Advanced imaging analysis and Machine Learning
Automated Segmentation of the Kidneys
Segmentation of kidneys is an important yet time consuming aspect of many studies. Existing automated segmentation methods using classical image processing are specific to a single pathology. Using a convolutional neural network the kidneys of both a healthy control and chronic kidney disease cohort can be segmented with better than human precision. This work has been published in Magnetic Resonance In Medicine
and is now being applied to large multi-site, multi-vendor cohorts.
The kidneys of a healthy volunteer segmented by a human (blue overlays) and automatically (red overlays) and the overlap between the two (magenta overlays).
Layer Based Analysis of the Kidneys
Most analysis of renal MRI data is based on defining regions of interest (ROI) for different tissues in the kidneys however this technique can be variable between investigators. To eliminate the subjectivity in ROI definition, the distance from each voxel to the surface of the kidney is calculated allowing the kidney to be divided into layers and quantitative calculated allowing the kidney to be divided into layers and quantitative maps to be expressed as a function of renal depth.