Department of Radiology, University of Chicago, Chicago, IL 60637, USA.
Annu Rev Biomed Eng. 2013;15:327-57. doi: 10.1146/annurev-bioeng-071812-152416. Epub 2013 May 13.
The role of breast image analysis in radiologists' interpretation tasks in cancer risk assessment, detection, diagnosis, and treatment continues to expand. Breast image analysis methods include segmentation, feature extraction techniques, classifier design, biomechanical modeling, image registration, motion correction, and rigorous methods of evaluation. We present a review of the current status of these task-based image analysis methods, which are being developed for the various image acquisition modalities of mammography, tomosynthesis, computed tomography, ultrasound, and magnetic resonance imaging. Depending on the task, image-based biomarkers from such quantitative image analysis may include morphological, textural, and kinetic characteristics and may depend on accurate modeling and registration of the breast images. We conclude with a discussion of future directions.
乳腺图像分析在放射科医生进行癌症风险评估、检测、诊断和治疗中的作用不断扩大。乳腺图像分析方法包括分割、特征提取技术、分类器设计、生物力学建模、图像配准、运动校正和严格的评估方法。我们对这些基于任务的图像分析方法的现状进行了综述,这些方法是为乳腺摄影、断层合成、计算机断层扫描、超声和磁共振成像的各种图像采集方式开发的。根据任务的不同,基于图像的生物标志物可能包括形态、纹理和动力学特征,并且可能依赖于对乳腺图像的准确建模和配准。最后,我们讨论了未来的发展方向。