Enhanced image similarity analysis system in digital pathology

In digital pathology, image similarity algorithms are used to find cancer in tissue cells from medical images. However, it is very difficult to apply image similarity algorithms used in general purpose system. Because in the medical field, accuracy and reliability must be perfect when looking for ca...

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Bibliographic Details
Published inMultimedia tools and applications Vol. 76; no. 23; pp. 25477 - 25494
Main Authors Lee, Jae-Gu, Choi, Kyung-Chan, Yeon, Seung-Ho, Kim, Jeong Won, Ko, Young-Woong
Format Journal Article
LanguageEnglish
Published New York Springer US 01.12.2017
Springer Nature B.V
Subjects
Algorithms
Cancer
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Digital imaging
Feature extraction
Image enhancement
Medical imaging
Medical research
Multimedia Information Systems
Pathology
Search algorithms
Similarity
Special Purpose and Application-Based Systems
Tiling
Leveling
Tiling
Image sync
OpenSlide
Image similarity
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Summary:In digital pathology, image similarity algorithms are used to find cancer in tissue cells from medical images. However, it is very difficult to apply image similarity algorithms used in general purpose system. Because in the medical field, accuracy and reliability must be perfect when looking for cancer cells by using image similarity techniques to pathology images. To cope with this problem, this paper proposes an efficient similar image search algorithm for digital pathology by applying leveling and tiling scheme on OpenSlide format. Furthermore, we apply image sync method to extract feature key points during image similarity processing. In the experiment, to prove the efficiency of the proposed system, we conduct several experiments including algorithm performance, algorithm accuracy and computation time. The experiments result shows that the proposed system efficiently retrieves similar cell images from pathology images.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-017-4773-z