Liver tumour segmentation from MR-Linac
Background
Accurate liver tumour delineation is essential for MR-guided radiotherapy, yet it remains challenging due to low soft-tissue contrast variability, respiratory motion artefacts, and anatomical deformation between fractions. The MR-Linac provides on-treatment MRI at every fraction, offering an opportunity to improve contouring accuracy and support adaptive workflows — but the volume and complexity of this data demand automated solutions.
Aims
- Develop robust deep learning–based segmentation models for liver tumours in MR-Linac imaging data.
- Support adaptive radiotherapy workflows through reliable tumour localisation and contouring in real-time or near real-time clinical environments.
- Improve the precision of radiation treatment delivery by enabling accurate fraction-by-fraction tumour tracking.