Keywords: Data Processing, PerfusionRenal perfusion quantification is of importance in the post-operative surveillance of the allograft in translated patients. Together with cortical perfusion measurement, there is a strong interest in the quantification of medullary perfusion values, which requires an additional segmentation step of renal compartments. We applied Gaussian Mixture Models over renal MRI dataset to automatically extract the labels for each compartment to separately calculate cortical and medullary perfusion values. Proposed method showed performance metrics above 85% against ground truth labels and correlation coefficient above 96% and 58% for cortical and medullary perfusion values comparing with ground truth perfusion values.
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