基于双边双视角的乳腺癌检测与分类方法研究

项目名称： 基于双边双视角的乳腺癌检测与分类方法研究

项目编号： No.61502025

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 计算机科学学科

项目作者： 李艳凤

作者单位： 北京交通大学

项目金额： 20万元

中文摘要： 我国已成为乳腺癌发病率增长速度最快的国家之一，且呈年轻化趋势。对乳腺癌的早期检测与诊断是提高患者治愈率的关键。基于图像处理和模式识别理论，可获取乳腺X线图像定量客观的分析结果，有助于乳腺癌早期检测与分类。现有检测与分类方法存在的主要问题有：(1) 大多基于单幅或两幅图像进行病变检测，缺少双边双视角图像的病变检测方法，其与医生阅片机制存在一定差别。(2) 大多基于单个视角提取病变特征和实现病变良恶性分类，缺少双视角病变特征融合，同时在特征提取时忽略了病变中心与外围区域的差异性。.针对上述问题，本课题的主要研究内容为：(1) 模拟医生阅片机制，研究基于双边双视角图像的肿块检测方法。(2) 研究肿块中心与外围区域差异的特征提取以及双视角肿块特征融合，实现基于双视角图像的肿块良恶性分类方法。本课题是信息学科与医学学科的交叉学科，具有重要的理论意义，同时对乳腺癌早期检测与诊断将起到积极的推动作用。

中文关键词： 图像处理；模式识别；特征提取；特征融合；分类器设计

英文摘要： China has become one of the countries where the breast cancer morbidity is with the fastest speed. Moreover, breast cancer is getting more frequent among young people in China. Early detection is the key to increase recovery rate for breast cancer. Using the theory of image processing and pattern recognition, objective and quantitative results can be obtained, which contributes to detecting and classifying the breast cancer at an early stage. The existing detection and classification methods bared some problems. Lesion detection was more on single or two mammograms, and less on bilateral and two-view information. This was not fit with radiologist reading. Lesion feature extraction and classification was more on single view, and less on the fusion of two-view information. Moreover, the difference between the lesion center and lesion periphery was ignored in feature extraction..Aiming at these problems, the following contents will be studied. Simulating the radiologist reading, mass detection based on bilateral and two-view information will be studied. Lesion feature representing the difference between the lesion center and lesion periphery will also be studied. Fusing mass features from two views, classifying mass as benign or malignant based on two-view information can be implemented. The information discipline and medical discipline will be combined in this project research. This study has important significance in theory and will also promote the early detection and classification of breast cancer.

英文关键词： image processing;pattern recognition;feature extraction;information fusion;classifier design