Adaptive segmentation of nuclei in H&E stained tendon microscopy

Bo I. Chuang, Po Ting Wu, Jian Han Hsu, I. Ming Jou, Fong Chin Su, Yung Nien Sun

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

Abstract

Tendiopathy is a popular clinical issue in recent years. In most cases like trigger finger or tennis elbow, the pathology change can be observed under H&E stained tendon microscopy. However, the qualitative analysis is too subjective and thus the results heavily depend on the observers. We develop an automatic segmentation procedure which segments and counts the nuclei in H&E stained tendon microscopy fast and precisely. This procedure first determines the complexity of images and then segments the nuclei from the image. For the complex images, the proposed method adopts sampling-based thresholding to segment the nuclei. While for the simple images, the Laplacian-based thresholding is employed to re-segment the nuclei more accurately. In the experiments, the proposed method is compared with the experts outlined results. The nuclei number of proposed method is closed to the experts counted, and the processing time of proposed method is much faster than the experts'.

Original languageEnglish
Title of host publicationSeventh International Conference on Graphic and Image Processing, ICGIP 2015
EditorsXudong Jiang, Xudong Jiang, Yulin Wang, Xudong Jiang, Yulin Wang, Xudong Jiang, Yulin Wang, Yulin Wang
PublisherSPIE
ISBN (Electronic)9781510600584, 9781510600584, 9781510600584, 9781510600584
DOIs
Publication statusPublished - 2015
Event7th International Conference on Graphic and Image Processing, ICGIP 2015 - Singapore, Singapore
Duration: 2015 Oct 232015 Oct 25

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9817
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

Other7th International Conference on Graphic and Image Processing, ICGIP 2015
Country/TerritorySingapore
CitySingapore
Period15-10-2315-10-25

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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