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自动化医学图像分割技术。

Automated medical image segmentation techniques.

作者信息

Sharma Neeraj, Aggarwal Lalit M

机构信息

School of Biomedical Engineering, Institute of Technology, Institute of Medical Sciences, Banaras Hindu University, Varanasi-221 005, UP, India.

出版信息

J Med Phys. 2010 Jan;35(1):3-14. doi: 10.4103/0971-6203.58777.

Abstract

Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

摘要

医学图像的精确分割是放射治疗计划中轮廓勾画的关键步骤。计算机断层扫描(CT)和磁共振成像(MR)是诊断、临床研究和治疗计划中使用最广泛的射线照相技术。本综述详细介绍了自动分割方法,特别是在CT和MR图像的背景下进行讨论。目的是探讨CT和MR图像分割中遇到的问题,以及当前医学图像分割方法的相对优缺点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d61/2825001/c8d6eb003ced/JMP-35-3-g001.jpg

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