Automated Organ Segmentation in MRI
In this use case we realized a robust and accurate segmentation of the liver, the spleen, the kidneys and the heart in various Magnetic Resonance Imaging (MRI) sequences. The approach has proven to cope with even non-standardized image intensities and varying contrast in MRI.
All aspects of a typical AI service project have been realized in-house by our annotation and software experts.
Data
Input data:
- 120 3D MRI series of the torso
Annotation classes:
- Liver
- Spleen
- Kidney left and right separately
- Heart
A set of neighboring axial slices taken from an evaluation MRI series that was not contained within training. The automatically segmented organs are marked in color.
Results
We have achieved an average DICE coefficient across the sequences of 92%.