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Proceedings Paper

Evaluation of nucleus segmentation in digital pathology images through large scale image synthesis
Author(s): Naiyun Zhou; Xiaxia Yu; Tianhao Zhao; Si Wen; Fusheng Wang; Wei Zhu; Tahsin Kurc; Allen Tannenbaum; Joel Saltz; Yi Gao
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Paper Abstract

Digital histopathology images with more than 1 Gigapixel are drawing more and more attention in clinical, biomedical research, and computer vision fields. Among the multiple observable features spanning multiple scales in the pathology images, the nuclear morphology is one of the central criteria for diagnosis and grading. As a result it is also the mostly studied target in image computing. Large amount of research papers have devoted to the problem of extracting nuclei from digital pathology images, which is the foundation of any further correlation study. However, the validation and evaluation of nucleus extraction have yet been formulated rigorously and systematically. Some researches report a human verified segmentation with thousands of nuclei, whereas a single whole slide image may contain up to million. The main obstacle lies in the difficulty of obtaining such a large number of validated nuclei, which is essentially an impossible task for pathologist. We propose a systematic validation and evaluation approach based on large scale image synthesis. This could facilitate a more quantitatively validated study for current and future histopathology image analysis field.

Paper Details

Date Published: 1 March 2017
PDF: 6 pages
Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 101400K (1 March 2017); doi: 10.1117/12.2254220
Show Author Affiliations
Naiyun Zhou, Stony Brook Univ. (United States)
Xiaxia Yu, Stony Brook Univ. (United States)
Tianhao Zhao, Stony Brook Univ. (United States)
Si Wen, Stony Brook Univ. (United States)
Fusheng Wang, Stony Brook Univ. (United States)
Wei Zhu, Stony Brook Univ. (United States)
Tahsin Kurc, Stony Brook Univ. (United States)
Allen Tannenbaum, Stony Brook Univ. (United States)
Joel Saltz, Stony Brook Univ. (United States)
Yi Gao, Stony Brook Univ. (United States)

Published in SPIE Proceedings Vol. 10140:
Medical Imaging 2017: Digital Pathology
Metin N. Gurcan; John E. Tomaszewski, Editor(s)

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