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Computer Aided Screening of Breast Cancer Based on the Processing of Mammograms

基于乳房X线照片处理的计算机辅助乳腺癌筛查

基本信息

批准号：
08555100
负责人：
KUBATAKE Hidefumi
金额：
$ 1.54万
依托单位：
TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (A)
财政年份：
1996
资助国家：
日本
起止时间：
1996 至 1997
项目状态：
已结题

项目摘要

Mammogram is considered to be the most reliable modality for the screening of breast cancer, and screening program using mammography has become popular for the detection of early breast cancer. Computer aided diagnosis (CAD) system for mammography has the possibility to be used as a second reader to increase reliability of mass screening. And development of CAD system for mammography has become one of the most important subjects of research in the area of medical image processing. CAD system for mammography consists of two subsystems in general.One of them is a tumor mass detection system and the other is a clustered microcalcification detection system. In this research, we have developed new methods to detect malignant tumors and clustered microcalcifications.In the tumor detection system, a nonlinear filter called Iris filter has been adopted to enhance rounded opacities on mammogram. A new boundary estimation method of tumor candidates and feature parameters to extract boundary characteristics of tumors have been adopted. In the clustered microcalcification detection system, morphological operation to detect microcalcifications has been developed. And adaptive processing is also adopted to keep the system optimum under various imaging conditions and patient variations.The system performance has been evaluated at National Cancer Center Hospital East.Mammograms taken from outpatients during the past one and a half years were used as unknown samples. The number of mammograms is 3812. The system performance was as follows.True positive detection rate and average number of false positives of the malignant tumor detection system were 88% and 1.34 per image, respectively. Those of the clustered microcalcification detection system were 94% and 0.39, respectively. These results show the effectiveness of proposed system..

乳房x光检查被认为是最可靠的乳腺癌筛查方式，使用乳房x光检查的筛查程序已成为早期乳腺癌检测的流行方法。计算机辅助诊断（CAD）系统用于乳房x线摄影有可能作为第二阅读器，以提高可靠性的大规模筛查。乳房x线摄影CAD系统的开发已成为医学图像处理领域的重要研究课题之一。乳房x线摄影CAD系统一般由两个子系统组成。其中一个是肿瘤肿块检测系统，另一个是集群微钙化检测系统。在本研究中，我们开发了检测恶性肿瘤和聚集性微钙化的新方法。在肿瘤检测系统中，采用了一种称为虹膜滤波器的非线性滤波器来增强乳房x光片上的圆形浑浊。采用一种新的候选肿瘤边界估计方法和特征参数来提取肿瘤的边界特征。在簇状微钙化检测系统中，提出了形态学操作检测微钙化的方法。并采用自适应处理，使系统在各种成像条件和患者变化下保持最佳状态。该系统的性能已在国家癌症中心东医院进行了评估。过去一年半门诊患者的乳房x光照片被用作未知样本。乳房x光检查的次数是3812次。系统性能表现如下。恶性肿瘤检测系统的真阳性检出率为88%，假阳性平均次数为1.34张/张。聚类微钙化检测系统的检出率分别为94%和0.39。这些结果表明了所提系统的有效性。