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000302854 041__ $$aEnglish
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000302854 1001_ $$aThummerer, Adrian$$b0
000302854 245__ $$aSynthRAD2025 Grand Challenge dataset: Generating synthetic CTs for radiotherapy from head to abdomen.
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000302854 520__ $$aMedical imaging is crucial in modern radiotherapy, aiding diagnosis, treatment planning, and monitoring. The development of synthetic imaging techniques, particularly synthetic computed tomography (sCT), continues to attract interest in radiotherapy. The SynthRAD2025 dataset and the accompanying SynthRAD2025 Grand Challenge aim to stimulate advancements in synthetic CT generation algorithms by providing a platform for comprehensive evaluation and benchmarking of synthetic CT generation algorithms based on cone-beam CTs (CBCT) and magnetic resonance images (MRI).The dataset comprises 2362 cases, including 890 MRI-CT pairs and 1472 CBCT-CT pairs of head-and-neck, thoracic, and abdominal cancer patients treated at five European university medical centers [UMC Groningen, UMC Utrecht, Radboud UMC (Netherlands), LMU University Hospital Munich, and University Hospital of Cologne (Germany)]. Images were acquired using a wide range of acquisition protocols and scanners. Pre-processing, including rigid and deformable image registration methods, was performed to ensure high-quality image datasets and alignment between modalities. Extensive quality assurance was performed to validate image consistency and usability.All imaging data is provided using the MetaImage (.mha) file format, ensuring compatibility with common medical image processing tools. Metadata, including acquisition parameters and registration details, is available in structured comma-separated value (CSV) files. To ensure dataset integrity, SynthRAD2025 is split into training (65%), validation (10%), and test (25%) sets. The dataset is accessible through https://doi.org/10.5281/zenodo.14918088 under the SynthRAD2025 collection.This dataset enables benchmarking and development of synthetic imaging techniques for radiotherapy applications. Potential use cases include sCT generation for MRI-only and MR-guided photon and proton radiotherapy, CBCT-based dose calculations, and adaptive radiotherapy workflows. By incorporating data from diverse acquisition settings, SynthRAD2025 supports the advancement of robust and generalizable image synthesis algorithms for clinical implementation, ultimately promoting personalized cancer care and improving adaptive radiotherapy workflows.
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000302854 650_7 $$2Other$$aCBCT
000302854 650_7 $$2Other$$aCT
000302854 650_7 $$2Other$$aMR
000302854 650_7 $$2Other$$aartificial intelligence
000302854 650_7 $$2Other$$adeep learning
000302854 650_7 $$2Other$$aimage synthesis
000302854 650_2 $$2MeSH$$aHumans
000302854 650_2 $$2MeSH$$aImage Processing, Computer-Assisted
000302854 650_2 $$2MeSH$$aMagnetic Resonance Imaging
000302854 650_2 $$2MeSH$$aAbdomen: diagnostic imaging
000302854 650_2 $$2MeSH$$aAbdomen: radiation effects
000302854 650_2 $$2MeSH$$aHead: diagnostic imaging
000302854 650_2 $$2MeSH$$aCone-Beam Computed Tomography
000302854 650_2 $$2MeSH$$aRadiotherapy, Image-Guided
000302854 650_2 $$2MeSH$$aHead and Neck Neoplasms: radiotherapy
000302854 650_2 $$2MeSH$$aHead and Neck Neoplasms: diagnostic imaging
000302854 650_2 $$2MeSH$$aTomography, X-Ray Computed
000302854 7001_ $$avan der Bijl, Erik$$b1
000302854 7001_ $$aGalapon, Arthur Jr$$b2
000302854 7001_ $$aKamp, Florian$$b3
000302854 7001_ $$aSavenije, Mark$$b4
000302854 7001_ $$aMuijs, Christina$$b5
000302854 7001_ $$aAluwini, Shafak$$b6
000302854 7001_ $$aSteenbakkers, Roel J H M$$b7
000302854 7001_ $$aBeuel, Stephanie$$b8
000302854 7001_ $$aIntven, Martijn Pw$$b9
000302854 7001_ $$aLangendijk, Johannes A$$b10
000302854 7001_ $$aBoth, Stefan$$b11
000302854 7001_ $$aCorradini, Stefanie$$b12
000302854 7001_ $$aRogowski, Viktor$$b13
000302854 7001_ $$aTerpstra, Maarten$$b14
000302854 7001_ $$0P:(DE-He78)dfd5aaf608015baaaed0a15b473f1336$$aWahl, Niklas$$b15$$udkfz
000302854 7001_ $$aKurz, Christopher$$b16
000302854 7001_ $$0P:(DE-HGF)0$$aLandry, Guillaume$$b17
000302854 7001_ $$aMaspero, Matteo$$b18
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