Hippocampus three-dimensional semantic network segmentation method based on multi-scale feature multi-path attention fusion mechanism
A multi-scale feature and semantic network technology, applied in the field of medical image processing, to achieve the effect of improving segmentation accuracy
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[0049]The invention can automatically process brain magnetic resonance images and realize automatic three-dimensional segmentation of the hippocampus; aiming at problems such as the position change and complex shape of the hippocampus, a more effective image feature processing module is used to construct a semantic segmentation network to improve the segmentation of the trained model Accuracy, providing more reliable information support for the diagnosis of Alzheimer's disease.
[0050] as attached figure 1 As shown, a 3D hippocampus semantic network segmentation method based on multi-scale feature multi-channel attention fusion mechanism includes the following five steps:
[0051] 1. Obtain and preprocess the hippocampal image and label data in the ADNI database;
[0052] 2. 3D hippocampus semantic segmentation network structure design based on multi-scale feature extraction and multi-channel attention fusion mechanism;
[0053] 3. Training and verification data set divisio...
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