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1. Segmentation and synthesis of pelvic region CT images via neural networks trained on XCAT phantom data
Master-uppsats, Linköpings universitet/DatorseendeSammanfattning : Deep learning methods for medical image segmentation are hindered by the lack of training data. This thesis aims to develop a method that overcomes this problem. Basic U-net trained on XCAT phantom data was tested first. The segmentation results were unsatisfactory even when artificial quantum noise was added. LÄS MER
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