Automatic segmentation and classification of tendon nuclei from IHC stained images

Chan Pang Kuok, Po-Ting Wu, I. Ming Jou, Fong-chin Su, Yung-Nien Sun

研究成果: Conference contribution

1 引文 (Scopus)

摘要

Immunohistochemical (IHC) staining is commonly used for detecting cells in microscopy. It is used for analyzing many types of diseases, e.g. breast cancer. Dispersion problem often exist at cell staining which will affect the accuracy of automatic counting. In this paper, we introduce a new method to overcome this problem. Otsu's thresholding method is first applied to exclude the background, so that only cells with dispersed staining are left at foreground, and then refinement will be applied by local adaptive thresholding method according to the irregularity index of the segmented shape at foreground. The segmentation results are also compared to the refinement results using Otsu's thresholding method. Cell classification based on the shape and color indices obtained from the segmentation result is applied to determine the cell condition into normal, abnormal and suspected abnormal cases.

原文English
主出版物標題Seventh International Conference on Graphic and Image Processing, ICGIP 2015
編輯Xudong Jiang, Xudong Jiang, Yulin Wang, Xudong Jiang, Yulin Wang, Xudong Jiang, Yulin Wang, Yulin Wang
發行者SPIE
ISBN(電子)9781510600584, 9781510600584, 9781510600584, 9781510600584
DOIs
出版狀態Published - 2015 一月 1
事件7th International Conference on Graphic and Image Processing, ICGIP 2015 - Singapore, Singapore
持續時間: 2015 十月 232015 十月 25

出版系列

名字Proceedings of SPIE - The International Society for Optical Engineering
9817
ISSN(列印)0277-786X
ISSN(電子)1996-756X

Other

Other7th International Conference on Graphic and Image Processing, ICGIP 2015
國家Singapore
城市Singapore
期間15-10-2315-10-25

指紋

tendons
Tendons
Nucleus
Microscopic examination
Segmentation
Color
staining
nuclei
Cell
cells
Thresholding
Refinement
Adaptive Thresholding
Irregularity
Breast Cancer
irregularities
Microscopy
breast
Counting
counting

All Science Journal Classification (ASJC) codes

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

引用此文

Kuok, C. P., Wu, P-T., Jou, I. M., Su, F., & Sun, Y-N. (2015). Automatic segmentation and classification of tendon nuclei from IHC stained images. 於 X. Jiang, X. Jiang, Y. Wang, X. Jiang, Y. Wang, X. Jiang, Y. Wang, ... Y. Wang (編輯), Seventh International Conference on Graphic and Image Processing, ICGIP 2015 [98170J] (Proceedings of SPIE - The International Society for Optical Engineering; 卷 9817). SPIE. https://doi.org/10.1117/12.2228579
Kuok, Chan Pang ; Wu, Po-Ting ; Jou, I. Ming ; Su, Fong-chin ; Sun, Yung-Nien. / Automatic segmentation and classification of tendon nuclei from IHC stained images. Seventh International Conference on Graphic and Image Processing, ICGIP 2015. 編輯 / Xudong Jiang ; Xudong Jiang ; Yulin Wang ; Xudong Jiang ; Yulin Wang ; Xudong Jiang ; Yulin Wang ; Yulin Wang. SPIE, 2015. (Proceedings of SPIE - The International Society for Optical Engineering).
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abstract = "Immunohistochemical (IHC) staining is commonly used for detecting cells in microscopy. It is used for analyzing many types of diseases, e.g. breast cancer. Dispersion problem often exist at cell staining which will affect the accuracy of automatic counting. In this paper, we introduce a new method to overcome this problem. Otsu's thresholding method is first applied to exclude the background, so that only cells with dispersed staining are left at foreground, and then refinement will be applied by local adaptive thresholding method according to the irregularity index of the segmented shape at foreground. The segmentation results are also compared to the refinement results using Otsu's thresholding method. Cell classification based on the shape and color indices obtained from the segmentation result is applied to determine the cell condition into normal, abnormal and suspected abnormal cases.",
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Kuok, CP, Wu, P-T, Jou, IM, Su, F & Sun, Y-N 2015, Automatic segmentation and classification of tendon nuclei from IHC stained images. 於 X Jiang, X Jiang, Y Wang, X Jiang, Y Wang, X Jiang, Y Wang & Y Wang (編輯), Seventh International Conference on Graphic and Image Processing, ICGIP 2015., 98170J, Proceedings of SPIE - The International Society for Optical Engineering, 卷 9817, SPIE, 7th International Conference on Graphic and Image Processing, ICGIP 2015, Singapore, Singapore, 15-10-23. https://doi.org/10.1117/12.2228579

Automatic segmentation and classification of tendon nuclei from IHC stained images. / Kuok, Chan Pang; Wu, Po-Ting; Jou, I. Ming; Su, Fong-chin; Sun, Yung-Nien.

Seventh International Conference on Graphic and Image Processing, ICGIP 2015. 編輯 / Xudong Jiang; Xudong Jiang; Yulin Wang; Xudong Jiang; Yulin Wang; Xudong Jiang; Yulin Wang; Yulin Wang. SPIE, 2015. 98170J (Proceedings of SPIE - The International Society for Optical Engineering; 卷 9817).

研究成果: Conference contribution

TY - GEN

T1 - Automatic segmentation and classification of tendon nuclei from IHC stained images

AU - Kuok, Chan Pang

AU - Wu, Po-Ting

AU - Jou, I. Ming

AU - Su, Fong-chin

AU - Sun, Yung-Nien

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Immunohistochemical (IHC) staining is commonly used for detecting cells in microscopy. It is used for analyzing many types of diseases, e.g. breast cancer. Dispersion problem often exist at cell staining which will affect the accuracy of automatic counting. In this paper, we introduce a new method to overcome this problem. Otsu's thresholding method is first applied to exclude the background, so that only cells with dispersed staining are left at foreground, and then refinement will be applied by local adaptive thresholding method according to the irregularity index of the segmented shape at foreground. The segmentation results are also compared to the refinement results using Otsu's thresholding method. Cell classification based on the shape and color indices obtained from the segmentation result is applied to determine the cell condition into normal, abnormal and suspected abnormal cases.

AB - Immunohistochemical (IHC) staining is commonly used for detecting cells in microscopy. It is used for analyzing many types of diseases, e.g. breast cancer. Dispersion problem often exist at cell staining which will affect the accuracy of automatic counting. In this paper, we introduce a new method to overcome this problem. Otsu's thresholding method is first applied to exclude the background, so that only cells with dispersed staining are left at foreground, and then refinement will be applied by local adaptive thresholding method according to the irregularity index of the segmented shape at foreground. The segmentation results are also compared to the refinement results using Otsu's thresholding method. Cell classification based on the shape and color indices obtained from the segmentation result is applied to determine the cell condition into normal, abnormal and suspected abnormal cases.

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M3 - Conference contribution

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A2 - Jiang, Xudong

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PB - SPIE

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Kuok CP, Wu P-T, Jou IM, Su F, Sun Y-N. Automatic segmentation and classification of tendon nuclei from IHC stained images. 於 Jiang X, Jiang X, Wang Y, Jiang X, Wang Y, Jiang X, Wang Y, Wang Y, 編輯, Seventh International Conference on Graphic and Image Processing, ICGIP 2015. SPIE. 2015. 98170J. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2228579