title: Computer aided analysis of prostate histopathology images Gleason grading especially for Gleason score 7.
abstract: Clinically, prostate adenocarcinoma is diagnosed by recognizing certain morphology on histology. While the Gleason grading system has been shown to be the strongest prognostic factor for men with prostrate adenocarcinoma, there is a significant intra and interobserver variability between pathologists in assigning this grading system. In this study, we present a new method for prostate gland segmentation from which we then utilize to develop a computer aided Gleason grading. The novelty of our method is a region-based nuclei segmentation to get individual gland without using lumen as prior information. Because each gland region is surrounded by nuclei, individual gland can be segmented by using the structure features and Delaunay Triangulation. The precision, recal and F1 of this approach are 0.94±0.11, 0.60±0.23 and 0.70±0.19 respectively. Our method achieves a high accuracy for prostate gland segmentation with less computation time.
authors.forename: Jian
authors.initials: J
authors.lastname: Ren
authors.forename: Evita T
authors.initials: ET
authors.lastname: Sadimin
authors.forename: Daihou
authors.initials: D
authors.lastname: Wang
authors.forename: Jonathan I
authors.initials: JI
authors.lastname: Epstein
authors.forename: David J
authors.initials: DJ
authors.lastname: Foran
authors.forename: Xin
authors.initials: X
authors.lastname: Qi
mesh_terms: D000230:Adenocarcinoma; D006801:Humans; D008297:Male; D060787:Neoplasm Grading; D015588:Observer Variation; D011471:Prostatic Neoplasms