We present an improved MRI acquisition and data processing pipeline to assess disease progression in mouse models of polycystic kidney disease. High-resolution anatomical T2 weighted images as well as T2 mapping are used to track changes in kidney volume, cyst burden and tissue composition. We established versatile deep-learning automatic kidney segmentation, trained on a range of kidney disease stages, animal models and image resolutions.
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