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 |
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| 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 | |
| State | Published - 16 12 2020 |
| Event | 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 - Virtual, Seoul, Korea, Republic of Duration: 16 12 2020 → 19 12 2020 |
Publication series
| Name | Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 |
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Conference
| Conference | 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 |
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| Country/Territory | Korea, Republic of |
| City | Virtual, Seoul |
| Period | 16/12/20 → 19/12/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- Feature Extraction
- GLRLM
- GPU
- mammogram