Horvat N, Carlos Tavares Rocha C, Clemente Oliveira B, Petkovska I, Gollub MJ. MRI of rectal cancer: tumor staging, imaging techniques, and management. Radiographics. 2019 Mar;39(2):367–87.

Dayarathna S, Islam KT, Uribe S, Yang G, Hayat M, Chen Z. Deep learning based synthesis of MRI, CT and PET: Review and analysis. Medical image analysis. 2024;92:103046.

Article  Google Scholar 

Wang T, Lei Y, Fu Y, Wynne JF, Curran WJ, Liu T, Yang X. A review on medical imaging synthesis using deep learning and its clinical applications. Journal of applied clinical medical physics. 2021;22(1):11-36.

Article  PubMed  Google Scholar 

Lei Y, Harms J, Wang T, Liu Y, Shu HK, Jani AB, Curran WJ, Mao H, Liu T, Yang X. MRI‐only based synthetic CT generation using dense cycle consistent generative adversarial networks. Medical physics. 2019 ;46(8):3565-81.

Article  PubMed  PubMed Central  Google Scholar 

Fu J, Yang Y, Singhrao K, Ruan D, Chu FI, Low DA, Lewis JH. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging. Medical physics. 2019;46(9):3788-98.

Article  PubMed  Google Scholar 

Ni Y, Ma J, Chen J. Medical volume CT-to-MRI translation with multi-dimensional diffusion architecture. Biomedical Signal Processing and Control. 2026;112:108627.

Article  Google Scholar 

McNaughton J, Holdsworth S, Chong B, Fernandez J, Shim V, Wang A. Synthetic MRI generation from CT scans for stroke patients. BioMedInformatics. 2023 Sep 11;3(3):791-816.

Article  Google Scholar 

Li W, Li Y, Qin W, Liang X, Xu J, Xiong J, Xie Y. Magnetic resonance image (MRI) synthesis from brain computed tomography (CT) images based on deep learning methods for magnetic resonance (MR)-guided radiotherapy. Quantitative imaging in medicine and surgery. 2020;10(6):1223.

Article  PubMed  PubMed Central  Google Scholar 

Kalantar R, Messiou C, Winfield JM, Renn A, Latifoltojar A, Downey K, Sohaib A, Lalondrelle S, Koh DM, Blackledge MD. CT-based pelvic T1-weighted MR image synthesis using UNet, UNet++ and cycle-consistent generative adversarial network (Cycle-GAN). Frontiers in oncology. 2021;11:665807.

Article  Google Scholar 

Xia YF, Zeng M, Sun SW, Liu QP, Zhang JL, Zhi R, Lu FY, Chen W, Zhang YD. Region‐guided focal adversarial learning for CT‐to‐MRI translation: A proof‐of‐concept and validation study in hepatocellular carcinoma. Medical Physics. 2025;52(5):2861-73.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen Z, Gao Q, Zhang Y, Shan H. ASCON: Anatomy-aware supervised contrastive learning framework for low-dose CT denoising. InInternational Conference on Medical Image Computing and Computer-Assisted Intervention 2023 Oct 1 (pp. 355–365). Cham: Springer Nature Switzerland.

Dalmaz O, Yurt M, Çukur T. ResViT: Residual vision transformers for multimodal medical image synthesis. IEEE Transactions on Medical Imaging. 2022;41(10):2598-614.

Article  PubMed  Google Scholar 

Ghasemabadi A, Janjua MK, Salameh M, Zhou C, Sun F, Niu D. Cascadedgaze: Efficiency in global context extraction for image restoration. arXiv preprint arXiv:2401.15235. 2024 Jan 26.

Thummerer A, Van der Bijl E, Galapon Jr A, Verhoeff JJ, Langendijk JA, Both S, van den Berg CN, Maspero M. SynthRAD2023 Grand Challenge dataset: Generating synthetic CT for radiotherapy. Medical physics. 2023 ;50(7):4664-74.

Article  PubMed  Google Scholar 

https://clinicaltrials.gov/ct2/show/NCT05716633

Nyholm T, Svensson S, Andersson S, Jonsson J, Sohlin M, Gustafsson C, Kjellén E, Söderström K, Albertsson P, Blomqvist L, Zackrisson B. MR and CT data with multiobserver delineations of organs in the pelvic area—Part of the Gold Atlas project. Medical physics. 2018;45(3):1295-300.

Article  PubMed  Google Scholar 

D'Antonoli TA, Berger LK, Indrakanti AK, Vishwanathan N, Weiß J, Jung M, Berkarda Z, Rau A, Reisert M, Küstner T, Walter A. TotalSegmentator MRI: Robust sequence-independent segmentation of multiple anatomic structures in MRI. arXiv preprint arXiv:2405.19492. 2024 May 29.