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METHOD AND APPARATUS FOR ATLAS/MODEL-BASED SEGMENTATION OF MAGNETIC RESONANCE IMAGES WITH WEAKLY SUPERVISED EXAMINATION-DEPENDENT LEARNING
METHOD AND APPARATUS FOR ATLAS/MODEL-BASED SEGMENTATION OF MAGNETIC RESONANCE IMAGES WITH WEAKLY SUPERVISED EXAMINATION-DEPENDENT LEARNING
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机译:带有弱监督的依赖于学习的基于Atlas /模型的磁共振图像分割方法和装置
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摘要
In a magnetic resonance (MR) apparatus and segmentation method, a region in an MR image, acquired from a scan of a patient with an MR scanner of the apparatus, is provided to a computer for segmentation of the region from the overall image dataset. The segmentation takes place based on a classification of image elements of the image dataset, and the classification is iteratively re-trained in a weakly supervised learning algorithm based on examination-specific information provided to the computer.
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