mlsanityData to 7 Oct 2026

Deep learning-based synthetic-CT generation in radiotherapy and PET: a review

arXiv 2102.02734 ↗First posted 4 Feb 2021physics.med-ph cs.LG eess.IVcited by 28

Not on the map. Why?

Abstract (arXiv)

Recently, deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping them into three categories, according to their clinical applications: I) To replace CT in magnetic resonance (MR)-based treatment planning. II) Facilitate cone-beam computed tomography (CBCT)-based image-guided adaptive radiotherapy. III) Derive attenuation maps for the correction of positron emission tomography (PET). Appropriate database searching was performed on journal articles published between January 2014 and December 2020. The DL methods' key characteristics were extracted from each eligible study, and a comprehensive comparison among network architectures and metrics was reported. A detailed review of each category was given, highlighting essential contributions, identifying specific challenges, and summarising the achievements. Lastly, the statistics of all the cited works from various aspects were analysed, revealing the popularity and future trends, and the potential of DL-based sCT generation. The current status of DL-based sCT generation was evaluated, assessing the clinical readiness of the presented methods.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 23 of its 221 references that are in the map. First posted on arXiv 4 Feb 2021.

Builds on

23 of 221 references.

References · 23

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  4. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  5. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
  6. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,420
  7. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,182
  8. 2020A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challengescited by 813
  9. 2017Generative Adversarial Networks: An Overviewcited by 588
  10. 2018Attention Gated Networks: Learning to Leverage Salient Regions in Medical Imagescited by 271
  11. 2018Generative Adversarial Network in Medical Imaging: A Reviewcited by 257
  12. 2018Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysiscited by 178
11 more
  1. 2017Deep MR to CT Synthesis using Unpaired Datacited by 86
  2. 2015Loss Functions for Neural Networks for Image Processingcited by 41
  3. 2018Deep CT to MR Synthesis using Paired and Unpaired Datacited by 31
  4. 2019Overfitting of neural nets under class imbalance: Analysis and improvements for segmentationcited by 27
  5. 2018Evaluating the Impact of Intensity Normalization on MR Image Synthesiscited by 26
  6. 2019Learning with Known Operators reduces Maximum Training Error Boundscited by 25
  7. 2017Deep Embedding Convolutional Neural Network for Synthesizing CT Image from T1-Weighted MR Imagecited by 9
  8. 2019Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasetscited by 9
  9. 2018Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planningcited by 8
  10. 2017Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR imagescited by 3
  11. 2019Generation of abdominal synthetic CTs from 0.35T MR images using generative adversarial networks for MR-only liver radiotherapycited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 3; 2023: 3; 2024: 5; 2025: 7; 2026: 9.

28 papers.

Sort:

By area:

  1. 2023SynthRAD2023 Grand Challenge dataset: generating synthetic CT for radiotherapycited by 53
  2. 2025SynthRAD2025 Grand Challenge dataset: generating synthetic CTs for radiotherapycited by 27
  3. 2024Chest-Diffusion: A Light-Weight Text-to-Image Model for Report-to-CXR Generationcited by 16
  4. 2024FedSynthCT-Brain: A Federated Learning Framework for Multi-Institutional Brain MRI-to-CT Synthesiscited by 6
  5. 2022Deformation equivariant cross-modality image synthesis with paired non-aligned training datacited by 5
  6. 2024Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning -- A Reviewcited by 5
  7. 2025Why Registration Quality Matters: Enhancing sCT Synthesis with IMPACT-Based Registrationcited by 4
  8. 2025Conditional Diffusion Models for CT Image Synthesis from CBCT: A Systematic Reviewcited by 3
  9. 2023Exploring contrast generalisation in deep learning-based brain MRI-to-CT synthesiscited by 2
  10. 2023Generalizable synthetic MRI with physics-informed convolutional networkscited by 2
  11. 2024Deformation-aware GAN for Medical Image Synthesis with Substantially Misaligned Pairscited by 2
  12. 2024HC3L-Diff: Hybrid conditional latent diffusion with high frequency enhancement for CBCT-to-CT synthesiscited by 2
16 more
  1. 2026DoseRAD2026 Challenge dataset: AI accelerated photon and proton dose calculation for radiotherapycited by 2
  2. 2021Training of deep cross-modality conversion models with a small dataset, and their application in megavoltage CT to kilovoltage CT conversioncited by 1
  3. 2022Region of Interest focused MRI to Synthetic CT Translation using Regression and Classification Multi-task Networkcited by 1
  4. 2025A Privacy-Preserving Federated Learning Framework for Generalizable CBCT to Synthetic CT Translation in Head and Neckcited by 1
  5. 2026Rectified flow-based prediction of post-treatment brain MRI from pre-radiotherapy priors for patients with gliomacited by 1
  6. 2026Cross Modality Image Translation In Medical Imaging Using Generative Frameworkscited by 1
  7. 2022Structure Unbiased Adversarial Model for Medical Image Segmentationcited by 0
  8. 2025AI-Assisted Decision-Making for Clinical Assessment of Auto-Segmented Contour Qualitycited by 0
  9. 2025DINOv3-Guided Cross Fusion Framework for Semantic-aware CT generation from MRI and CBCTcited by 0
  10. 2025Energy-Efficient Federated Learning via Adaptive Encoder Freezing for MRI-to-CT Conversion: A Green AI-Guided Researchcited by 0
  11. 2026RAFM: Retrieval-Augmented Flow Matching for Unpaired CBCT-to-CT Translationcited by 0
  12. 2026VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translationcited by 0
  13. 2026EPC-3D-Diff: Equivariant Physics Consistent Conditional 3D Latent Diffusion for CBCT to CT Synthesiscited by 0
  14. 2026WING: A Window-Prior-Based Generative Network with Gated Inception for Cross-Modality CT Synthesiscited by 0
  15. 2026Anatomical and Physical Supervision for CT-less PET Attenuation Correction: BIC-MAC 2026 Challengecited by 0
  16. 2026TotalSynth: Robust Whole-Body Synthetic CT from MRI and CBCTcited by 0