann. Surg. Oncol. 12 7 2005 561 569
212. R. Cambria, F. Cattani, M. Ciocca, C. Garibaldi, G. Tosi, and R. Orecchia CT image fusion as a tool to measure the 3D setup errors during conformal radiotherapy for prostate cancer Tumori 92 2 2006 118 123
213. R.J. Ellis, H. Zhou, D.A. Kaminsky, P. Fu, E.Y. Kim, D.B. Sodee, V. Colussi, J.P. Spirnak, C.C. Whalen, and M.I. Resnick Rectal morbidity after permanent prostate brachytherapy with dose escalation to biologic target volumes identified by SPECT/CT fusion Brachytherapy 6 2 2007 149 156
214. A.P. Pecking SPECT-CT fusion imaging radionuclide lymphoscintigraphy: potential for limb lymphedema assessment and sentinel node detection in breast cancer Cancer Metastasis and the Lymphovascular System: Basis for Rational Therapy 2007 Springer 79 84
215. J.L. Alberini, M. Wartski, V. Edeline, S. Banayan, and A.P. Pecking Molecular imaging of neuroendocrine cancer by fusion SPET/CT From Local Invasion to Metastatic Cancer 2009 Springer 169 175
216. K.-P. Lin, and W.-J. Yao A SPECT-CT image fusion technique for diagnosis of head-neck cancer IEEE 17th Annual Conference on Engineering in Medicine and Biology Society, 1995 vol. 1 1995 IEEE 377 378
217. A.C. Riegel, A.M. Berson, S. Destian, T. Ng, L.B. Tena, R.J. Mitnick, and P.S. Wong Variability of gross tumor volume delineation in head-and-neck cancer using CT and PET/CT fusion Int. J. Rad. Oncol. Biol. Phys. 65 3 2006 726 732
218. M. Feichtinger, R.M. Aigner, and H. Karcher F-18 positron emission tomography and computed tomography image-fusion for image-guided detection of local recurrence in patients with head and neck cancer using a 3-dimensional navigation system: a preliminary report J. Oral Maxillofac. Surg. 66 1 2008 193 200
219. A.M. Berson, N.F. Stein, A.C. Riegel, S. Destian, T. Ng, L.B. Tena, R.J. Mitnick, and S. Heiba Variability of gross tumor volume delineation in head-and-neck cancer using PET/CT fusion, part ii: the impact of a contouring protocol Med. Dosi. 34 1 2009 30 35
220. C. Anderson, M. Koshy, C. Staley, N. Esiashvili, S. Ghavidel, Z. Fowler, T. Fox, F. Esteves, J. Landry, and K. Godette PET-CT fusion in radiation management of patients with anorectal tumors Int. J. Rad. Oncol. Biol. Phys. 69 1 2007 155 162
221. S. Katyal, E.L. Kramer, M.E. Noz, D. McCauley, A. Chachoua, and A. Steinfeld Fusion of immunoscintigraphy single photon emission computed tomography (SPECT) with CT of the chest in patients with non-small cell lung cancer Canc. Res. 55 23 Supplement 1995 5759s 5763s
222. J.F. Vansteenkiste, S.G. Stroobants, P.J. Dupont, P.R. De Leyn, W.F. De Wever, E.K. Verbeken, J.L. Nuyts, F.P. Maes, and J.G. Bogaert FDG-PET scan in potentially operable non-small cell lung cancer: do anatometabolic PET-CT fusion images improve the localisation of regional lymph node metastases? Euro. J. Nucl. Med. 25 11 1998 1495 1501
223. M. Schmuecking, K. Plichta, E. Lopatta, C. Przetak, J. Leonhardi, D. Gottschild, T. Wendt, and R. Baum Image fusion of f-18 FDG PET and CT.-is there a role in 3D-radiation treatment planning of non-small cell lung cancer? Int. J. Rad. Oncol. Biol. Phys. 48 3 2000 130
224. P. Giraud, D. Grahek, F. Montravers, M.-F. Carette, E. Deniaud-Alexandre, F. Julia, J.-C. Rosenwald, J.-M. Cosset, J.-N. Talbot, and M. Housset et al. CT and 18 F-deoxyglucose (FDG) image fusion for optimization of conformal radiotherapy of lung cancers Int. J. Rad. Oncol. Biol. Phys. 49 5 2001 1249 1257
225. J. Wong, S. Grimm, M. Chow, M. Uematsu, R. Oren, A. Scher, C. Wilson, P. Schi, and A. Fung Shallow breathing control with 100 (fusion of CT and LINAC) treatment in frameless fractionated stereotactic radiotherapy for lung cancer Radioth. Oncol. 64 2002 S261
226. E. Deniaud-Alexandre, E. Touboul, D. Lerouge, D. Grahek, J.-N. Foulquier, Y. Petegnief, B. Gres, H. El Balaa, K. Keraudy, and K. Kerrou et al. Impact of computed tomography and 18 F-deoxyglucose coincidence detection emission tomography image fusion for optimization of conformal radiotherapy in non-small-cell lung cancer Int. J. Rad. Oncol. Biol. Phys. 63 5 2005 1432 1441
227. W. Ge, G. Yuan, C. Li, Y. Wu, Y. Zhang, and X. Xu CT image fusion in the evaluation of radiation treatment planning for non-small cell lung cancer Chin.-Ger. J. Clin. Oncol. 7 6 2008 315 318
228. A. Kovacs, J. Hadjiev, F. Lakosi, G. Antal, G. Liposits, and P. Bogner 119P tumor movements detected by multi-slice CT-based image fusion in the radiotherapy of lung cancer Lung Can. 64 2009 S50
229. X. Xu, J. Deng, H. Guo, M. Xiang, C. Li, L. Xu, W. Ge, G. Yuan, Q. Li, S. Shan, CT image fusion in the optimization of replanning during the course of 3-Dimensional conformal radiotherapy for non-small-cell lung cancer, in: 3rd International Conference on Biomedical Engineering and Informatics (BMEI) 2010, vol. 3, IEEE, 2010, pp. 1336-1339.
230. S. Gordon, J. DeMarco, G. Hugo, K. Boedeker, J. Smathers, R. Parker, H. Withers, and T. Solberg Evaluation of patient positioning and inter-fraction organ motion using an infrared positioning system, serial CT, and information image fusion in the treatment of prostate cancer Radioth. Oncol. 58 2001 S67 S68
231. L. Taylor, J. Beaty, J. Enderle, M. Escabi, Design of a simple ultrasound/CT fusion image fusion solution for the evaluation of prostate seed brachytherapy, in: Proceedings of the IEEE 27th Annual Northeast Bioengineering Conference, 2001, IEEE, 2001, pp. 57-58.
232. L. Taylor, B. Porter, G. Nadasdy, P. diSantagnese, D. Pasternack, E. Messing, D. Rubens, and K. Parker Three-dimensional fusion of prostate histology with sonoelastography images Ultrasound Med. Biol. 29 5 2003 S57
233. M. Krengli, M. Dominietto, S. Chiara, C. Barbara, R. Marco, I. Eugenio, K. Irvin, and B. Frea et al. Study of lymphatic drainage by SPECT-CT fusion images for pelvic irradiation of prostate cancer Int. J. Rad. Oncol. Biol. Phys. 63 2005 S305
234. D.B. Fuller, H. Jin, J.A. Koziol, and A.C. Feng CT-ultrasound fusion prostate brachytherapy: a dynamic dosimetry feedback and improvement method. A report of 54 consecutive cases Brachytherapy 4 3 2005 207 216
235. M. Krengli, A. Ballare, B. Cannillo, M. Rudoni, E. Kocjancic, G. Loi, M. Brambilla, E. Inglese, and B. Frea Potential advantage of studying the lymphatic drainage by sentinel node technique and SPECT-CT image fusion for pelvic irradiation of prostate cancer Int. J. Rad. Oncol. Biol. Phys. 66 4 2006 1100 1104
236. D.B. Sodee, A.E. Sodee, and G. Bakale Synergistic value of single-photon emission computed tomography/computed tomography fusion to radioimmunoscintigraphic imaging of prostate cancer Seminars in Nuclear Medicine vol. 37 2007 Elsevier 17 28
237. R. Hammoud, D. Pradhan, J. Kim, S. Patel, S. Kowalski, H. Guan, Y. Xu, M. Elshaikh, M. Ajlouni, and B. Movsas Prostate localization: fiducial marker versus cone beam CT (CBCT) 3D image fusion Int. J. Rad. Oncol. Biol. Phys. 69 3 2007 S679 S680
238. F. Dube, A. Mahadevan, and T. Sheldon Fusion of CT and 3D ultrasound (3dus) for prostate delineation of patients with metallic hip prostheses (MHP) Int. J. Rad. Oncol. Biol. Phys. 75 3 2009 S327 S328
239. E. Saibishkumar, D. Iupati, J. Borg, and K. Fernandes Denition and dosimetric evaluation of a clinical target volume (CTV) in the post implant (CT/MR fusion) analysis of low-dose-rate brachytherapy for prostate cancer at princess margaret hospital Brachytherapy 10 2011 S28
240. 125I-seed implant CT images to improve consistency and accuracy of post-seed implant quality statistics Brachytherapy 8 2 2009 116
241. J. Li, K. F. Koral, An algorithm to adjust a rigid CT-SPECT fusion so as to maximize tumor counts from CT Vol in I-131 therapies, in: IEEE Nuclear Science Symposium Conference Record, 2001, vol. 3, IEEE, 2001, pp. 1432-1436.
242. 111In-pentetreotide scintigraphy Rev. Espan. Med. Nucl. 24 1 2005 14 18
243. K.K. Wong, J.M. Cahill, K.A. Frey, and A.M. Avram Incremental value of 111-In pentetreotide SPECT/CT fusion imaging of neuroendocrine tumors Acad. Radiol. 17 3 2010 291 297
244. A. Riegel, M. Berson, S. Destian, T. Ng, L. Tena, R. Mitnick, and P. Wong Variability of gross tumor volume delineation in head and neck cancer using CT and PET/CT fusion Int. J. Rad. Oncol. Biol. Phys. 63 2005 S142 S143
245. E. Lartigau, L. Ceugnart, S. Taieb, Y. Belkacemi, D. Pasquier, E. Castellanos, T. Lacornerie, Image fusion in pelvic cancer, in: Radiotherapy and Oncology, vol. 73, 2004, pp. S76-S76.
246. T. Denecke, B. Hildebrandt, L. Lehmkuhl, N. Peters, A. Nicolaou, M. Pech, H. Riess, J. Ricke, R. Felix, and H. Amthauer Fusion imaging using a hybrid SPECT-CT camera improves port perfusion scintigraphy for control of hepatic arterial infusion of chemotherapy in colorectal cancer patients Euro. J. Nucl. Med. Mole. Imag. 32 9 2005 1003 1010
247. 18F-FDG PET/CT fusion imaging in paediatric solid extracranial tumours Biomed. Pharmaco. 60 9 2006 593 606
248. 18F-FDG PET/CT) in combination with ultrasonography for axillary staging in primary breast cancer BMC Can. 8 1 2008 165
249. 18F-FDG PET/CT) in detecting multifocality and axillary lymph node metastasis and correlation of clinicopathologic factors in primary breast cancer Euro. J. Can. Suppl. 8 3 2010 230
250. M. Feichtinger, W. Zemann, R.-M. Aigner, and H. Kaercher O. 258 3D control of resection margins in oral cancer based on PET/CT image-fusion J. Cranio-Maxillofac. Surg. 36 2008 S65
251. Z. Zhao, L. Li, F. Li, and L. Zhao Single photon emission computed tomography/spiral computed tomography fusion imaging for the diagnosis of bone metastasis in patients with known cancer Skel. Radiol. 39 2 2010 147 153
252. Y. Nakamoto, M. Senda, T. Okada, S. Sakamoto, T. Saga, T. Higashi, and K. Togashi Software-based fusion of PET and CT images for suspected recurrent lung cancer Mole. Imag. Biol. 10 3 2008 147 153
253. H. Iwase, Y. Yamamoto, T. Kawasoe, and M. Ibusuki Qs106. sentinel lymph node biopsy using SPECT-CT fusion imaging in patients with breast cancer and its clinical usefulness J. Surg. Res. 151 2 2009 287
254. A. Hakime, T. de Baere, F. Deschamps, P. Rao, A. Auperin, and E. Marques de Carvalho Clinical evaluation of spatial accuracy of a fusion imaging technique combining previously-acquired computed tomography and real time ultrasound for imaging of liver tumors J. Vasc. Interven. Radiol. 21 2 2010 S49
255. Y. Xia, S. Eberl, D. Feng, Dual-modality 3D brain PET-CT image segmentation based on probabilistic brain atlas and classification fusion, in: 17th IEEE International Conference on Image Processing (ICIP), 2010, IEEE, 2010, pp. 2557-2560.
256. A.J. Walker, B.J. Spier, S.B. Perlman, J.R. Stangl, T.J. Frick, D.V. Gopal, M.J. Lindstrom, T.L. Weigel, and P.R. Pfau Integrated PET/CT fusion imaging and endoscopic ultrasound in the pre-operative staging and evaluation of esophageal cancer Mole. Imag. Biol. 13 1 2011 166 171
257. 18F-FDG PET/MRI fusion in characterizing pancreatic tumors: comparison to PET/CT Int. J. Clin. Oncol. 16 4 2011 408 415
258. F. Kahmann, T. Henkel, A. Polo, H. Marsiglia, and P. Wust CT/MRI image fusion based postplans significantly improve the quality control after prostate seed brachytherapy Euro. J. Can. 37 2001 S220
259. B. Al-Qaisieh CT, MRI, and CT-MRI image fusion assessment for prostate I-125 post implant dosimetry Radioth. Oncol. 71 2004 S126 S127
260. N. Papanikolaou, D. Gearheart, T. Bolek, A. Meigooni, D. Meigooni, M. Mohiuddin, A volumetric and dosimetric study of LDR brachytherapy prostate implants based on image fusion of ultrasound and computed tomography, in: Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2000, vol. 4, IEEE, 2000, pp. 2769-2770.
261. E. Barranger, K. Kerrou, Y. Petegnief, E. David-Monteore, A. Cortez, and E. Darai Laparoscopic resection of occult metastasis using the combination of FDG positron emission tomography/computed tomography image fusion with intraoperative probe guidance in a woman with recurrent ovarian cancer Gynecol. Oncol. 96 1 2005 241 244
262. M. McGurk PET and CT fusion scans in the early detection and the evaluation of recurrences in head and neck tumors Oral Oncol. 1 2005 50
263. T. Shigekawa, I. Sugitani, H. Takeuchi, M. Misumi, N. Nakamiya, M. Sugiyama, N. Fujiuchi, A. Osaki, and T. Saeki Examination about the adaptation of sentinel lymph node biopsy after neoadjuvant chemotherapy using 18F-fluoro-deoxyglucose emission tomography/computed tomography fusion imaging (18F-FDG PET/CT) in breast cancer The Breast 20 1 2011 S57
264. T. Block, F. Zimmermann, H. Czempiel, TRUS- and CT-image fusion in the postplanning procedure after transperineal permanent interstitial seed implantation (TPSI) of "low risk" prostate cancer, in: Radiotherapy and Oncology, vol. 71, 2004, pp. S105-S105.
265. M. Stutz, K. Zuhlke, D. Kraable, and B. Moran Comparing apples to apples: fusion of preplan ultrasound structures and postimplant CT images for prostate brachytherapy dosimetry Int. J. Rad. Oncol. Biol. Phys. 51 3 2001 322
266. K. Yamauchi, A. Tashiro, M. Watanabe, A. Okino, T. Kohno, E. Hotta, M. Yuura, Fundamental study of proton source based on inertial electrostatic confinement fusion for medical positron emission tomography, in: The 31st IEEE International Conference on Plasma Science, 2004, ICOPS 2004, IEEE Conference Record-Abstracts, IEEE, 2004, p. 139.
267. E. Holupka, I. Kaplan, E. Burdette, and G. Svensson Ultrasound image fusion for external beam radiotherapy for prostate cancer Int. J. Rad. Oncol. Biol. Phys. 35 5 1996 975 984
268. J. Bradley, K. Bae, N. Choi, K. Forster, B. Siegel, J. Brunetti, J. Purdy, S. Faria, T. Vu, and H. Choy A phase ii comparative study of gross tumor volume definition with or without PET/CT fusion in dosimetric planning for non-small-cell lung cancer (NSCLC): primary analysis of radiation therapy oncology group (RTOG) 0515 Int. J. Rad. Oncol. Biol. Phys. 75 3 2009 S2
269. S. Kremp, A. Schaefer-Schuler, U. Nestle, C. Sebastian-Welsch, C. Rube, C. Kirsch, Comparison of CT and CT-PET-fusion based 3D treatment plans in the percutaneous radiotherapy of lung cancer, in. Radiotherapy and Oncology, vol. 73, pp. S447-S448.
270. A. Lin, K. Teo, and R. Rengan A comparative study of PET-CT fusion versus PET-CT simulation for target delineation in non-small cell lung cancer Int. J. Rad. Oncol. Biol. Phys. 78 3 2010 S543
271. J. Wolthaus, M. van Herk, S. Muller, D. Bois, M. Rossi, J. Belderbos, J. Lebesque, E. Damen, 4D PET and 4D CT image fusion for accurate radiotherapy planning of lung cancer patients, in: Radiotherapy and Oncology, vol. 73, pp. S162-S163.
272. S. Sobottka, R. Steinmeier, B. Beuthien-Baumann, D. Mucha, and G. Schackert Evaluation of automatic multimodality fusion technique of PET and MRI/CT images for computer assisted brain tumor surgery International Congress Series vol. 1230 2001 Elsevier 261 267
273. A. Grosu, C. Nieder, W. Weber, M. Franz, S. Staerk, M. Schwaiger, and M. Molls Re-irradiation of recurrent high grade gliomas using amino-acids-PET (SPECT)/CT/MRI image fusion to determine gross tumor volume for stereotactic fractionated radiotherapy Int. J. Rad. Oncol. Biol. Phys. 60 1 2004 S222
274. L. Beaulieu, D. Tubic, J. Pouliot, E. Vigneault, and R. Taschereau Post-implant dosimetry using fusion of ultrasound images with 3D seed coordinates from fluoroscopic images in transperineal interstitial permanent prostate brachytherapy Int. J. Rad. Oncol. Biol. Phys. 48 3 2000 360
275. B. C. Porter, L. Taylor, R. Baggs, A. di Sant'Agnese, G. Nadasdy, D. Pasternack, D. J. Rubens, K. J. Parker, Histology and ultrasound fusion of excised prostate tissue using surface registration, in: IEEE Ultrasonics Symposium, 2001, vol. 2, IEEE, 2001, pp. 1473-1476.
276. F. Arena, T. DiCicco, A. Anand, Multimodality data fusion aids early detection of breast cancer using conventional technology and advanced digital infrared imaging, in: 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004, IEMBS'04, vol. 1, IEEE, 2004, pp. 1170-1173.
277. C. Jiang, C. Wang, C. Chiang, Oral cancer detection in fluorescent image by color image fusion, in: 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004, IEMBS'04, vol. 1, IEEE, 2004, pp. 1260-1262.
278. L. Gong, P.S. Cho, B.H. Han, K.E. Wallner, S.G. Sutlief, S.D. Pathak, D.R. Haynor, and Y. Kim Ultrasonography and fluoroscopic fusion for prostate brachytherapy dosimetry Int. J. Rad. Oncol. Biol. Phys. 54 5 2002 1322 1330
279. I. Aslay, G. Kemikler, N. Tenekeci, I. Ozbay, M. Akinci, The benefits provided by using intra-operative dosimetry and the fusion of MRI to CT for post plan dosimetry in the learning curve of transperineal interstitial permanent prostate brachytherapy, in: Radiotherapy and Oncology, vol. 71, 2004, pp. S93-S93.
280. Y. Chen, E. Gunawan, Y. Kim, K. Low, C. Soh, UWB microwave imaging for breast cancer detection: tumor/clutter identification using a time of arrival data fusion method, in: IEEE Antennas and Propagation Society International Symposium 2006, IEEE, 2006, pp. 255-258.
281. Y. Chen, E. Gunawan, K.S. Low, S.-C. Wang, C.B. Soh, and L.L. Thi Time of arrival data fusion method for two-dimensional ultrawideband breast cancer detection IEEE Trans. Anten. Propag. 55 10 2007 2852 2865
282. G. Lv, A. He, X. Yang, X. Ning, Fusion of medical microscopic images based on estimation and compensation, in: IEEE/ICME International Conference on Complex Medical Engineering, 2007, CME 2007, IEEE, 2007, pp. 736-739.
283. G. Lan, M. Xiu-ming, Multi-level classifier design for tumor micro-image based on multi-feature fusion, in: International Seminar on Future BioMedical Information Engineering, 2008, FBIE'08, IEEE, 2008, pp. 60-63.
284. S. Daneshvar, H. Ghassemian, A feedback retina model for improving medical images fusion, in: 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008, EMBS 2008, IEEE, 2008, pp. 4035-4038.
285. M. Wozniak Information fusion for probabilistic reasoning and its application to the medical decision support systems Computational Science and its Applications-ICCSA 2004 2004 Springer 593 601
286. Y. Hu, D. Morgan, H.U. Ahmed, D. PendsÍe, M. Sahu, C. Allen, M. Emberton, D. Hawkes, and D. Barratt A statistical motion model based on biomechanical simulations for data fusion during image-guided prostate interventions Medical Image Computing and Computer-Assisted Intervention-MICCAI 2008 2008 Springer 737 744
287. M. Dietzel, T. Hopp, N. Ruiter, R. Zoubi, I.B. Runnebaum, W.A. Kaiser, and P.A. Baltzer Fusion of dynamic contrast-enhanced magnetic resonance mammography at 3.0T with X-ray mammograms: Pilot study evaluation using dedicated semi-automatic registration software Euro. J. Radiol. 79 2 2011 e98 e102
288. K.G. Baum, M. Helguera, and A. Krol Fusion viewer: a new tool for fusion and visualization of multimodal medical data sets J. Dig. Imag. 21 1 2008 59 68
289. A. Viola, T. Major, and J. Julow The importance of postoperative CT image fusion verification of stereotactic interstitial irradiation for brain tumors Int. J. Rad. Oncol. Biol. Phys. 60 1 2004 322 328
290. H. Eldredge, A. Doemer, D. Friedman, and M. Werner-Wasik Improvement in optic chiasm contouring for RT planning in patients with brain tumors using CT/MP-RAGE MRI fusion as compared to the routine T1-weighted MRI image Int. J. Rad. Oncol. Biol. Phys. 75 3 2009 S246
291. A. Villeger, L. Ouchchane, J.-J. Lemaire, J.-Y. Boire, Assistance to planning in deep brain stimulation: data fusion method for locating anatomical targets in MRI, in: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, EMBS'06, IEEE, 2006, pp. 144-147.
292. W. Dou, A. Dong, P. Chi, S. Li, J.-M. Constans, Brain tumor segmentation through data fusion of T2-weighted image and MR spectroscopy, in: 5th International Conference on Bioinformatics and Biomedical Engineering, (iCBBE), 2011, IEEE, 2011, pp. 1-4.
293. D.M. Tucker, and P. Luu Operational brain dynamics: data fusion technology for neurophysiological, behavioral, and scenario context information in operational environments Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience 2009 Springer 98 104
294. M. Ganna, M. Rombaut, R. Goutte, Y. Zhu, Improvement of brain lesions detection using information fusion approach, in: 6th International Conference on Signal Processing, 2002, vol. 2, IEEE, 2002, pp. 1104-1107.
295. L. Gupta, B. Chung, M.D. Srinath, D.L. Molfese, and H. Kook Multichannel fusion models for the parametric classification of differential brain activity IEEE Trans. Biomed. Eng. 52 11 2005 1869 1881
296. H. Kook, L. Gupta, S. Kota, D. Molfese, A dynamic multi-channel decision-fusion strategy to classify differential brain activity, in: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, EMBS 2007, IEEE, 2007, pp. 3212-3215.
297. A. Vaccarella, E. De Momi, A. Enquobahrie, and G. Ferrigno Unscented Kalman Filter Based Sensor Fusion for Robust Optical and Electromagnetic Tracking in Surgical Navigation Instrumentation and Measurement, IEEE Transactions on 62 2013 2067 2081
298. R. Velik, D. Bruckner, R. Lang, and T. Deutsch Emulating the perceptual system of the brain for the purpose of sensor fusion Human-Computer Systems Interaction 2009 Springer 17 27
299. R. Polikar, A. Topalis, D. Parikh, D. Green, J. Frymiare, J. Kounios, and C.M. Clark An ensemble based data fusion approach for early diagnosis of Alzheimer's disease Inform. Fus. 9 1 2008 83 95
300. K. P. Thomas, C. Guan, L. C. Tong, A. P. Vinod, Discriminative filterbank selection and EEG information fusion for brain computer interface, in: IEEE International Symposium on Circuits and Systems, 2009, ISCAS 2009, IEEE, 2009, pp. 1469-1472.
301. V. Metsis, H. Huang, F. Makedon, and A. Tzika Heterogeneous data fusion to type brain tumor biopsies Artificial Intelligence Applications and Innovations III 2009 Springer 233 240
302. R. Leeb, H. Sagha, R. Chavarriaga, J. del R Millan, Multimodal fusion of muscle and brain signals for a hybrid-BCI, in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2010, IEEE, 2010, pp. 4343-4346.
303. C. Cabral, M. Silveira, and P. Figueiredo Decoding visual brain states from FMRI using an ensemble of classifiers Patt. Recog. 45 6 2012 2064 2074
304. T.M. Rutkowski, A. Cichocki, and D. Mandic Information fusion for perceptual feedback: A brain activity sonification approach Signal Processing Techniques for Knowledge Extraction and Information Fusion 2008 Springer 261 273
305. Y.M. Kirova, V. Servois, F. Reyal, D. Peurien, A. Fourquet, and N. Fournier-Bidoz Use of deformable image fusion to allow better definition of tumor bed boost volume after oncoplastic breast surgery Surg. Oncol. 20 2 2011 e123 e125
306. J. L. Jesneck, S. Mukherjee, L. W. Nolte, A. E. Lokshin, J. R. Marks, J. Lo, Decision fusion of circulating markers for breast cancer detection in premenopausal women, in: Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, 2007, BIBE 2007, IEEE, 2007, pp. 1434-1438.
307. T. Wurm, K. Eichhorn, S. Corvin, A. Anastasiadis, R. Bares, and A. Stenzl 549 anatomic-functional image fusion allows intraoperative sentinel node detection in prostate cancer patients Euro. Urol. Suppl. 3 2 2004 140
308. M. Moerland, I. Jurgenliemk-Schulz, J. Battermann, Fusion of pre-implant MRI and intra-operative us images for planning of permanentprostate implants. in: Radiotherapy and Oncology, vol. 75, 2005, pp. S38-S38.
309. R.J. Ellis, D.A. Kaminsky, H. Zhou, and M.I. Resnick Erectile dysfunction following permanent prostate brachytherapy with dose escalation to biological tumor volumes (BTVS) identified with SPECT/CT fusion Brachytherapy 6 2 2007 103
310. A. Hervas, R. Moris, A. Montero, I. Rodriguez, S. Sancho, J. Delgado, R. Morera, M. Bejarano, A. Capuz, and A. Ramos Image-fusion based CT pre and post-implant in seed implantation: a useful tool for accurate prostate definition in the post-planning setting Radioth. Oncol. v71 Suppl. 2 2004 S107
311. S. Germano, M. Santos, T. Almeida, C. Miguel, I. Grillo, CT image fusion to evaluate prostate gland motion and volume change between planning CT and repeat CT after four weeks of external radiotherapy treatment, Radioth. Oncol. 73 (2004) S399-S399.
312. Y. Hu, T.J. Carter, H.U. Ahmed, M. Emberton, C. Allen, D.J. Hawkes, and D.C. Barratt Modelling prostate motion for data fusion during image-guided interventions IEEE Trans. Med. Imag. 30 11 2011 1887 1900
313. J. Bradley, K. Bae, N. Choi, K. Forster, B.A. Siegel, J. Brunetti, J. Purdy, S. Faria, T. Vu, and W. Thorstad et al. A phase ii comparative study of gross tumor volume definition with or without PET/CT fusion in dosimetric planning for non-small-cell lung cancer (NSCLC): Primary analysis of radiation therapy oncology group (RTOG) 0515 Int. J. Rad. Oncol. Biol. Phys. 82 1 2012 435 441
314. 18FDG-hybrid PET fusion Int. J. Rad. Oncol. Biol. Phys. 48 3 2000 128 129
315. 18F-deoxyglucose-hybrid positron emission tomography image fusion on conformal radiotherapy in non-small cell lung cancer Int. J. Rad. Oncol. Biol. Phys. 63 2005 S102
316. C. Liu, L. Kong, W. Zhong, J. Zhu, D. Xia, Multi-information fusion based tumor cell of bone marrow involvement, in: Proceedings of the International Workshop on Medical Imaging and Augmented Reality, 2001, IEEE, 2001, pp. 211-215.
317. K.C. Wong, S.M. Kumta, G.E. Antonio, and L.F. Tse Image fusion for computer-assisted bone tumor surgery Clin. Orthopaed. Related Res. 466 10 2008 2533 2541
318. K. Nakajo, M. Tatsumi, A. Inoue, K. Isohashi, I. Higuchi, H. Kato, M. Imaizumi, T. Enomoto, E. Shimosegawa, and T. Kimura et al. Diagnostic performance of fluorodeoxyglucose positron emission tomography/magnetic resonance imaging fusion images of gynecological malignant tumors: comparison with positron emission tomography/computed tomography Japan. J. Radiol. 28 2 2010 95 100
319. W. Ye, D.J. Isaman, and J. Barhak Use of secondary data to estimate instantaneous model parameters of diabetic heart disease: lemonade method Inform. Fus. 13 2 2012 137 145
320. R. Teodorescu, C. Cernazanu-Glavan, V. Cretu, D. Racoceanu, The use of the medical ontology for a semantic-based fusion system in biomedical informatics application to Alzheimer's disease, in: 4th International Conference on Intelligent Computer Communication and Processing, 2008, ICCP 2008, IEEE, 2008, pp. 265-268.