AI Article Synopsis
- Prostate adenocarcinoma diagnosis relies on histological morphology, particularly using the Gleason grading system, which can have variances in interpretations among pathologists.
- * A new method introduced in this study focuses on prostate gland segmentation, enabling computer-aided Gleason grading without prior lumen information.
- * This region-based nuclei segmentation technique shows high precision and efficiency, achieving accuracy metrics of 0.94 for precision, 0.60 for recall, and 0.70 for F1 score.*
Article 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.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4917302 | PMC |
| http://dx.doi.org/10.1109/EMBC.2015.7319026 | DOI Listing |
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