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ISBI
2011
IEEE

Network cycle features: Application to computer-aided Gleason grading of prostate cancer histopathological images

11 years 1 months ago
Network cycle features: Application to computer-aided Gleason grading of prostate cancer histopathological images
Features extracted from cell networks have become popular tools in histological image analysis. However, existing features do not take sufficient advantage of the cycle structure present within the cell networks. We introduce a new class of network cycle features that take advantage of such structures. We demonstrate the utility of these features for automated prostate cancer scoring using histological images. Prostate cancer is commonly scored by pathologists using the Gleason grading system and our automated system based upon network cycle features serves an important need in making this process less labor-intensive and more reproducible. Our system first extracts the cells from the histological images, computes networks from the cell locations and then computes features based upon statistics for the different cycles present in these networks. Using an SVM (Support Vector Machine) classifier on these features, we demonstrate the efficacy of our system in distinguishing between g...
Parmeshwar Khurd, Leo Grady, Ali Kamen, Summer Gib
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ISBI
Authors Parmeshwar Khurd, Leo Grady, Ali Kamen, Summer Gibbs-Strauss, Elizabeth Genega, John V. Frangioni
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