Quantitative measurement for pathological change of pulley tissue from microscopic images via color-based segmentation

Yung Chun Liu, Hui Hsuan Shih, Tai-Hua Yang, Hsiao Bai Yang, Dee Shan Yang, Yung-Nien Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Measurement of pathological change in pulley tissue is an important index for trigger finger disease. However, the current measurement process is mostly based on manual estimation which is subjective and time-consuming. We hence propose an automatic method for quantitatively measuring the pathological change of pulley tissue from microscopic images. We first apply the color normalization to normalize all the acquired images. Then we use a three-stepped color segmentation process to extract the areas of diseased tissues. On the other hand, we also apply an active double thresholding scheme to segment the nuclei and extract shape features of nucleus. At last, the ratio of abnormal tissue area and the ratio of abnormal nuclei are calculated as the indices for the evaluation of trigger finger disease. The result showed good correlation between the expert judgments and the measured parameters.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings
Pages476-485
Number of pages10
EditionPART 3
DOIs
Publication statusPublished - 2012 Mar 27
Event4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012 - Kaohsiung, Taiwan
Duration: 2012 Mar 192012 Mar 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7198 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012
CountryTaiwan
CityKaohsiung
Period12-03-1912-03-21

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Liu, Y. C., Shih, H. H., Yang, T-H., Yang, H. B., Yang, D. S., & Sun, Y-N. (2012). Quantitative measurement for pathological change of pulley tissue from microscopic images via color-based segmentation. In Intelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings (PART 3 ed., pp. 476-485). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7198 LNAI, No. PART 3). https://doi.org/10.1007/978-3-642-28493-9_50