LMU Adaptive Radiation Therapy Lab


The LMU Adaptive Radiation Therapy Lab of the Department of Radiation Oncology, LMU University Hospital, led by Prof. Guillaume Landry, is active at the intersection of imaging and radiation therapy; we aim at exploiting the latest developments in artificial intelligence and imaging to improve radiation therapy.

Latest News

Two 2023 articles selected as Editor's Choice
Recent articles from Elia Lombardo and Moritz Rabe have been selected as Editor’s Choice at the journal Medical Physics in 2023. Have a look at Elia’s and Moritz’ papers.
Apr 9, 2024
Two 2023 articles selected as Editor's Choice
Emerging Talent Award (“Prix de la relève”)
Guillaume Landry was the recipient of the Emerging Talent Award of the Faculty of Sciences of Moncton University, awarded every 2 years to emeging talents under 40.
Apr 5, 2024
Emerging Talent Award (“Prix de la relève”)
First DWI results
Mar 7, 2024
First DWI results
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Latest Publications

Minimum imaging dose for deep learning-based pelvic synthetic computed tomography generation from cone beam images
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Repeatability quantification of brain diffusion-weighted imaging for future clinical implementation at a low-field MR-linac
Longitudinal assessments of apparent diffusion coefficients (ADCs) derived from diffusion-weighted imaging (DWI) during intracranial …
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Auto-segmentation of pelvic organs at risk on 0.35T MRI using 2D and 3D Generative Adversarial Network models
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Our Research

Active Areas

4DCBCT Scatter Correction
Classical and AI Methods
4DCBCT Scatter Correction
Advanced CBCT Imaging
Robotic CBCT
Advanced CBCT Imaging
AI Dose Calculation
Millisecond Computation
AI Dose Calculation
CBCT Dose Reduction with AI Super-Resolution
Projection Based Methods
CBCT Dose Reduction with AI Super-Resolution
CBCT Dose Reduction with Generative AI
Image Based Methods
CBCT Dose Reduction with Generative AI
Clinical Use of AI
Automatic Segmentation
Clinical Use of AI
Dose Accumulation
Truly Delivered Dose
Dose Accumulation
Imaging biomarkers
0.35 T imaging
Imaging biomarkers
Markerless Tumor Tracking
Fluoroscopic Imaging
Markerless Tumor Tracking
Motion Modelling
3D+t Imaging
Motion Modelling
MRgRT AI-based Target Tracking
Real Time Motion Management
MRgRT AI-based Target Tracking
Outcome Modelling
Deep Learning Based
Outcome Modelling
Patient Specific Auto-Segmentation for MRgRT
Personalization and Prior Knowledge
Patient Specific Auto-Segmentation for MRgRT