期刊
ACADEMIC RADIOLOGY
卷 14, 期 11, 页码 1350-1366出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.acra.2007.07.020
关键词
PACS; probabilistic atlas; children; brain segmentation; expectation-maxinuzation; registration-based segmentation
资金
- MRC [MC_U120088465, MC_U120061309] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [GR/S08916/01] Funding Source: researchfish
- Medical Research Council [MC_U120088465, MC_U120061309] Funding Source: researchfish
- Medical Research Council [MC_U120088465, MC_U120061309] Funding Source: Medline
Rationale and Objectives. This article deals with an automatic tissue segmentation of brain magnetic resonance imaging (MRI) in young children. Materials and Methods. We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the brain MRI in young children. We develop a method of creation of a population-specific atlas in young children using a single manual segmentation. The method is based on nonlinear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. Results. Using this approach, we significantly improve the performance of the popular expectation- maximization algorithm on brain MRI in young children. The method can be used for building probabilistic atlases with any number of structures. We compare resulting algorithm with nonrigid registration-based label propagation. Conclusions. Finally, both methods are used to measure the volume of seven brain structures and measure the growth between 1 and 2 years of age.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据