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

doi:10.1117/12.2228579

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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.

Original language	English
Title of host publication	Seventh International Conference on Graphic and Image Processing, ICGIP 2015
Editors	Xudong Jiang, Xudong Jiang, Yulin Wang, Xudong Jiang, Yulin Wang, Xudong Jiang, Yulin Wang, Yulin Wang
Publisher	SPIE
ISBN (Electronic)	9781510600584, 9781510600584, 9781510600584, 9781510600584
DOIs	https://doi.org/10.1117/12.2228579
Publication status	Published - 2015
Event	7th International Conference on Graphic and Image Processing, ICGIP 2015 - Singapore, Singapore Duration: 2015 Oct 23 → 2015 Oct 25

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	9817
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Other

Other	7th International Conference on Graphic and Image Processing, ICGIP 2015
Country/Territory	Singapore
City	Singapore
Period	15-10-23 → 15-10-25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

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

Access to Document

10.1117/12.2228579

Cite this

Kuok, C. P., Wu, P. T., Jou, I. M., Su, F. C., & Sun, Y. N. (2015). Automatic segmentation and classification of tendon nuclei from IHC stained images. In X. Jiang, X. Jiang, Y. Wang, X. Jiang, Y. Wang, X. Jiang, Y. Wang, & Y. Wang (Eds.), Seventh International Conference on Graphic and Image Processing, ICGIP 2015 Article 98170J (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9817). SPIE. https://doi.org/10.1117/12.2228579

Kuok, Chan Pang ; Wu, Po Ting ; Jou, I. Ming et al. / Automatic segmentation and classification of tendon nuclei from IHC stained images. Seventh International Conference on Graphic and Image Processing, ICGIP 2015. editor / 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).

@inproceedings{e854a0a7d3e64dd5b43aa411a4c47d09,

title = "Automatic segmentation and classification of tendon nuclei from IHC stained images",

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.",

author = "Kuok, \{Chan Pang\} and Wu, \{Po Ting\} and Jou, \{I. Ming\} and Su, \{Fong Chin\} and Sun, \{Yung Nien\}",

note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; 7th International Conference on Graphic and Image Processing, ICGIP 2015 ; Conference date: 23-10-2015 Through 25-10-2015",

year = "2015",

doi = "10.1117/12.2228579",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Xudong Jiang and Xudong Jiang and Yulin Wang and Xudong Jiang and Yulin Wang and Xudong Jiang and Yulin Wang and Yulin Wang",

booktitle = "Seventh International Conference on Graphic and Image Processing, ICGIP 2015",

address = "United States",

}

Kuok, CP, Wu, PT, Jou, IM, Su, FC & Sun, YN 2015, Automatic segmentation and classification of tendon nuclei from IHC stained images. in X Jiang, X Jiang, Y Wang, X Jiang, Y Wang, X Jiang, Y Wang & Y Wang (eds), Seventh International Conference on Graphic and Image Processing, ICGIP 2015., 98170J, Proceedings of SPIE - The International Society for Optical Engineering, vol. 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 et al.
Seventh International Conference on Graphic and Image Processing, ICGIP 2015. ed. / 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; Vol. 9817).

Research output: Chapter in Book/Report/Conference proceeding › 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

Y1 - 2015

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.

UR - https://www.scopus.com/pages/publications/85028356482

UR - https://www.scopus.com/pages/publications/85028356482#tab=citedBy

U2 - 10.1117/12.2228579

DO - 10.1117/12.2228579

M3 - Conference contribution

AN - SCOPUS:85028356482

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Seventh International Conference on Graphic and Image Processing, ICGIP 2015

A2 - Jiang, Xudong

A2 - Wang, Yulin

A2 - Jiang, Xudong

A2 - Wang, Yulin

A2 - Jiang, Xudong

A2 - Wang, Yulin

PB - SPIE

T2 - 7th International Conference on Graphic and Image Processing, ICGIP 2015

Y2 - 23 October 2015 through 25 October 2015

ER -

Kuok CP, Wu PT, Jou IM, Su FC , Sun YN. Automatic segmentation and classification of tendon nuclei from IHC stained images. In Jiang X, Jiang X, Wang Y, Jiang X, Wang Y, Jiang X, Wang Y, Wang Y, editors, Seventh International Conference on Graphic and Image Processing, ICGIP 2015. SPIE. 2015. 98170J. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2228579

Automatic segmentation and classification of tendon nuclei from IHC stained images

Abstract

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