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Stockholm, Sweden

ESTRO 2026

Session

Image acquisition and processing
Digital Poster
Physics
Radiotherapy CT simulation. HU-to-relativeElectronDensity calibration curves. A validation study
Periklis Papavasileiou, Greece
-100
Study on the Motion Characteristics of Transposed Ovaries Using the Fan-beam CT of the United Imaging uRT-linac 506c Linear Accelerator
Xiaolong Cheng, China
-553
MR-visible composite material for radiation oncology applications
Astrid Hafner, Austria
-1008
How to fix a synthetic CT: a Deep Learning model to predict the voxel-wise conversion error
Lorena Romeo, Italy
-1037
Metal artefact reduction for spinal implants: A quantitative comparison of Photon-Counting and Energy-Integrating CT
Tin Lok Chiu, China, Hong Kong Special Administrative Region
-1069
Evaluating the Generalisability of a Deep Learning Synthetic CT Model for Prostate MR-only Radiotherapy
Teresa Guerrero Urbano, United Kingdom
-1093
Repeatability of quantitative MRI sequences on a 1.5T MR-Linac
Anaïs Barateau, France
-1152
Image quality assessment of photon-counting and dual energy CT for prostate radiotherapy planning
Mathias Teller, Denmark
-1230
Optimizing Material Decomposition and Dose Efficiency in Dual-Energy X-ray Imaging on a Flat-Panel Detector
Nawal Alqethami, Germany
-1371
Widening applicability of MR-only radiotherapy: MR-based synthetic CT generation for patients with hip implants using deep learning methods
Mariia Lapaeva, Switzerland
-1554
Proof-of-concept cone-beam Ion Computed Tomography (ion-CT) imaging system with a single scintillator-CMOS detector
Tianyuan Wang, Japan
-1699
Feasibility Study of an MR-Only Workflow for CyberKnife Stereotactic Radiosurgery in Brain Metastases
Xue Bai, China
-1800
AI based MRI reconstruction in Radiotherapy: Improving Efficiency Without Compromising Quality
Bashar Al-Qaisieh, United Kingdom
-2744
Feasibility of Deep Learning-Based Synthetic CT Generation for MRI-Only Brain Radiotherapy Planning
Sharad Singh, India
-3081
Feasibility of liquid fiducial markers for target localization in abdominal SBRT: a kick-off study
Denis Panizza, Italy
-3083
Evaluating Image Quality of Cone-Beam CT Using Hypersight® on the Varian TrueBeam: A Quantitative and Subjective Study
Jesse Lohela, Finland
-3304
Quantitative and Clinical Evaluation of HyperSight CBCT
Nicolle Gomes, Portugal
-3347
Metal artifact reduction for 3T MRI-only prostate radiotherapy with hip prostheses: target definition, synthetic CT and fiducial marker identification
Mizgin Coskun, Sweden
-3763
Assessment of CT number accuracy in Single-Energy versus spectral CT imaging: a phantom study
Gary Razinskas, Germany
-3810
Generalizability of deep learning networks for synthetic CT generation from limited FOV CBCT of the pelvic region in Carbon Ion Radiotherapy
MAKSYM HLADCHUK, Italy
-3902
Impact of SGRT optimization on IGRT rotational corrections in lung radiotherapy
Carmelo Marino, Italy
-4043
Evaluation of Direct Density kernel conversion for mass-density mapping
Tamás Pócza, Hungary
-4090
Geometric evaluation of deformable image registration for paediatric head and neck reirradiation
Ellie Glaister, United Kingdom
-4333
Quantitative and qualitative evaluation of HyperSight cone-beam CT imaging for contouring in lung cancer patients
Nadine Coorens, The Netherlands
-4414
Evaluation of geometric integrity around hip arthroplasty in prostate cancer radiotherapy simulation using a 0.55T MR Scanner
Bertrand Pouymayou, Switzerland
-4470
Extended Field of View (eFoV) Image Quality Analysis for Proton Therapy Using Philips Spectral CT7500 scanner
Ka Wing Savanna Chung, United Kingdom
-4787
Motion Correction in 4D CBCT Projections for Enhanced Reconstruction
Johannes Bastian Gebauer, Germany
-4917
ACCURACY AND PRECISION OF THE 5DCT APPROACH
Daniel Low, USA
-4924
Improved Abdominal Gas Cavity Definition in Synthetic CT for MRI-Only Simulation Imaging with MRI-Guided Gastrointestinal Radiotherapy
Marvin Kinz, USA
-5039
Verification of metal artifact reduction effectiveness in Varian HyperSight system
Bartosz Pawalowski, Poland
-5110
A Novel Sim2Real Deep Learning Approach for Scatter Correction in Cone-Beam CT
Camille Draguet, Canada
-5155
Predict the three-dimensional spatial contour of  target volume based on the body surface movement characteristics of patients with thoracic tumors
Yinglin Peng, China
-5215