Clinic and Polyclinic for Radiation Therapy and Radio-Oncology
LMU Adaptive Radiation Therapy Lab
- Department/Institute:
- Clinic and Polyclinic for Radiation Therapy and Radio-Oncology / LMU Adaptive Radiation Therapy Lab https://lmu-art-lab.userweb.mwn.de/
- Subject area:
- AI in Radiation Therapy/Medical Physics
- Name of supervisor:
- Prof. Guillaume Landry
- Number of open position:
- 1
- Project title:
- Real time adaptive dose calculation methods
- Project time
- Full Doctoral Study-Model: 48 months
- Language requirements:
- English
- Academic requirements:
- Candidates with experience in medical physics and deep learning would be ideal.
Prerequisites are good programming knowledge (python, pytorch/keras/tensorflow) and knowledge of the physics of radiation therapy and imaging.
Familiarity with medical imaging topics would be desirable.
This can be expected from a physics graduate student, who has ideally already worked on a topic related to medical radiation physics in their master thesis. Equivalent engineering backgrounds may also be compatible.
Project description:
The advancement of real time imaging based on adaptive radiotherapy platforms such as MR-linacs allows the development of dose personalization at increasingly finer time scales. Current workflows rely on online radiation therapy plan adaptation on a daily basis; however real time imaging advances may make it possible continuously re-optimize radiation delivery based on continuous dose reconstruction. One of the critical components of such a workflow is fast dose calculation on real time images, such as MRI or CBCT. Classically, this requires conversion to pseudo CT images (for high electron density accuracy). Our project aims at developing fast dose calculation methods based on artificial intelligence directly on MRI or CBCT. We aim to build on our prior work in this area (https://iopscience.iop.org/article/10.1088/1361-6560/ad7f1e/meta) including expertise in Monte Carlo simulation and training of AI models. The project will also strive towards the organization of a data challenge on the topic.
To applicants: Please send following initial application documents to LMU-CSC Office before 15th December:
- Resume and Research Motivation Letter
- Certificate of Proficiency in English, equivalent to IELTS Test Academic 6.5 (no module below 6) or TOEFL IBT 95, is required
- Two letters of recommendation directly sent from your current Supervisors/Professors to LMU-CSC Office
Contact LMU-CSC Office: csc.international@lmu.de