GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics

Che Lun Hung; Chun Yuan Lin

doi:10.1109/BIBM49941.2020.9313307

GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics

Che Lun Hung, Chun Yuan Lin

Institute of Biomedical Informatics

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

2 Scopus citations

Abstract

Mammograms are always used to detect signs of breast cancer. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps, and they can be utilized to retravel specific features of symptoms from medical images produced by X-ray, magnetic resonance imaging, computed tomography, and so forth. Gray level run-length matrix is the one of the texture extraction methods which has been successfully used to facilitate medical image analysis. However, it is computation-intensive method. We implemented it on GPU to accelerating extraction process for mammograms. The proposed method achieves significant speedup over CPU-based implementation.

Original language	English
Title of host publication	Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
Editors	Taesung Park, Young-Rae Cho, Xiaohua Tony Hu, Illhoi Yoo, Hyun Goo Woo, Jianxin Wang, Julio Facelli, Seungyoon Nam, Mingon Kang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2183-2186
Number of pages	4
ISBN (Electronic)	9781728162157
DOIs	https://doi.org/10.1109/BIBM49941.2020.9313307
State	Published - 16 Dec 2020
Event	2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 - Virtual, Seoul, Korea, Republic of Duration: 16 Dec 2020 → 19 Dec 2020

Publication series

Name	Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

Conference

Conference	2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
Country/Territory	Korea, Republic of
City	Virtual, Seoul
Period	16/12/20 → 19/12/20

Keywords

Feature Extraction
GLRLM
GPU
mammogram

UN SDGs

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

Access to Document

10.1109/BIBM49941.2020.9313307

Cite this

Hung, C. L., & Lin, C. Y. (2020). GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics. In T. Park, Y.-R. Cho, X. T. Hu, I. Yoo, H. G. Woo, J. Wang, J. Facelli, S. Nam, & M. Kang (Eds.), Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 (pp. 2183-2186). Article 9313307 (Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM49941.2020.9313307

Hung, Che Lun ; Lin, Chun Yuan. / GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics. Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020. editor / Taesung Park ; Young-Rae Cho ; Xiaohua Tony Hu ; Illhoi Yoo ; Hyun Goo Woo ; Jianxin Wang ; Julio Facelli ; Seungyoon Nam ; Mingon Kang. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 2183-2186 (Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020).

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title = "GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics",

abstract = "Mammograms are always used to detect signs of breast cancer. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps, and they can be utilized to retravel specific features of symptoms from medical images produced by X-ray, magnetic resonance imaging, computed tomography, and so forth. Gray level run-length matrix is the one of the texture extraction methods which has been successfully used to facilitate medical image analysis. However, it is computation-intensive method. We implemented it on GPU to accelerating extraction process for mammograms. The proposed method achieves significant speedup over CPU-based implementation.",

keywords = "Feature Extraction, GLRLM, GPU, mammogram",

author = "Hung, {Che Lun} and Lin, {Chun Yuan}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 ; Conference date: 16-12-2020 Through 19-12-2020",

year = "2020",

month = dec,

day = "16",

doi = "10.1109/BIBM49941.2020.9313307",

language = "English",

series = "Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2183--2186",

editor = "Taesung Park and Young-Rae Cho and Hu, {Xiaohua Tony} and Illhoi Yoo and Woo, {Hyun Goo} and Jianxin Wang and Julio Facelli and Seungyoon Nam and Mingon Kang",

booktitle = "Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020",

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Hung, CL & Lin, CY 2020, GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics. in T Park, Y-R Cho, XT Hu, I Yoo, HG Woo, J Wang, J Facelli, S Nam & M Kang (eds), Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020., 9313307, Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020, Institute of Electrical and Electronics Engineers Inc., pp. 2183-2186, 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020, Virtual, Seoul, Korea, Republic of, 16/12/20. https://doi.org/10.1109/BIBM49941.2020.9313307

GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics. / Hung, Che Lun; Lin, Chun Yuan.
Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020. ed. / Taesung Park; Young-Rae Cho; Xiaohua Tony Hu; Illhoi Yoo; Hyun Goo Woo; Jianxin Wang; Julio Facelli; Seungyoon Nam; Mingon Kang. Institute of Electrical and Electronics Engineers Inc., 2020. p. 2183-2186 9313307 (Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020).

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

TY - GEN

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AU - Hung, Che Lun

AU - Lin, Chun Yuan

PY - 2020/12/16

Y1 - 2020/12/16

N2 - Mammograms are always used to detect signs of breast cancer. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps, and they can be utilized to retravel specific features of symptoms from medical images produced by X-ray, magnetic resonance imaging, computed tomography, and so forth. Gray level run-length matrix is the one of the texture extraction methods which has been successfully used to facilitate medical image analysis. However, it is computation-intensive method. We implemented it on GPU to accelerating extraction process for mammograms. The proposed method achieves significant speedup over CPU-based implementation.

AB - Mammograms are always used to detect signs of breast cancer. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps, and they can be utilized to retravel specific features of symptoms from medical images produced by X-ray, magnetic resonance imaging, computed tomography, and so forth. Gray level run-length matrix is the one of the texture extraction methods which has been successfully used to facilitate medical image analysis. However, it is computation-intensive method. We implemented it on GPU to accelerating extraction process for mammograms. The proposed method achieves significant speedup over CPU-based implementation.

KW - Feature Extraction

KW - GLRLM

KW - GPU

KW - mammogram

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M3 - Conference contribution

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T3 - Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

SP - 2183

EP - 2186

BT - Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

A2 - Park, Taesung

A2 - Cho, Young-Rae

A2 - Hu, Xiaohua Tony

A2 - Yoo, Illhoi

A2 - Woo, Hyun Goo

A2 - Wang, Jianxin

A2 - Facelli, Julio

A2 - Nam, Seungyoon

A2 - Kang, Mingon

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

Y2 - 16 December 2020 through 19 December 2020

ER -

Hung CL, Lin CY. GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics. In Park T, Cho YR, Hu XT, Yoo I, Woo HG, Wang J, Facelli J, Nam S, Kang M, editors, Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 2183-2186. 9313307. (Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020). doi: 10.1109/BIBM49941.2020.9313307

GPU-Based Texture Analysis approach for Mammograms Institute of Biomedical Informatics

Abstract

Publication series

Conference

Keywords

UN SDGs

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