mlsanityData to 14 Oct 2026

Similarity and Quality Metrics for MR Image-To-Image Translation

arXiv 2405.08431 ↗First posted 14 May 2024eess.IV cs.CVcited by 20

Not on the map. Why?

Abstract (arXiv)

Image-to-image translation can create large impact in medical imaging, as images can be synthetically transformed to other modalities, sequence types, higher resolutions or lower noise levels. To ensure patient safety, these methods should be validated by human readers, which requires a considerable amount of time and costs. Quantitative metrics can effectively complement such studies and provide reproducible and objective assessment of synthetic images. If a reference is available, the similarity of MR images is frequently evaluated by SSIM and PSNR metrics, even though these metrics are not or too sensitive regarding specific distortions. When reference images to compare with are not available, non-reference quality metrics can reliably detect specific distortions, such as blurriness. To provide an overview on distortion sensitivity, we quantitatively analyze 11 similarity (reference) and 12 quality (non-reference) metrics for assessing synthetic images. We additionally include a metric on a downstream segmentation task. We investigate the sensitivity regarding 11 kinds of distortions and typical MR artifacts, and analyze the influence of different normalization methods on each metric and distortion. Finally, we derive recommendations for effective usage of the analyzed similarity and quality metrics for evaluation of image-to-image translation models.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Builds on 37 of its 117 references that are in the map. First posted on arXiv 14 May 2024.

Builds on

37 of 117 references.

References · 37

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  3. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  4. 2014Going Deeper with Convolutionscited by 4,241
  5. 2016Improved Techniques for Training GANscited by 2,970
  6. 2021Palette: Image-to-Image Diffusion Modelscited by 1,300
  7. 2020Image Quality Assessment: Unifying Structure and Texture Similaritycited by 811
  8. 2021The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classificationcited by 518
  9. 2018Generative Adversarial Network in Medical Imaging: A Reviewcited by 257
  10. 2019From Patches to Pictures (PaQ-2-PiQ): Mapping the Perceptual Space of Picture Qualitycited by 223
  11. 2022Metrics reloaded: Recommendations for image analysis validationcited by 195
  12. 2019Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathologycited by 173
25 more
  1. 2018PieAPP: Perceptual Image-Error Assessment through Pairwise Preferencecited by 160
  2. 2020MetaIQA: Deep Meta-learning for No-Reference Image Quality Assessmentcited by 144
  3. 2021Pros and Cons of GAN Evaluation Measures: New Developmentscited by 123
  4. 2018Distribution Matching Losses Can Hallucinate Features in Medical Image Translationcited by 99
  5. 2019Missing MRI Pulse Sequence Synthesis using Multi-Modal Generative Adversarial Networkcited by 98
  6. 2022Diffusion Probabilistic Models beat GANs on Medical Imagescited by 77
  7. 2023Understanding metric-related pitfalls in image analysis validationcited by 58
  8. 2022Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Networkcited by 57
  9. 2023A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyondcited by 55
  10. 2023Deep Learning Approaches for Data Augmentation in Medical Imaging: A Reviewcited by 48
  11. 2023Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesiscited by 43
  12. 2022One Model to Synthesize Them All: Multi-contrast Multi-scale Transformer for Missing Data Imputationcited by 40
  13. 2019mustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesiscited by 34
  14. 2019DermGAN: Synthetic Generation of Clinical Skin Images with Pathologycited by 33
  15. 2018Evaluating the Impact of Intensity Normalization on MR Image Synthesiscited by 26
  16. 2023The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)cited by 24
  17. 2015Geodesics of learned representationscited by 14
  18. 2022DSSIM: a structural similarity index for floating-point datacited by 10
  19. 2017Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Resultscited by 9
  20. 2021Is Image-to-Image Translation the Panacea for Multimodal Image Registration? A Comparative Studycited by 9
  21. 2020Comparison of Image Quality Models for Optimization of Image Processing Systemscited by 8
  22. 2024BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectivescited by 7
  23. 2023fRegGAN with K-space Loss Regularization for Medical Image Translationcited by 3
  24. 2023The Beauty or the Beast: Which Aspect of Synthetic Medical Images Deserves Our Focus?cited by 2
  25. 2015Multi-Region Probabilistic Dice Similarity Coefficient using the Aitchison Distance and Bipartite Graph Matchingcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 7; 2026: 11.

20 papers.

Sort:

By area:

  1. 2025Metrics that matter: Evaluating image quality metrics for medical image generationcited by 12
  2. 2024Five Pitfalls When Assessing Synthetic Medical Images with Reference Metricscited by 4
  3. 2025Hierarchical Diffusion Framework for Pseudo-Healthy Brain MRI Inpainting with Enhanced 3D Consistencycited by 2
  4. 2026Multiscale Structure-Guided Latent Diffusion for Multimodal MRI Translationcited by 2
  5. 2024ADOBI: Adaptive Diffusion Bridge For Blind Inverse Problems with Application to MRI Reconstructioncited by 1
  6. 2026Single-Subject Multi-View MRI Super-Resolution via Implicit Neural Representationscited by 1
  7. 2026Cross Modality Image Translation In Medical Imaging Using Generative Frameworkscited by 1
  8. 2025IXGS-Intraoperative 3D Reconstruction from Sparse, Arbitrarily Posed Real X-rayscited by 0
  9. 2025D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI Synthesiscited by 0
  10. 2025Locally-Supervised Global Image Restorationcited by 0
  11. 2025Generative deep learning for foundational video translation in ultrasoundcited by 0
  12. 2025HULFSynth : An INR based Super-Resolution and Ultra Low-Field MRI Synthesis via Contrast factor estimationcited by 0
8 more
  1. 2026Multi-Temporal Frames Projection for Dynamic Processes Fusion in Fluorescence Microscopycited by 0
  2. 2026Vectra: A New Metric, Dataset, and Model for Visual Quality Assessment in E-Commerce In-Image Machine Translationcited by 0
  3. 2026Optimisation of SOUP-GAN and CSR-GAN for High Resolution MR Images Reconstructioncited by 0
  4. 2026No Image, No Problem: End-to-End Multi-Task Cardiac Analysis from Undersampled k-Spacecited by 0
  5. 2026Mamba-driven MRI-to-CT Synthesis for MRI-only Radiotherapy Planningcited by 0
  6. 2026Domain-Specific Latent Representations Improve the Fidelity of Diffusion-Based Medical Image Super-Resolutioncited by 0
  7. 2026DSA-CycleGAN: A Domain Shift Aware CycleGAN for Robust Multi-Stain Glomeruli Segmentationcited by 0
  8. 2026M3-Score: Fidelity, Memorization and Coverage as Separate Axes for Evaluating Generative Radiology Image Modelscited by 0