We present an improved imaging and data analysis strategy for kidney MRI in mouse models of polycystic kidney disease. By registering multiple high resolution datasets at lower SNR, slow movement is compensated for and high resolution datasets with high quality and fine detail are achieved, allowing for detection and longitudinal tracking of kidney volume as well as cyst number and size. We established automatic cyst detection and are developing automatic kidney segmentation, for accurate and reliable assessment of polycystic kidney disease in mouse models.
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