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A Multi-Atlas-Based Hippocampus Segmentation Method for Automatic Brain MRI Images

A hippocampus, multi-atlas technology, applied in the field of medical image processing, can solve the problem of low accuracy of automatic hippocampus segmentation, achieve the effect of reducing the number, reducing the accuracy requirements, and overcoming the low accuracy

Active Publication Date: 2020-10-02
HUAZHONG UNIV OF SCI & TECH
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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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  • A Multi-Atlas-Based Hippocampus Segmentation Method for Automatic Brain MRI Images
  • A Multi-Atlas-Based Hippocampus Segmentation Method for Automatic Brain MRI Images
  • A Multi-Atlas-Based Hippocampus Segmentation Method for Automatic Brain MRI Images

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[0028] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0029] refer to figure 1 , is a schematic flow chart of the hippocampus segmentation method based on the multi-atlas automatic brain MRI image provided by the present invention, comprising the following steps:

[0030](1) The non-rigid registration method is used to register the atlas and the MRI image of the brain to be segmented;

[0031] (2) Calculate the similarity between the atlas image ...

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Abstract

The invention belongs to the technical field of medical image processing, and discloses a multi-atlas-based automatic brain MRI image hippocampus segmentation method, including (1) using a non-rigid registration method to align the atlas set with the brain MRI image to be segmented (2) Calculate the similarity between the atlas image and the target image, and construct and select the similarity atlas that is most conducive to the segmentation of the hippocampus of the target image; (3) Obtain the confidence weighted probability matrix of the atlas image; establish a context model based on the similarity atlas; Combining the confidence probability weighting matrix of the atlas image and the context model to obtain the hippocampus segmentation result in the target image; the present invention obtains accurate hippocampus segmentation results under the control of time complexity by exploring the image features and information used to segment the hippocampus in the atlas image. The hippocampus segmentation result of this method overcomes the problem of low accuracy in the automatic hippocampus segmentation of brain MRI images in the prior art.

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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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/174G06T7/33G06K9/62
CPCG06T7/174G06T7/337G06T2207/30016G06T2207/10088G06F18/22G06F18/24323
Inventor 刘宏许立君宋恩民
Owner HUAZHONG UNIV OF SCI & TECH
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