Automated prostate cancer diagnosis and Gleason grading of tissue microarrays

Ali Tabesh; Vinay P. Kumar; Ho-Yuen Pang; David Verbel; Angeliki Kotsianti; Mikhail Teverovskiy; Olivier Saidi

doi:10.1117/12.597250

29 April 2005 Automated prostate cancer diagnosis and Gleason grading of tissue microarrays

Ali Tabesh, Vinay P. Kumar, Ho-Yuen Pang, David Verbel, Angeliki Kotsianti, Mikhail Teverovskiy, Olivier Saidi

Proceedings Volume 5747, Medical Imaging 2005: Image Processing; (2005) https://doi.org/10.1117/12.597250
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

We present the results on the development of an automated system for prostate cancer diagnosis and Gleason grading. Images of representative areas of the original Hematoxylin-and-Eosin (H&E)-stained tissue retrieved from each patient, either from a tissue microarray (TMA) core or whole section, were captured and analyzed. The image sets consisted of 367 and 268 color images for the diagnosis and Gleason grading problems, respectively. In diagnosis, the goal is to classify a tissue image into tumor versus non-tumor classes. In Gleason grading, which characterizes tumor aggressiveness, the objective is to classify a tissue image as being from either a low- or high-grade tumor. Several feature sets were computed from the image. The feature sets considered were: (i) color channel histograms, (ii) fractal dimension features, (iii) fractal code features, (iv) wavelet features, and (v) color, shape and texture features computed using Aureon Biosciences' MAGIC system. The linear and quadratic Gaussian classifiers together with a greedy search feature selection algorithm were used. For cancer diagnosis, a classification accuracy of 94.5% was obtained on an independent test set. For Gleason grading, the achieved accuracy of classification into low- and high-grade classes of an independent test set was 77.6%.

Citation Download Citation

Ali Tabesh, Vinay P. Kumar, Ho-Yuen Pang, David Verbel, Angeliki Kotsianti, Mikhail Teverovskiy, and Olivier Saidi "Automated prostate cancer diagnosis and Gleason grading of tissue microarrays", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.597250

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