Automation of Hessian-based tubularity measure response function in 3d biomedical images

International Journal of Biomedical Imaging

Volumn 2011, Issue , 2011, Pages

  Ritman, Erik L ^a   Dzyubak, Oleksandr P ^a  

^a MAYO GRADUATE SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMEDICAL IMAGES; EXPONENTIAL INCREASE; IMAGE PROCESSING LIBRARIES; IMAGERS; INSIGHT SEGMENTATION AND REGISTRATION TOOLKITS; LARGE IMAGES; MANUAL TRACKING; MULTISCALE FRAMEWORK; MULTISCALES; NATIONAL LIBRARY OF MEDICINES; OBJECT SHAPE; RESPONSE FUNCTIONS; SCALE-5; TUBULAR OBJECTS;

BLOOD VESSELS; IMAGE SEGMENTATION; MATRIX ALGEBRA; MICROCIRCULATION;

THREE DIMENSIONAL;

EID: 79955009107     PISSN: 16874188     EISSN: 16874196     Source Type: Journal    
DOI: 10.1155/2011/920401     Document Type: Article

References (93)

1. Marr D., Vision: A Computational Investigation into the Human Representation and Processing of Visual Information 2010 Cambridge, MA, USA The MIT Press
2. ter Haar Romeny B. M., Front-End Vision and Multi-Scale Image Analysis: Multi-scale Computer Vision Theory and Applications, Written in Mathematica 2003 1st Berlin, Germany Springer
3. Witkin A. P., Scale-space filtering Proceedings of the 8th International Joint Conference on Artificial Intelligence 1983 Karlsruhe, Germany 1019 1022
4. Koenderink J. J., The structure of images Biological Cybernetics 1984 50 5 363 370 (Pubitemid 14070727)
5. Hummel R. A., Fischler M. A., Firschein O., Representations based on zero-crossings in scale-space Readings in Computer Vision: Issues, Problems, Principles, and Paradigms 1987 Los Altos, Calif, USA Morgan Kaufmann 753 758
6. Yuille A. L., Poggio T. A., Scaling theorems for zero-crossings IEEE Transactions on Pattern Analysis and Machine Intelligence 1986 8 1 15 25
7. Koenderink J. J., van Doorn A. J., Generic neighborhood operators IEEE Transactions on Pattern Analysis and Machine Intelligence 1992 14 6 597 605
8. Florack M. J., The syntactical structure of scalar images, Ph.D. thesis 1993 Utrecht, Netherlands Department of Medical Physics, Utrecht University
9. Lindeberg T., Scale-space for discrete signals IEEE Transactions on Pattern Analysis and Machine Intelligence 1990 12 3 234 254 (Pubitemid 20677933)
10. Lindeberg T., Scale-Space Theory in Computer Vision 1994 Dordrecht, The Netherlands Kluwer Academic Publishers
11. Koenderink J. J., Scale-time Biological Cybernetics 1988 58 3 159 162
12. Lindeberg T., Fagerstrm D., Buxton B., Cipolla R., Scale-space with casual time direction 1 Proceedings of the 4th European Conference on Computer Vision (ECCV '96) 1996 Cambridge, UK 229 240
13. Lindeberg T., ter Haar Romeny B. M., Florack L., Koenderink J., Viergever M., Linear spatio-temporal scale-space Proceedings of the First International Conference on Scale-Space Theory in Computer Vision (Scale-Space '97) 1997 1st Berlin, Germany Springer 113 127 (Pubitemid 127097435)
14. Perona P., Malik J., Scale-space and edge detection using anisotropic diffusion IEEE Transactions on Pattern Analysis and Machine Intelligence 1990 12 7 629 639 (Pubitemid 20726016)
15. Weickert J., Buxton B., Cipolla R., A review of nonlinear diffusion filtering Proceedings of the First International Conference on Scale-Space Theory in Computer Vision (Scale-Space '97) 1997 Springer 3 28 (Pubitemid 127097428)
16. Florack L. M. J., Salden A. H., ter Haar Romeny B. M., Koenderink J. J., Viergever M. A., Nonlinear scale-space Image and Vision Computing 1995 13 4 279 294
17. Burgeth B., Didas S., Weickert J., Olsen O. F., Florack L., Kuijper A., The Bessel Scale-Space 3753 Proceedings of the 1st International Workshop Deep Structure, Singularities, and Computer Vision (DSSCV '05) June 2005 Maastricht, The Netherlands Springer 84 95 Lecture Notes in Computer Science
18. Heil C., Walnut D. F., Fundamental Papers in Wavelet Theory 2006 Princeton University Press
19. Mallat S., Hwang W. L., Singularity detection and processing with wavelets IEEE Transactions on Information Theory 1992 38 2 617 643
20. Doering D., Schuck A., A novel method for generating scale space kernels based on wavelet theory Revista de Informtica Terica e Aplicada 2008 15 2 121 137
21. Vu T. T., Tokunaga M., Wavelet and scale-space theory in segmentation of airborne laser scanner data 1 Proceedings of the 22nd Asian Conference on Remote Sensing (ACRS '01) November 2001 Singapore 176 180
22. Ferdman Y., Sagiv C., Sochen N., Sgallari F., Murli A., Paragios N., Full affine wavelets are scale-space with twist Proceedings of the 1st International Conference on Scale-Space and Variational Methods in Computer Vision (SSVM '07) June 2007 Ischia, Italy Springer 1 12
23. Wang YU. P., Lee S. L., Scale-space derived from B-splines IEEE Transactions on Pattern Analysis and Machine Intelligence 1998 20 10 1040 1055 (Pubitemid 128741364)
24. Babaud J., Witkin A. P., Baudin M., Duda R. O., Uniqueness of the Gaussian kernel for scale-space filtering IEEE Transactions on Pattern Analysis and Machine Intelligence 1986 8 1 26 33 (Pubitemid 16575716)
25. Florack L. M. J., ter Haar Romeny B. M., Koenderink J. J., Viergever M. A., Scale and the differential structure of images Image and Vision Computing 1992 10 6 376 388
26. Florack L. M. J., ter Haar Romeny B. M., Koenderink J. J., Viergever M. A., Linear scale-space Journal of Mathematical Imaging and Vision 1994 4 4 325 351
27. Duits R., Florack L., De Graaf J., Ter Haar Romeny B., On the axioms of scale space theory Journal of Mathematical Imaging and Vision 2004 20 3 267 298
28. Wennekers T., Suder K., Fitting of spatio-temporal receptive fields by sums of Gaussian components Neurocomputing 2004 5860 929 934 (Pubitemid 38684353)
29. Young R. A., The Gaussian derivative model for spatial vision: I. Retinal mechanisms Spatial Vision 1987 2 4 273 293
30. Young R. A., Lesperance R. M., Meyer W. W., The Gaussian derivative model for spatial-temporal vision: I. Cortical model Spatial Vision 2001 14 3-4 261 319 (Pubitemid 34079507)
31. Young R. A., Lesperance R. M., The Gaussian derivative model for spatial-temporal vision: II. Cortical data Spatial Vision 2001 14 3-4 321 389 (Pubitemid 34079508)
32. Lindeberg T., Feature detection with automatic scale selection International Journal of Computer Vision 1998 30 2 79 116 (Pubitemid 128517917)
33. Lindeberg T., Scale-space theory: a basic tool for analyzing structures at different scales Journal of Applied Statistics 1994 21 2 225 270
34. Lindeberg T., Edge detection and ridge detection with automatic scale selection International Journal of Computer Vision 1998 30 2 117 154 (Pubitemid 128517918)
35. Marr D., Early processing of visual information Philosophical transactions of the Royal Society of London B 1976 275 942 483 519
36. Marr D., Hildreth E., Theory of edge detection Proceedings of the Royal Society of London 1980 207 1167 187 217 (Pubitemid 10103608)
37. Canny J., A computational approach to edge detection IEEE Transactions on Pattern Analysis and Machine Intelligence 1986 8 6 679 698
38. Majer P., Kerckhove M., The influence of the gamma-parameter on feature detection with automatic scale Selection Proceedings of the 3rd International Conference on Scale-Space and Morphology in Computer Vision 2001 Springer 245 254 (Pubitemid 33303186)
39. Majer P., On the influence of scale selection on feature detection for the case of linelike structures International Journal of Computer Vision 2004 60 3 191 202
40. Lorenz C., Carlsen I.-C., Buzug T.-M., Fassnacht C., Weese J., ter Haar Romeny B. M., Florack L., Koenderink J., Viergever M., A multi-scale line filter with automatic scale selection based on the Hessian matrix for medical image segmentation Proceedings of the First International Conference on Scale-Space Theory in Computer Vision (Scale-Space '97) 1997 Springer 152 163 (Pubitemid 127097438)
41. Ritman E. L., Micro-computed tomographycurrent status and developments Annual Review of Biomedical Engineering 2004 6 185 208
42. Faridani A., Ritman E. L., High-resolution computed tomography from efficient sampling Inverse Problems 2000 16 3 635 650
43. Witt S. T., Riedel C. H., Goessl M., Chmelik M. S., Ritman E. L., Point spread function deconvolution in 3D micro-CT angiography for multiscale vascular tree separation 5030 Physics of Medical Imaging 2003 720 727 Proceedings of SPIE
44. Kundur D., Hatzinakos D., Blind image deconvolution IEEE Signal Processing Magazine 1996 13 3 43 64 (Pubitemid 126518975)
45. Koller T. M., Gerig G., Szekely G., Dettwiler D., Grimson E., Shafer S., Blake A., Sugihara K., Multiscale detection of curvilinear structures in 2-D and 3-D image data Proceedings of 15th International Conference on Computer Vision (ICCV '95) 1995 Springer 864 869
46. ter Haar Romeny B. M., Florack L., Koenderink J., Viergever M., Scale-Space Theory in Computer Vision 1997 1st Berlin, Germany Springer
47. Kimmel R., Suchen N., Weickert J., Scale Space and PDE Methods in Computer Vision 2005 1st Berlin, Germany Springer
48. Aylward S. R., Bullitt E., Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction IEEE Transactions on Medical Imaging 2002 21 2 61 75 (Pubitemid 34466421)
49. Sato Y., Nakajima S., Atsumi H., Troccaz J., Grimson E., Mosges R., 3D multi-scale line filter for segmentation and visualization of curvilinear structures in medical images Proceedings of the 1st Joint Conference Computer Vision, Virtual Reality and Robotics in Medicine and Medical Robotics and Computer-Assisted Surgery Grenoble (CVRMed-MRCAS '97) 1997 Springer 213 222 (Pubitemid 127045554)
50. Sato Y., Nakajima S., Shiraga N., Atsumi H., Yoshida S., Koller T., Gerig G., Kikinis R., Three-dimensional multi-scale line filter for segmentation and visualization of curvilinear structures in medical images Medical Image Analysis 1998 2 2 143 168 (Pubitemid 128501135)
51. Sato Y., Westin C. F., Bhalerao A., Nakajima S., Shiraga N., Tamura S., Kikinis R., Tissue classification based on 3D local intensity structures for volume rendering IEEE Transactions on Visualization and Computer Graphics 2000 6 2 160 180
52. Frangi A. F., Niessen W. J., Vincken K. L., Viergever M. A., Wells W. M., Colchester A., Delp S. L., Multiscale vessel enhancement filtering Proceedings of the 1st International Conference Medical Image Computing and Computer-Assisted Intervention (MICCAI '98) October 1998 Cambridge, Mass, USA Springer 130 137
53. Manniesing R., Viergever M. A., Niessen W. J., Vessel enhancing diffusion. A scale space representation of vessel structures Medical Image Analysis 2006 10 6 815 825 (Pubitemid 44804129)
54. Wink O., Niessen W. J., Viergever M. A., Multiscale Vessel Tracking IEEE Transactions on Medical Imaging 2004 23 1 130 133
55. Olabarriaga S. D., Breeuwer M., Niessen W. J., Evaluation of Hessian-based filters to enhance the axis of coronary arteries in CT images International Congress Series 2003 1256 1191 1196
56. Santamaria-Pang A., Bildea T. S., Colbert C., Saggau P., Kakadiaris I. A., Towards segmentation of irregular tubular structures in 3D confocal microscope images Proceedings of the Workshop in Microscopic Image Analysis and Applications in Biology (MIAAB '06) October 2006 Copenhagen, Denmark 78 85
57. Gonzalez G., Aguet F., Fleuret F., Unser M., Fua P., Steerable features for statistical 3D dendrite detection 5762 Proceedings of 12th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI '09) September 2009 London, UK Springer 625 632
58. Bauer C., Pock T., Bischof H., Beichel R., Brown M., de Bruijne M., van Ginneken B., Kiraly A., Airway tree reconstruction based on tube detection Proceedings of the 2nd International Workshop on Pulmonary Image Analysis September 2009 London, UK CreateSpace 203 214
59. Sonka M., Shikata H., McLennan G., Hoffman E. A., Segmentation of pulmonary vascular trees from thoracic 3D CT images International Journal of Biomedical Imaging 2009 2009 11
60. Osher S., Sethian J. A., Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations Journal of Computational Physics 1988 79 1 12 49
61. Sethian J. A., Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science 1999 2nd New York, NY, USA Cambridge University Press
62. Lehmann G., Noise simulation. 2010, http://hdl.handle.net/10380/3158
63. Matsumoto M., Nishimura T., Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator ACM Transactions on Modeling and Computer Simulation 1998 8 1 3 30
64. Jorgensen S. M., Demirkaya O., Ritman E. L., Three-dimensional imaging of vasculature and parenchyma in intact rodent organs with X-ray micro-CT American Journal of Physiology 1998 44 3 H1103 H1114
65. Sugihara I., Wu H. S., Shinoda Y., Morphology of single olivocerebellar axons labeled with biotinylated dextran amine in the rat Journal of Comparative Neurology 1999 414 2 131 148 (Pubitemid 29489899)
66. Brown K. M., Donohue D. E., D'Alessandro G., Ascoli G. A., A cross-platform freeware tool for digital reconstruction of neuronal arborizations from image stacks Neuroinformatics 2005 3 4 343 359 (Pubitemid 41640745)
67. The digital reconstruction of axonal and dendritic morphology (DIADEM 2010) competition. 2010, http://diademchallenge.org/
68. Zamir M., Tree structure and branching characteristics of the right coronary artery in a right-dominant human heart Canadian Journal of Cardiology 1996 12 6 593 599 (Pubitemid 26237615)
69. Insight Segmentation and Registration Toolkit (ITK). http://www.itk.org/
70. Ibanez L., Schroeder W., The ITK Software Guide 2.4 2005 Clifton Park, NY, USA Kitware
71. Yoo T. S., Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis 2004 1st Wellesley, Mass, USA AK Peters
72. Nichols B., Buttlar D., Farrell J. B., Pthreads Programming: A POSIX Standard for Better Multiprocessing 1996 1st Sebastopol, Calif, USA OReilly Media
73. Gough B. J., Stallman R. M., An Introduction to GCC 2004 1st Bristol, UK Network Theory
74. von Hagen W., The Definitive Guide to GCC 2006 2nd Berkely, Calif, USA Apress
75. Stallman R. M., GCC Developer Community, Using the Gnu Compiler Collection: A Gnu Manual for GCC Version 4.3.3 2009 Boston, Mass, USA GNU Press
76. Debian Linux Operating System. www.debian.org
77. Krafft M., The Debian System: Concepts and Techniques 2005 San Francisco, Calif, USA Pap/Dvdr ed. No Starch Press
78. Enquobahrie A., Ibanez L., Aylward A., Bullitt E., Vessel Enhancing Diffusion Filter. http://hdl.handle.net/1926/558
79. Manniesing R., Viergever M., Niessen W., Vessel Enhancing Diffusion. 2009, http://hdl.handle.net/1926/1515
80. Antiga L., Generalizing vesselness with respect to dimensionality and shape. 2007, http://hdl.handle.net/1926/576
81. Gonzalez R. C., Woods R. E., Digital Image Processing 2007 3rd Upper Saddle River, NJ, USA Prentice Hall
82. Sonka M., Hlavac V., Boyle R., Image Processing, Analysis, and Machine Vision 2007 2nd Pacific Grove, Calif, USA Brooks/Cole
83. Parker J. R., Algorithms for Image Processing and Computer Vision 1996 Hoboken, NJ, USA John Wiley Sons
84. Wang Z., Bovik A. C., Modern Image Quality Assessment 2006 1st San Rafael, Calif, USA Morgan Claypool Synthesis Lectures on Image, Video Multimedia Processing
85. Avciba I., Sankur B., Sayood K., Statistical evaluation of image quality measures Journal of Electronic Imaging 2002 11 2 206 223 (Pubitemid 34536986)
86. Huynh-Thu Q., Ghanbari M., Scope of validity of PSNR in image/video quality assessment Electronics Letters 2008 44 13 800 801
87. Wang Z., Bovik A. C., Sheikh H. R., Simoncelli E. P., Image quality assessment: from error visibility to structural similarity IEEE Transactions on Image Processing 2004 13 4 600 612
88. Wang Z., Bovik A. C., Lu L., Why is image quality assessment so difficult? 4 Proceedings of the IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP '02) May 2002 Orlando, Fla, USA IV/3313 IV/3316
89. Eskicioglu A. M., Fisher P. S., Image quality measures and their performance IEEE Transactions on Communications 1995 43 12 2959 2965
90. Wang Z., Bovik A. C., Mean squared error: lot it or leave it? A new look at signal fidelity measures IEEE Signal Processing Magazine 2009 26 1 98 117
91. Homann H., Implementation of a 3D thinning algorithm. 2007, http://hdl.handle.net/1926/1292
92. Bouix S., Siddiqi K., Tannenbaum A., Flux driven automatic centerline extraction Medical Image Analysis 2005 9 3 209 221 (Pubitemid 40613522)
93. Mellado X., Larrabide I., Hernandez M., Frangi A., Flux driven medial curve extraction. 2007, http://hdl.handle.net/1926/560