徐莹莹^{1, 2},
沈红斌^2,,
1.南方医科大学生物医学工程学院 广州 510515
2.上海交通大学图像处理与模式识别研究所 上海 200240
基金项目:国家自然科学基金(61803196, 61671288)，广东省自然科学基金(2018030310282)

详细信息

作者简介:徐莹莹：女，1989年生，副教授，研究方向为生物图像信息学与模式识别
沈红斌：男，1979年生，教授，研究方向为模式识别、数据挖掘以及生物信息学

通讯作者:沈红斌　hbshen@sjtu.edu.cn

中图分类号:TN911.73

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被引次数:0

出版历程

收稿日期:2019-08-29
修回日期:2019-11-12
网络出版日期:2019-11-18
刊出日期:2020-01-21

Review of Research on Biomedical Image Processing Based on Pattern Recognition

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)


摘要
摘要:海量的生物医学图像蕴含着丰富的信息，模式识别算法能够从中挖掘规律并指导生物医学基础研究和临床应用。近年来，模式识别和机器学习理论和实践不断完善，尤其是深度学习的广泛研究和应用，促使人工智能、模式识别与生物医学的交叉研究成为了当前的前沿热点，相关的生物医学图像研究有了突破式的进展。该文首先简述模式识别的常用算法，然后总结了这些算法应用于荧光显微图像、组织病理图像、医疗影像等多种图像中的挑战性和国内外研究现状，最后对几个潜在研究方向进行了分析和展望。
关键词:图像处理/
生物医学图像/
模式识别/
深度学习
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.
Key words:Image processing/
Biomedical images/
Pattern recognition/
Deep learning



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