Global context inference for adaptive abnormality detection in PET-CT images

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2012, Pages 482-485

  Song, Yang ^a   Cai, Weidong ^b   Feng, David Dagan ^a,b,c  

^a UNIVERSITY OF SYDNEY   (Australia)

^b HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

abnormality; detection; global contexts; max margin; PET CT

Indexed keywords

ABNORMALITY; ABNORMALITY DETECTION; GLOBAL CONTEXT; LEARNING-BASED METHODS; LOCAL FEATURE; LUNG CANCER; MAX-MARGIN; PET-CT; PRECISION AND RECALL;

ERROR DETECTION; MEDICAL IMAGING;

COMPUTERIZED TOMOGRAPHY;

EID: 84864856790     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2012.6235589     Document Type: Conference Paper

References (11)

1. W.D. Wever, S. Stroobants, J. Coolen, and J.A. Verschakelen, "Integrated PET/CT in the staging of nonsmall cell lung cancer: technical aspects and clinical integration," Eur. Respir. J., vol. 33, pp. 201-212, 2009.
2. H. Zaidi and I. E. Naqa, "PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques," Eur J. Nucl Med Mol Imaging, vol. 37, no. 11, pp. 2165-2187, 2010.
3. H. Guan, T. Kubota, X. Huang, X.S. Zhou, and M. Turk, "Automatic hot spot detection and segmentation in whole body FDG-PET images," in Proc. ICIP, pp. 85-88, 2006.
4. G.V. Saradhi, G. Gopalakrishnan, A.S. Roy, R. Mullick, R. Manjeshwar, K. Thielemans, and U. Patil, "A framework for automated tumor detection in thoracic FDG PET images using texture-based features," in Proc. ISBI, pp. 97-100, 2009.
5. V. Potesil, G. Platsch, D. Slosman, and T. Kadir, "Image normalization strategies for organ specific models of functional uptake in FDG-PET/CT," in Proc. NSS, pp. 5225-5228, 2008.
6. U. Nestle, S. Kremp, A. Schaefer-Schuler, C. Sebastian- Welsch, D. Hellwig, C. Rube, and C.M. Kirsch, "Comparison of different methods for delineation of 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-small cell lung cancer," J. Nucl. Med., vol. 46, pp. 1342-1348, 2005.
7. Y. Song, W. Cai, S. Eberl, M.J. Fulham, and D. Feng, "Automatic detection of lung tumor and abnormal regional lymph nodes in PET-CT images," J. Nucl. Med., vol. 52, no. Supplement 1, pp. 211, 2011.
8. D. Comaniciu and P. Meer, "Mean shift: a robust approach toward feature space analysis," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, pp. 603-619, 2002.
9. C.C. Chang and C.J. Lin, "LIBSVM: A library for support vector machines," ACM Transactions on Intelligent Systems and Technology, vol. 2, pp. 27:1-27:27, 2011.
10. S. Lazebnik, C. Schmid, and J. Ponce, "Beyond bags of features: spatial pyramid matching for recognizing natural scene categories," CVPR, pp. 2169-2178, 2006.
11. A. Frome, Y. Singer, F. Sha, and J. Malik, "Learning globallyconsistent local distance functions for shape-based image retrieval and classification," ICCV, pp. 1-8, 2007.