A detector for MVI based on lesion segmentation network, radiomics extractor and a classifier (better description comes later).
PyTorch implementation 3D U-Net and its variants:
- Standard 3D U-Net based on 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation Özgün Çiçek et al.
- Residual 3D U-Net based on Superhuman Accuracy on the SNEMI3D Connectomics Challenge Kisuk Lee et al. The code allows for training the U-Net for both: semantic segmentation (binary and multi-class) and regression problems (e.g. de-noising, learning deconvolutions).
This is implemented on pyradiomics