116 citations · 153 across the 7 of their papers we have counts for
7 papers
COBRA2026: a large-scale multicenter pelvic cone-beam computed tomography projection dataset
Adrian Thummerer, Simon Rit, Florian Kamp +11
The COBRA2026 dataset is a large-scale, multicenter resource of raw radiotherapy cone-beam computed tomography (CBCT) acquisitions created for the development and evaluation of con…
Generating synthetic computed tomography for radiotherapy: SynthRAD2025 challenge report
Viktor Rogowski, Maarten L. Terpstra, Niklas Wahl +30
Radiation therapy (RT) requires precise dose delivery over multiple fractions, with CT fundamental for treatment planning due to its electron density information. Repeated CT acqui…
DoseRAD2026 Challenge dataset: AI accelerated photon and proton dose calculation for radiotherapy
Fan Xiao, Nikolaos Delopoulos, Niklas Wahl +13
Purpose: Accurate dose calculation is essential in radiotherapy for precise tumor irradiation while sparing healthy tissue. With the growing adoption of MRI-guided and real-time ad…
TrackRAD2025 challenge dataset: Real-time tumor tracking for MRI-guided radiotherapy
Yiling Wang, Elia Lombardo, Adrian Thummerer +25
Purpose: Magnetic resonance imaging (MRI) to visualize anatomical motion is becoming increasingly important when treating cancer patients with radiotherapy. Hybrid MRI-linear accel…
SynthRAD2025 Grand Challenge dataset: generating synthetic CTs for radiotherapy
Adrian Thummerer, Erik van der Bijl, Arthur Jr Galapon +16
Medical imaging is essential in modern radiotherapy, supporting diagnosis, treatment planning, and monitoring. Synthetic imaging, particularly synthetic computed tomography (sCT),…
Generating Synthetic Computed Tomography for Radiotherapy: SynthRAD2023 Challenge Report
Evi M. C. Huijben, Maarten L. Terpstra, Arthur Jr. Galapon +56
Radiation therapy plays a crucial role in cancer treatment, necessitating precise delivery of radiation to tumors while sparing healthy tissues over multiple days. Computed tomogra…
SynthRAD2023 Grand Challenge dataset: generating synthetic CT for radiotherapy
Adrian Thummerer, Erik van der Bijl, Arthur Jr Galapon +6
Purpose: Medical imaging has become increasingly important in diagnosing and treating oncological patients, particularly in radiotherapy. Recent advances in synthetic computed tomo…