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Computer-Aided Diagnosis in Medical Imaging: Historical Review Current Status and Future Potential

机译:医学影像中的计算机辅助诊断:历史回顾现状和未来潜力

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摘要

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. In this article, the motivation and philosophy for early development of CAD schemes are presented together with the current status and future potential of CAD in a PACS environment. With CAD, radiologists use the computer output as a “second opinion” and make the final decisions. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms.A CAD scheme that makes use of lateral chest images has the potential to improve the overall performance in the detection of lung nodules when combined with another CAD scheme for PA chest images. Because vertebral fractures can be detected reliably by computer on lateral chest radiographs, radiologists’ accuracy in the detection of vertebral fractures would be improved by the use of CAD, and thus early diagnosis of osteoporosis would become possible. In MRA, a CAD system has been developed for assisting radiologists in the detection of intracranial aneurysms. On successive bone scan images, a CAD scheme for detection of interval changes has been developed by use of temporal subtraction images. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for chest CAD may include the computerized detection of lung nodules, interstitial opacities, cardiomegaly, vertebral fractures, and interval changes in chest radiographs as well as the computerized classification of benign and malignant nodules and the differential diagnosis of interstitial lung diseases. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with known pathology, which would be very similar to a new unknown case, from PACS when a reliable and useful method has been developed for quantifying the similarity of a pair of images for visual comparison by radiologists.
机译:计算机辅助诊断(CAD)已成为医学成像和诊​​断放射学的主要研究主题之一。本文介绍了CAD方案早期开发的动机和理念,以及在PACS环境中CAD的现状和未来潜力。借助CAD,放射线医师会将计算机输出作为“第二意见”,并做出最终决定。 CAD是通过平等考虑医生和计算机的角色而建立的概念,而自动计算机诊断是仅基于计算机算法的概念。使用CAD,计算机的性能不必与医师的性能相当或更好,而需要与医师的性能互补。实际上,已经使用了大量的CAD系统来协助医生在乳房X线照片上早期发现乳腺癌。利用胸部侧面图像的CAD方案有可能在检测肺结节时改善整体性能结合另一种用于PA胸部图像的CAD方案。由于可以通过计算机在胸部胸部X光片上可靠地检测出椎体骨折,因此放射科医师通过使用CAD可以提高椎体骨折检测的准确性,从而可以早期诊断骨质疏松症。在MRA中,已经开发了一个CAD系统,以协助放射科医生检测颅内动脉瘤。在连续的骨扫描图像上,已经通过使用时间相减图像开发了用于检测间隔变化的CAD方案。将来,许多CAD方案都可以作为软件包组装并作为PACS的一部分实施。例如,用于胸部CAD的包装可能包括计算机检测肺结节,间质混浊,心脏肿大,椎骨骨折以及胸部X线照片的间隔变化,以及对良性和恶性结节进行计算机分类以及间质性肺病的鉴别诊断。为了帮助进行鉴别诊断,当已经开发出一种可靠且有用的方法时,可以从PACS中搜索和检索具有已知病理学的图像(或病变),这与新的未知病例非常相似。量化一对图像的相似性,以供放射科医生进行视觉比较。

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    Kunio Doi;

  • 作者单位
  • 年(卷),期 -1(31),4-5
  • 年度 -1
  • 页码 198–211
  • 总页数 29
  • 原文格式 PDF
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