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- W4385555014 abstract "Atherosclerotic plaque is a major cause of ischemic stroke. Some arterial morphological features obtained from MR vessel wall images show great potential for identifying high-risk plaques. Deep learning has now been applied to the automatic segmentation of vessel walls to accurately and efficiently measure arterial morphological features. However, the accuracy of the existing segmentation methods is not yet high enough for clinical practical applications. This study proposed a new segmentation framework with custom convolutional trajectories for automatic segmentation of arterial vessel wall and the framework improved the accuracy of vessel wall segmentation." @default.
- W4385555014 created "2023-08-04" @default.
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- W4385555014 date "2023-08-03" @default.
- W4385555014 modified "2023-09-27" @default.
- W4385555014 title "Automatic analysis of carotid vessel wall in MR black blood images using custom convolutional trajectories" @default.
- W4385555014 doi "https://doi.org/10.58530/2022/3158" @default.
- W4385555014 hasPublicationYear "2023" @default.
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