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Proceedings Paper

Content-based histopathological image retrieval for whole slide image database using binary codes
Author(s): Yushan Zheng; Zhiguo Jiang; Yibing Ma; Haopeng Zhang; Fengying Xie; Huaqiang Shi; Yu Zhao
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Paper Abstract

Content-based image retrieval (CBIR) has been widely researched for medical images. In application of histo- pathological images, there are two issues that need to be carefully considered. The one is that the digital slide is stored in a spatially continuous image with a size of more than 10K x 10K pixels. The other is that the size of query image varies in a large range according to different diagnostic conditions. It is a challenging work to retrieve the eligible regions for the query image from the database that consists of whole slide images (WSIs). In this paper, we proposed a CBIR framework for the WSI database and size-scalable query images. Each WSI in the database is encoded and stored in a matrix of binary codes. When retrieving, the query image is first encoded into a set of binary codes and analyzed to pre-choose a set of regions from database using hashing method. Then a multi-binary-code-based similarity measurement based on hamming distance is designed to rank proposal regions. Finally, the top relevant regions and their locations in the WSIs along with the diagnostic information are returned to assist pathologists in diagnoses. The effectiveness of the proposed framework is evaluated in a fine-annotated WSIs database of epithelial breast tumors. The experimental results show that proposed framework is both effective and efficiency for content-based whole slide image retrieval.

Paper Details

Date Published: 1 March 2017
PDF: 6 pages
Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 1014013 (1 March 2017); doi: 10.1117/12.2253988
Show Author Affiliations
Yushan Zheng, Beihang Univ. (China)
Beijing Key Lab. of Digital Media (China)
Zhiguo Jiang, Beihang Univ. (China)
Beijing Key Lab. of Digital Media (China)
Yibing Ma, Beihang Univ. (China)
Beijing Key Lab. of Digital Media (China)
Haopeng Zhang, Beihang Univ. (China)
Beijing Key Lab. of Digital Media (China)
Fengying Xie, Beihang Univ. (China)
Beijing Key Lab. of Digital Media (China)
Huaqiang Shi, Motic Medical Diagnostic Systems Co., Ltd. (China)
General Hospital of the Air Force (China)
Yu Zhao, Motic Medical Diagnostic Systems Co., Ltd. (China)

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

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