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Stockholm, Sweden

ESTRO 2026

Session

Machine learning and AI algorithms (excluding any abstracts focused on application of machine learning/AI)
Digital Poster
Physics
Anatomical augmentation and automated planning for high accuracy deep learning dose prediction with few training patients.
Joep van Genderingen, The Netherlands
-517
Missing tissue generation in CT scans using a transformer-based AI model
Siyong Kim, USA
-607
Evaluation of a Pre-trained Transformer-based Foundation Model (TabPFN) for Predicting Radiotherapy Toxicity in Head and Neck Cancer
Thomas Young, United Kingdom
-1283
Robust to Bladder Filling Variations: Deep learning–based DIR auto segmentation in MR guided online adaptive radiotherapy for prostate cancer patients
Kota Abe, Japan
-1316
Interactive radiotherapy dose prediction for prostate cancer using a 3D text-guided diffusion model
YENJUNG CHEN, Taiwan, Province of China
-1808
Tool-augmented large language model for accurate radiobiological calculations in radiotherapy
Haitam Lamtai, Germany
-1872
Rectified flow-based post-treatment brain MRI generation for patients with glioma from pre-RT priors
Selena Huisman, The Netherlands
-2259
Improving treatment planning outcomes with AI tools in radiotherapy
Noemi Cucurachi, Italy
-2742
Prediction of lung cancer among the National Lung Screening Trial Program participants with Machine Learning methods
Mayur Munshi, United Kingdom
-2962
AI-based metrics of contouring consistency in breast cancer patients predict Radiotherapy outcome
Maria Giulia Ubeira Gabellini, Italy
-2983
Training foundational vision models on 152,000 CBCTs with limited computing resources
Alejandro Cortina Uribe, Denmark
-2987
Comparison of AI based techniques for toxicity prediction
Anthony Carver, United Kingdom
-3068
causal discovery of radiotherapy-induced cardiotoxicity and survival in lung cancer
Bowen Jiang, United Kingdom
-3079
Superior multi-artifact reduction using Mamba infused residual 3D-Unet for adaptive Head and Neck radiotherapy
Viktor Rogowski, Sweden
-3239
Whole Slide Image Interpretability Agent for Translational Integration in Radiotherapy
Shirin A. Enger, Canada
-3411
Fast deformable vector field generation for lung ventilation imaging using deep learning and DEEDS registration.
Marvin Kinz, USA
-3611
ML and AI based predictions in vestibular schwannoma dynamics after radiosurgery integrating morphological, anatomical, and dosimetric insights
Christina Skourou, Ireland
-3796
Efficacy of radiotherapy auto-planning on dosimetric quality: A systematic review and meta-analysis
Lin-Shan Chou, Taiwan, Province of China
-4210
AI-based synthetic CT on MRIdian enables accurate abdominal SBRT without dosimetric compromise
Daniel NGUYEN, France
-4436
Optimizing Breast Cancer Radiotherapy: AI and Tangential Index for VMAT vs HYBRID Selection
Abel Rodriguez Aranda, Spain
-4765
Reproducible cancer science utilizing the Cancer Genomics Cloud
Aditya Apte, USA
-4978