Automatic detection of malignant prostatic gland units in cross-sectional microscopic images

Proceedings - International Conference on Image Processing, ICIP

Volumn , Issue , 2010, Pages 1057-1060

  Xia, Tian ^a   Yu, Yizhou ^a   Hua, Jing ^b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b WAYNE STATE UNIVERSITY   (United States)

Author keywords

Classification; Histological Images; Prostate glands; Segmentation

Indexed keywords

AUTOMATIC DETECTION; CLASSIFICATION; CLASSIFICATION METHODS; CO-OCCURRENCE; COLOR HISTOGRAM; ERROR PRONES; FEATURE DESCRIPTORS; HISTOLOGICAL IMAGES; LARGE REGIONS; MICROSCOPIC IMAGE; PROSTATE CANCERS; PROSTATE GLANDS; SCREENING METHODS; SEGMENTATION;

DISEASES; IMAGING SYSTEMS;

IMAGE SEGMENTATION;

EID: 78651095236     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2010.5650763     Document Type: Conference Paper

References (15)

1. B. Julesz, "Textons, the elements of texture perception and their interactions, " Nature(London), vol. 290, pp. 91-97, 1981.
2. T. Leung and J. Malik, "Representing and recognizing the visual appearance of materials using three-dimensional textons, " Intl. Journal Computer Vision, vol. 43, no. 1, pp. 29-44, 2001.
3. D.E. Pitts, B.S. Premkumar, A.G. Houston, R.J. Badain, and P. Troncosa, "Texture analysis of digitized prostate pathological cross-section, " in SPIE Proceedings of Medical Imaging: Image Processing, 1993, vol. 1898, pp. 456-470.
4. K. Jafari-Khouzani and H. Soltanian-Zadeh, "Multiwavelet grading of pathological images of prostate, " IEEE Transactions on Biomedical Engineering, vol. 50, no. 6, pp. 697-704, 2003.
5. S. Doyle, A. Madabhushi, M. Feldman, and J. Tomaszeweski, "A boosting cascade for automated detection of prostate cancer from digitized histology, " in Medical Image Computing and Computer Assisted Intervention, 2006, vol. 9, pp. 504-511.
6. A. Tabesh, M. Teverovskiy, H.Y. Pang, V.P. Kumar, D. Verbel, A. Kotsianti, and O. Saidi, "Multifeature prostate cancer diagnosis and gleason grading of histological images, " IEEE Transactions on Medical Imaging, vol. 26, no. 10, pp. 1366- 1378, 2007.
7. P.-W. Huang and C.-H. Lee, "Automatic classification for pathological prostate images based on fractal analysis, " IEEE Transactions on Medical Imaging, vol. 28, no. 7, pp. 1037- 1050, 2009.
8. Y. Zhu, S. Williams, and Zwiggelaar R., "Computer technology in detection and staging of prostate carcinoma: a review, " Medical Image Analysis, vol. 10, no. 2, pp. 178-199, 2006.
9. Y. Li, J. Sun, C.-K. Tang, and H.-Y. Shum, "Lazy snapping, " ACM Transaction on Graphics, vol. 23, no. 3, pp. 303-308, 2004.
10. R.E. Schapire, "The boosting approach to machine learning: An overview, " in MSRI Workshop on Nonlinear Estimation and Classification, 2002.
11. T. Xia, Q. Wu, C. Chen, and Y. Yu, "Lazy texture selection based on active learning, " The Visual Computer Journal, vol. 26, no. 3, 2010.
12. Y. Boykov and M.P. Jolly, "Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images, " in Intl. Conf. Computer Vision, 2001, vol. I, pp. 105-112.
13. C. Rother, A. Blake, and V. Kolmogorov, "Grabcut-interactive foreground extraction using iterated graph cuts, " ACM Transaction on Graphics, vol. 23, no. 3, pp. 309-314, 2004.
14. R.Haralick, K. Shanmugam, and I. Dinstein, "Textural features for image classification, " IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-3, no. 6, pp. 610-621, 1973.
15. Chih-Chung Chang and Chih-Jen Lin, "LIBSVM: a library for support vector machines, " 2001, Software available at http://www.csie.ntu.edu.tw/ ̃cjlin/libsvm.