Ayer Turgay, Ayvaci Mehmet Us, Liu Ze Xiu, Alagoz Oguzhan, Burnside Elizabeth S
Industrial & Systems Engineering Department, University of Wisconsin, Madison, WI, USA.
Imaging Med. 2010 Jun 1;2(3):313-323. doi: 10.2217/IIM.10.24.
Mammography is the most common modality for breast cancer detection and diagnosis and is often complemented by ultrasound and MRI. However, similarities between early signs of breast cancer and normal structures in these images make detection and diagnosis of breast cancer a difficult task. To aid physicians in detection and diagnosis, computer-aided detection and computer-aided diagnostic (CADx) models have been proposed. A large number of studies have been published for both computer-aided detection and CADx models in the last 20 years. The purpose of this article is to provide a comprehensive survey of the CADx models that have been proposed to aid in mammography, ultrasound and MRI interpretation. We summarize the noteworthy studies according to the screening modality they consider and describe the type of computer model, input data size, feature selection method, input feature type, reference standard and performance measures for each study. We also list the limitations of the existing CADx models and provide several possible future research directions.
乳腺钼靶摄影是乳腺癌检测和诊断最常用的方法，常辅以超声和磁共振成像（MRI）。然而，这些图像中乳腺癌早期迹象与正常结构之间的相似性使得乳腺癌的检测和诊断成为一项艰巨的任务。为了帮助医生进行检测和诊断，人们提出了计算机辅助检测和计算机辅助诊断（CADx）模型。在过去20年里，针对计算机辅助检测和CADx模型都发表了大量研究。本文的目的是对为辅助乳腺钼靶摄影、超声和MRI解读而提出的CADx模型进行全面综述。我们根据它们所考虑的筛查方式总结了值得注意的研究，并描述了每个研究的计算机模型类型、输入数据大小、特征选择方法、输入特征类型、参考标准和性能指标。我们还列出了现有CADx模型的局限性，并提供了几个可能的未来研究方向。
