Histopathological image analysis: a review.
Histopathological image analysis: a review.
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DOI：
10.1109/rbme.2009.2034865
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发表时间：
2009
影响因子：
17.6
通讯作者：
Yener B
中科院分区：
文献类型：
--
作者：
Gurcan MN;Boucheron LE;Can A;Madabhushi A;Rajpoot NM;Yener B
在过去的十年中，显着增加的计算能力和改进的图像分析算法，使强大的计算机辅助分析方法的放射性数据的发展。随着最近全载玻片数字扫描仪的出现，组织病理学载玻片现在可以数字化并以数字图像形式存储。因此，数字化组织病理学现在已经变得适合于计算机化图像分析和机器学习技术的应用。类似于计算机辅助诊断（CAD）算法在医学成像中补充放射科医生的意见的作用，CAD算法已经开始被开发用于疾病检测、诊断和预后预测以补充病理科医生的意见。本文综述了近年来组织病理学数字化CAD技术的研究进展。本文还简要介绍了新的图像分析技术的发展和应用的一些特定的组织病理学相关的问题正在追求在美国和欧洲。
Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement to the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe.