Machine Learning Approaches to Analyze Histological Images of Tissues from Radical Prostatectomies

Prostate cancer (PCa) remains the most commonly diagnosed cancer in men in developed countries. Fortunately, cancer deaths are steadily declining despite a fairly steady rate of new incidences per year [1]. Microscopic evaluation of prostate needle biopsies is the gold standard for PCa diagnosis and criteria have been established to manage patients based on histopathologic observations in the biopsy and radical prostatectomies. While normal glands are organized into ducts and acini and well separated by stroma, as PCa develops, the malignant acinar structures undergo excessive branching morphogenesis.

Source: Computerized Medical Imaging and Graphics - August 20, 2015 Category: Radiology Authors: Arkadiusz Gertych, Nathan Ing, Zhaoxuan Ma, Thomas J. Fuchs, Sadri Salman, Sambit Mohanty, Sanica Bhele, Adriana Velásquez-Vacca, Mahul Amin, Beatrice S. Knudsen Source Type: research