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Abstract #4386

Estimation of prostate cancer distribution on pathology slides via image analysis of IHC-stained slides.

Ethan Leng1, Jonathan C. Hendriksen2, Jin Jin3, Stephen C. Schmechel2, and Gregory J. Metzger1

1Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, 2Department of Pathology, University of Washington, Seattle, WA, United States, 3Department of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, United States

For the development of CAD systems of prostate cancer, manual annotation of cancer by experienced pathologists is the gold standard for establishing the ground truth. However, the process is tedious and has finite precision. Here, we describe a framework that uses quantitative analysis of IHC-stained slides to derive parameters, which in turn are used by a trained predictive model to estimate the spatial distribution of malignant epithelium. Thresholding of the results provides a reasonable map of cancer that is comparable to manual annotation.

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