DocumentCode
3684585
Title
Computer aided analysis of prostate histopathology images Gleason grading especially for Gleason score 7
Author
Jian Ren;Evita T. Sadimin;Daihou Wang;Jonathan I. Epstein;David J. Foran;Xin Qi
Author_Institution
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ 08854, USA
fYear
2015
Firstpage
3013
Lastpage
3016
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.
Keywords
"Glands","Image segmentation","Biomedical imaging","Image color analysis","Prostate cancer","Shape","Pathology"
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
ISSN
1094-687X
Electronic_ISBN
1558-4615
Type
conf
DOI
10.1109/EMBC.2015.7319026
Filename
7319026
Link To Document