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 :
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