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Proceedings Paper

A multiview boosting approach to tissue segmentation
Author(s): Jin Tae Kwak; Sheng Xu; Peter A. Pinto; Baris Turkbey; Marcelino Bernardo; Peter L Choyke; Bradford J. Wood
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Paper Abstract

Digitized histopathology images have a great potential for improving or facilitating current assessment tools in cancer pathology. In order to develop accurate and robust automated methods, the precise segmentation of histologic objects such epithelium, stroma, and nucleus is necessary, in the hopes of information extraction not otherwise obvious to the subjective eye. Here, we propose a multivew boosting approach to segment histology objects of prostate tissue. Tissue specimen images are first represented at different scales using a Gaussian kernel and converted into several forms such HSV and La*b*. Intensity- and texture-based features are extracted from the converted images. Adopting multiview boosting approach, we effectively learn a classifier to predict the histologic class of a pixel in a prostate tissue specimen. The method attempts to integrate the information from multiple scales (or views). 18 prostate tissue specimens from 4 patients were employed to evaluate the new method. The method was trained on 11 tissue specimens including 75,832 epithelial and 103,453 stroma pixels and tested on 55,319 epithelial and 74,945 stroma pixels from 7 tissue specimens. The technique showed 96.7% accuracy, and as summarized into a receiver operating characteristic (ROC) plot, the area under the ROC curve (AUC) of 0.983 (95% CI: 0.983-0.984) was achieved.

Paper Details

Date Published: 11 April 2014
PDF: 7 pages
Proc. SPIE 9041, Medical Imaging 2014: Digital Pathology, 90410R (11 April 2014); doi: 10.1117/12.2043966
Show Author Affiliations
Jin Tae Kwak, National Institutes of Health Clinical Ctr. (United States)
Sheng Xu, National Institutes of Health Clinical Ctr. (United States)
Peter A. Pinto, National Cancer Institute (United States)
Baris Turkbey, National Cancer Institute (United States)
Marcelino Bernardo, National Cancer Institute (United States)
Peter L Choyke, National Cancer Institute (United States)
Bradford J. Wood, National Institutes of Health Clinical Ctr. (United States)


Published in SPIE Proceedings Vol. 9041:
Medical Imaging 2014: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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