mlsanityData to 7 Oct 2026

Exploring the Power of Generative Deep Learning for Image-to-Image Translation and MRI Reconstruction: A Cross-Domain Review

arXiv 2303.09012 ↗First posted 16 Mar 2023eess.IV cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Deep learning has become a prominent computational modeling tool in the areas of computer vision and image processing in recent years. This research comprehensively analyzes the different deep-learning methods used for image-to-image translation and reconstruction in the natural and medical imaging domains. We examine the famous deep learning frameworks, such as convolutional neural networks and generative adversarial networks, and their variants, delving into the fundamental principles and difficulties of each. In the field of natural computer vision, we investigate the development and extension of various deep-learning generative models. In comparison, we investigate the possible applications of deep learning to generative medical imaging problems, including medical image translation, MRI reconstruction, and multi-contrast MRI synthesis. This thorough review provides scholars and practitioners in the areas of generative computer vision and medical imaging with useful insights for summarizing past works and getting insight into future research paths.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 68 of its 112 references that are in the map. First posted on arXiv 16 Mar 2023.

Builds on

68 of 112 references.

References · 68

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  5. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  6. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  7. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  8. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  9. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  10. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  11. 2022Generative Adversarial Networkscited by 5,603
  12. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,845
38 more
  1. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  2. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  3. 2014Deep Learning Face Attributes in the Wildcited by 3,679
  4. 2014Conditional Generative Adversarial Netscited by 2,152
  5. 2016Context Encoders: Feature Learning by Inpaintingcited by 1,424
  6. 2019Semantic Image Synthesis with Spatially-Adaptive Normalizationcited by 1,295
  7. 2016Instance Normalization: The Missing Ingredient for Fast Stylizationcited by 1,187
  8. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  9. 2016Colorful Image Colorizationcited by 1,113
  10. 2019StarGAN v2: Diverse Image Synthesis for Multiple Domainscited by 1,095
  11. 2017StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translationcited by 1,036
  12. 2018Self-Attention Generative Adversarial Networkscited by 809
  13. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  14. 2017Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkscited by 707
  15. 2020Contrastive Learning for Unpaired Image-to-Image Translationcited by 637
  16. 2017Unsupervised Image-to-Image Translation Networkscited by 602
  17. 2018fastMRI: An Open Dataset and Benchmarks for Accelerated MRIcited by 464
  18. 2017DualGAN: Unsupervised Dual Learning for Image-to-Image Translationcited by 310
  19. 2017Learning to Discover Cross-Domain Relations with Generative Adversarial Networkscited by 278
  20. 2019DRIT++: Diverse Image-to-Image Translation via Disentangled Representationscited by 244
  21. 2019U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translationcited by 186
  22. 2017Deep Photo Style Transfercited by 168
  23. 2018MedGAN: Medical Image Translation using GANscited by 152
  24. 2018Unsupervised Image Super-Resolution using Cycle-in-Cycle Generative Adversarial Networkscited by 133
  25. 2021UNIT-DDPM: UNpaired Image Translation with Denoising Diffusion Probabilistic Modelscited by 133
  26. 2018Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networkscited by 131
  27. 2017Real-Time User-Guided Image Colorization with Learned Deep Priorscited by 123
  28. 2021ViTGAN: Training GANs with Vision Transformerscited by 110
  29. 2019Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translationcited by 97
  30. 2017Deep learning for undersampled MRI reconstructioncited by 91
  31. 2017Deep MR to CT Synthesis using Unpaired Datacited by 86
  32. 2017Compressed Sensing MRI Reconstruction using a Generative Adversarial Network with a Cyclic Losscited by 82
  33. 2018Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Datacited by 76
  34. 2017A Deep Cascade of Convolutional Neural Networks for MR Image Reconstructioncited by 74
  35. 2022Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstructioncited by 64
  36. 2019Unsupervised Medical Image Translation Using Cycle-MedGANcited by 44
  37. 2019SPA-GAN: Spatial Attention GAN for Image-to-Image Translationcited by 43
  38. 2018Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data sizecited by 42

50 most cited of 68 All 68 (JSON)

Built on by

Not cited yet.