Wang Shijun, Burtt Karen, Turkbey Baris, Choyke Peter, Summers Ronald M
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10, Room 1C224, Bethesda, MD 20892-1182, USA.
Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Building 10, Room B3B69F, Bethesda, MD 20892-1088, USA.
Biomed Res Int. 2014;2014:789561. doi: 10.1155/2014/789561. Epub 2014 Dec 1.
Prostate cancer (PCa) is the most commonly diagnosed cancer among men in the United States. In this paper, we survey computer aided-diagnosis (CADx) systems that use multiparametric magnetic resonance imaging (MP-MRI) for detection and diagnosis of prostate cancer. We review and list mainstream techniques that are commonly utilized in image segmentation, registration, feature extraction, and classification. The performances of 15 state-of-the-art prostate CADx systems are compared through the area under their receiver operating characteristic curves (AUC). Challenges and potential directions to further the research of prostate CADx are discussed in this paper. Further improvements should be investigated to make prostate CADx systems useful in clinical practice.
前列腺癌（PCa）是美国男性中最常被诊断出的癌症。在本文中，我们调研了使用多参数磁共振成像（MP-MRI）进行前列腺癌检测和诊断的计算机辅助诊断（CADx）系统。我们回顾并列出了图像分割、配准、特征提取和分类中常用的主流技术。通过15个先进前列腺CADx系统的接收器操作特征曲线（AUC）下的面积来比较它们的性能。本文讨论了前列腺CADx研究的挑战和潜在方向。应研究进一步的改进措施，以使前列腺CADx系统在临床实践中发挥作用。
