Chinese Medical Sciences Journal ›› 2019, Vol. 34 ›› Issue (2): 110-119.doi: 10.24920/003576
收稿日期:
2019-02-27
接受日期:
2019-04-28
出版日期:
2019-05-14
发布日期:
2019-05-16
通讯作者:
张道强
E-mail:dqzhang@nuaa.edu.cn
Sun Liang1,Zhang Li2,Zhang Daoqiang1,*()
Received:
2019-02-27
Accepted:
2019-04-28
Published:
2019-05-14
Online:
2019-05-16
Contact:
Zhang Daoqiang
E-mail:dqzhang@nuaa.edu.cn
摘要:
脑感兴趣区域分割是很多脑疾病计算机辅助分析的重要步骤。然而人类大脑具有复杂的解剖结构,同时脑磁共振(Magnetic Resonance, MR)图像处理通常会面临感兴趣区域灰度对比度低,个体之间和个体内的差异性等问题。为了解决这些问题,近年来,基于多图谱的很多方法被用于脑感兴趣区域的分割。在这篇综述中,我们对一些基于多图谱的脑MR图像分割方法进行系统的介绍,包括常用的配准工具箱,经典的标签融合方法,常用数据集以及多图谱分割在临床研究中的应用。我们认为,将图谱图像的解剖结构先验信息融入端到端的深度学习框架中用于脑图像感兴趣区域分割将是多图谱方法未来一个重要的研究方向。
Sun Liang,Zhang Li,Zhang Daoqiang. Multi-Atlas Based Methods in Brain MR Image Segmentation[J].Chinese Medical Sciences Journal, 2019, 34(2): 110-119.
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