Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report.
Evi M. C. HuijbenMaarten L. TerpstraArthur Jr GalaponSuraj PaiAdrian ThummererPeter KoopmansManya AfonsoMaureen A. J. M. van EijnattenOliver J. Gurney-ChampionZeli ChenYiwen ZhangKaiyi ZhengChuanpu LiHaowen PangChuyang YeRunqi WangTao SongFuxin FanJingna QiuYixing HuangJuhyung HaJong Sung ParkAlexandra Alain-BeaudoinSilvain BériaultPengxin YuHongbin GuoZhanyao HuangGengwan LiXueru ZhangYubo FanHan LiuBowen XinAaron NicolsonLujia ZhongZhiwei DengGustav Müller-FranzesFiras KhaderXia LiYe ZhangCédric HémonValentin BoussotZhihao ZhangLong WangLu BaiShaobin WangDerk MusBram KooimanChelsea A. H. SargeantEdward G. A. HendersonSatoshi KondoSatoshi KasaiReza KarimzadehBulat IbragimovThomas HelferJessica DafflonZijie ChenEnpei WangZoltán PerkóMatteo MasperoPublished in: Medical Image Anal. (2024)
Keyphrases
- computed tomography
- ct images
- treatment planning
- medical imaging
- medical images
- image reconstruction
- ct scans
- lung cancer patients
- three dimensional
- image guided
- lung cancer
- ct data
- computed tomography scans
- radiation therapy
- low dose
- anatomical structures
- x ray
- cone beam ct
- pet ct
- medical image analysis
- magnetic resonance images
- cone beam
- region of interest
- remote sensing
- imaging modalities
- radon transform
- lymph nodes
- prostate cancer
- machine learning
- blood vessels
- magnetic resonance
- image analysis
- computational complexity
- image processing