Review of Research on Biomedical Image Processing Based on Pattern Recognition

Yingying XU; Hongbin SHEN

doi:10.11999/JEIT190657

Volume 42 Issue 1

Jan. 2020

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Article Navigation > Journal of Electronics & Information Technology > 2020 > 42(1): 201-213

Yingying XU, Hongbin SHEN. Review of Research on Biomedical Image Processing Based on Pattern Recognition[J]. Journal of Electronics & Information Technology, 2020, 42(1): 201-213. doi: 10.11999/JEIT190657

Citation:

Yingying XU, Hongbin SHEN. Review of Research on Biomedical Image Processing Based on Pattern Recognition[J]. Journal of Electronics & Information Technology, 2020, 42(1): 201-213. doi: 10.11999/JEIT190657

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Review of Research on Biomedical Image Processing Based on Pattern Recognition

doi: 10.11999/JEIT190657

Yingying XU^{1, 2},
Hongbin SHEN^{2
,
,}

1.
School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
2.
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai 200240, China

Funds: The National Natural Science Foundation of China (61803196, 61671288), The Natural Science Foundation of Guangdong Province (2018030310282)

Received Date: 2019-08-29
Rev Recd Date: 2019-11-12

Available Online: 2019-11-18

Publish Date: 2020-01-21

Abstract

Abstract

Pattern recognition algorithms can discover valuable information from mass data of biomedical images as guide for basic research and clinical application. In recent years, with improvement of the theory and practice of pattern recognition and machine learning, especially the appearance and application of deep learning, the crossing researches among artificial intelligence, pattern recognition, and biomedicine become a hotspot, and achieve many breakthrough successes in related fields. This review introduces briefly the common framework and algorithms of image pattern recognition, summarizes the applications of these algorithms to biomedical image analysis including fluorescence microscopic images, histopathological images, and medical radiological images, and finally analyzes and prospect several potential research directions.
- Image processing,
- Biomedical images,
- Pattern recognition,
- Deep learning

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References(100)

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