While high resolution 3D MR images are well suited for automated cartilage segmentation in the human knee joint, they are not routinely acquired in clinical practice which limits opportunities for reliable segmentation of cartilage using automated algorithms. We propose a neural network for generating synthetic MR images with enhanced contrast and higher spatial resolution from routine, low resolution clinical knee scans. Segmentation results showed that accurate cartilage segmentation can be obtained using the synthesised images.
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