Automatic segmentation of the striatum and globus pallidus using MIST: Multimodal Image Segmentation Tool

作者：Visser Eelke^*; Keuken Max C; Douaud Gwenaelle; Gaura Veronique; Bachoud Levi Anne Catherine; Remy Philippe; Forstmann Birte U; Jenkinson Mark

来源：NeuroImage, 2016, 125: 479-497.

DOI：10.1016/j.neuroimage.2015.10.013

• Segmentation
• Multimodal
• Striatum
• Globus pallidus
• Brain
• Huntington

Accurate segmentation of the subcortical structures is frequently required in neuroimaging studies. Most existing methods use only a T-1-weighted MRI volume to segment all supported structures and usually rely on a database of training data. We propose a new method that can use multiple image modalities simultaneously and a single reference segmentation for initialisation, without the need for a manually labelled training set. The method models intensity profiles in multiple images around the boundaries of the structure after nonlinear registration. It is trained using a set of unlabelled training data, which may be the same images that are to be segmented, and it can automatically infer the location of the physical boundary using user-specified priors. We show that the method produces high-quality segmentations of the striatum, which is clearly visible on T-1-weighted scans, and the globus pallidus, which has poor contrast on such scans. The method compares favourably to existing methods, showing greater overlap with manual segmentations and better consistency.

• 出版日期2016-1-15
• 单位中国地震局