Multimedia Tools and Applications

, Volume 76, Issue 23, pp 25477–25494 | Cite as

Enhanced image similarity analysis system in digital pathology

  • Jae-Gu Lee
  • Kyung-Chan Choi
  • Seung-Ho Yeon
  • Jeong Won Kim
  • Young-Woong Ko
Article
  • 67 Downloads

Abstract

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.

Keywords

OpenSlide Leveling Tiling Image similarity Image sync 

Notes

Acknowledgements

This research was supported by Hallym University Research Fund 2015(H20150684) and this research was also supported by The Leading Human Resource Training Program of Regional Neo industry through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and future Planning (2016H1D5A1910630).

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Computer EngineeringHallym UniversityChuncheonRepublic of Korea
  2. 2.Department of Pathology, Chuncheon Sacred Heart HospitalHallym UniversityChuncheonRepublic of Korea
  3. 3.Department of Pathology, Kangnam Sacred Heart HospitalHallym University College of MedicineSeoulRepublic of Korea

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