Hippocampus segmentation method for automatic brain MRI (Magnetic Resonance Image) on the basis of multiple atlases

Abstract

The invention belongs to the technical field of medical image processing, and discloses a hippocampus segmentation method for an automatic brain MRI (Magnetic Resonance Image) on the basis of multipleatlases. The method comprises the following steps that: (1) adopting a non-rigid registration method to carry out registration on atlas set and a brain MRI to be segmented; (2) calculating a similarity between an atlas image and a target image, and constructing and selecting a similar atlas which is most favorable for target image hippocampus segmentation; and (3) obtaining the confidence coefficient weighting probability matrix of the atlas image, establishing a context model based on the similar atlas, and combining the confidence coefficient weighting probability matrix of the atlas imagewith the context model to obtain a hippocampus segmentation result in the target image. By use of the method, image features and image used for segmenting the hippocampus in the atlas image can be mined, an accurate hippocampus segmentation result can be obtained under a situation that time complexity is controlled, and the problem in the prior art that the automatic segmentation accuracy of the hippocampus for the brain MRI image is low is overcome.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, and more particularly relates to a hippocampus segmentation method based on multi-atlas automatic brain MRI images. Background technique [0002] At present, the marking of the hippocampus is mainly based on brain MRI (magnetic resonance image, also known as Magnetic Resonance Image, MRI) images to segment the hippocampus, identify the region or boundary where the hippocampus is located; use the information provided by multiple atlas images The method of labeling brain MRI images is called multi-atlas labeling method. [0003] The multi-atlas labeling method mainly includes two steps: (1) spatially register all the atlases and the target image, so that the information of the atlases can be accurately mapped to the target image to be segmented. (2) Use the label fusion strategy to evaluate the labels provided by each map to obtain the segmentation results of the target image. In...

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Problems solved by technology

[0009] In view of the above defects or improvement needs of the prior art, the present invention provides a multi-atlas-based automatic brain MRI image hippocampus segmentation method, the purpose of which is to improve the existing automatic hippocampus segmentation in brain MRI images. Technical problems with low precision

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