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Persistent homology for fast tumor segmentation in whole slide histology images
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Qaiser, Talha, Sirinukunwattana, Korsuk, Nakane, Kazuaki, Tsang, Yee-Wah, Epstein, D. B. A. and Rajpoot, Nasir M. (2016) Persistent homology for fast tumor segmentation in whole slide histology images. In: Medical Image Understanding and Analysis (MIUA 2016), Loughborough, UK, 6-8 July 2016. Published in: Procedia Computer Science, 90 pp. 119-124. ISSN 1877-0509.
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Official URL: http://dx.doi.org/ 10.1016/j.procs.2016.07.033
Abstract
Automated tumor segmentation in Hematoxylin & Eosin stained histology images is an essential step towards a computer-aided diagnosis system. In this work we propose a novel tumor segmentation approach for a histology whole-slide image (WSI) by exploring the degree of connectivity among nuclei using the novel idea of persistent homology profiles. Our approach is based on 3 steps: 1) selection of exemplar patches from the training dataset using convolutional neural networks (CNNs); 2) construction of persistent homology profiles based on topological features; 3) classification using variant of k-nearest neighbors (k-NN). Extensive experimental results favor our algorithm over a conventional CNN.
Item Type: | Conference Item (Paper) | ||||||
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Subjects: | R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer) | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||
Library of Congress Subject Headings (LCSH): | Colon (Anatomy) -- Cancer -- Diagnosis , Rectum -- Cancer -- Diagnosis , Histology, Pathological , Tumors, Image segmentation | ||||||
Journal or Publication Title: | Procedia Computer Science | ||||||
Publisher: | Elsevier BV | ||||||
ISSN: | 1877-0509 | ||||||
Official Date: | 25 July 2016 | ||||||
Dates: |
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Volume: | 90 | ||||||
Page Range: | pp. 119-124 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Date of first compliant deposit: | 9 January 2017 | ||||||
Date of first compliant Open Access: | 11 January 2017 | ||||||
Conference Paper Type: | Paper | ||||||
Title of Event: | Medical Image Understanding and Analysis (MIUA 2016) | ||||||
Type of Event: | Conference | ||||||
Location of Event: | Loughborough, UK | ||||||
Date(s) of Event: | 6-8 July 2016 |
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