Computer-aided diagnostic models in breast cancer screening.
Computer-aided diagnostic models in breast cancer screening.
复制标题
DOI：
10.2217/iim.10.24
复制
发表时间：
2010-06-01
期刊：
影响因子：
--
通讯作者：
Burnside, Elizabeth S
中科院分区：
文献类型：
--
作者：
Ayer, Turgay;Ayvaci, Mehmet Us;Burnside, Elizabeth S
乳房X线摄影是乳腺癌检测和诊断的最常见方式，通常由超声和MRI补充。然而，这些图像中乳腺癌的早期体征和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，已经提出了计算机辅助检测和计算机辅助诊断（CADx）模型。在过去的20年里，已经发表了大量的研究，计算机辅助检测和CADx模型。本文的目的是提供对CADx模型的全面调查，这些模型已被提议用于辅助乳腺X射线摄影、超声和MRI判读。我们总结了值得注意的研究，根据他们考虑的筛选方式，并描述了计算机模型的类型，输入数据的大小，特征选择方法，输入特征类型，参考标准和性能指标的每项研究。我们还列出了现有的CADx模型的局限性，并提供了几个可能的未来研究方向。
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.