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A global covariance descriptor for nuclear atypia scoring in breast histopathology images
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Khan, Adnan M., Sirinukunwattana, Korsuk and Rajpoot, Nasir M. (2015) A global covariance descriptor for nuclear atypia scoring in breast histopathology images. IEEE Journal of Biomedical and Health Informatics, 19 (5). 1637 -1647. doi:10.1109/JBHI.2015.2447008
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WRAP_0070699-cs-070715-khansirinukunwattanarajpoot_jbhi2015.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (9Mb) |
Official URL: http://dx.doi.org/10.1109/JBHI.2015.2447008
Abstract
Nuclear atypia scoring is a diagnostic measure commonly used to assess tumor grade of various cancers, including breast cancer. It provides a quantitative measure of deviation in visual appearance of cell nuclei from those in normal epithelial cells. In this paper, we present a novel image-level descriptor for nuclear atypia scoring in breast cancer histopathology images. The method is based on the region covariance descriptor that has recently become a popular method in various computer vision applications. The descriptor in its original form is not suitable for classification of histopathology images as cancerous histopathology images tend to possess diversely heterogeneous regions in a single field of view. Our proposed image-level descriptor, which we term as the geodesic mean of region covariance descriptors, possesses all the attractive properties of covariance descriptors lending itself to tractable geodesic distance based k-nearest neighbor classification using efficient kernels. The experimental results suggest that the proposed image descriptor yields high classification accuracy compared to a variety of widely used image-level descriptors.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software R Medicine > R Medicine (General) R Medicine > RC Internal medicine R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer) T Technology > TA Engineering (General). Civil engineering (General) |
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| Divisions: | Faculty of Science > Computer Science | ||||||||
| Library of Congress Subject Headings (LCSH): | Breast--Cancer, Cancer--Histopathology, Diagnostic imaging--Digital techniques, Imaging systems in medicine, Optical pattern recognition | ||||||||
| Journal or Publication Title: | IEEE Journal of Biomedical and Health Informatics | ||||||||
| Publisher: | IEEE | ||||||||
| ISSN: | 2168-2194 | ||||||||
| Official Date: | September 2015 | ||||||||
| Dates: |
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| Volume: | 19 | ||||||||
| Number: | 5 | ||||||||
| Page Range: | 1637 -1647 | ||||||||
| DOI: | 10.1109/JBHI.2015.2447008 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Funder: | Qatar National Research Fund (QNRF), University of Warwick Postgraduate Research Scholarship, Department of Computer Science, University of Warwick | ||||||||
| Grant number: | NPRP 5-1345-1-228 (QNRF) |
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