computer-aided diagnosis in mammography using content-based image retrieval approaches current status and future perspectives利用基于内容的图像检索方法计算机辅助诊断乳房x光检查当前状态和未来的观点.pdf

Algorithms 2009, 2, 828-849; doi:10.3390/a2020828 OPEN ACCESS algorithms ISSN 1999-4893 /journal/algorithms Review Computer-Aided Diagnosis in Mammography Using Content- Based Image Retrieval Approaches: Current Status and Future Perspectives Bin Zheng Imaging Research Center, Department of Radiology, University of Pittsburgh, 3362 Fifth Avenue, Room 128, Pittsburgh, PA 15213, USA; E-mail address: zhengb@ Received: 29 April 2009; in revised form: 28 May 2009 / Accepted: 28 May 2009 / Published: 4 June 2009 Abstract: As the rapid advance of digital imaging technologies, the content-based image retrieval (CBIR) has became one of the most vivid research areas in computer vision. In the last several years, developing computer-aided detection and/or diagnosis (CAD) schemes that use CBIR to search for the clinically relevant and visually similar medical images (or regions) depicting suspicious lesions has also been attracting research interest. CBIR-based CAD schemes have potential to provide radiologists with “visual aid” and increase their confidence in accepting CAD-cued results in the decision making. The CAD performance and reliability depends on a number of factors including the optimization of lesion segmentation, feature selection, reference database size, computational efficiency, and relationship between the clinical relevance and visual similarity of the CAD results. By presenting and comparing a numbe