Department of Radiology, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands.
Radiology. 2011 Dec;261(3):719-32. doi: 10.1148/radiol.11091710.
Computer-aided diagnosis (CAD), encompassing computer-aided detection and quantification, is an established and rapidly growing field of research. In daily practice, however, most radiologists do not yet use CAD routinely. This article discusses how to move CAD from the laboratory to the clinic. The authors review the principles of CAD for lesion detection and for quantification and illustrate the state-of-the-art with various examples. The requirements that radiologists have for CAD are discussed: sufficient performance, no increase in reading time, seamless workflow integration, regulatory approval, and cost efficiency. Performance is still the major bottleneck for many CAD systems. Novel ways of using CAD, extending the traditional paradigm of displaying markers for a second look, may be the key to using the technology effectively. The most promising strategy to improve CAD is the creation of publicly available databases for training and validation. This can identify the most fruitful new research directions, and provide a platform to combine multiple approaches for a single task to create superior algorithms.
计算机辅助诊断(CAD)包括计算机辅助检测和定量分析,是一个成熟且快速发展的研究领域。然而,在日常实践中,大多数放射科医生尚未常规使用 CAD。本文讨论了如何将 CAD 从实验室转移到临床。作者回顾了 CAD 在病灶检测和定量分析方面的原理,并通过各种示例说明了其最新进展。讨论了放射科医生对 CAD 的要求:性能足够、不增加阅读时间、无缝工作流程集成、监管批准和成本效益。性能仍然是许多 CAD 系统的主要瓶颈。使用 CAD 的新方法,扩展传统的显示标记进行二次观察的范例,可能是有效使用该技术的关键。提高 CAD 性能的最有前途的策略是创建用于培训和验证的公共数据库。这可以确定最有前途的新研究方向,并提供一个平台,将多种方法结合用于单个任务,以创建优越的算法。