mlsanityData to 14 Oct 2026

A Unified Conditional Disentanglement Framework for Multimodal Brain MR Image Translation

arXiv 2101.05434 ↗First posted 14 Jan 2021eess.IV cs.CVcited by 19

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Abstract (arXiv)

Multimodal MRI provides complementary and clinically relevant information to probe tissue condition and to characterize various diseases. However, it is often difficult to acquire sufficiently many modalities from the same subject due to limitations in study plans, while quantitative analysis is still demanded. In this work, we propose a unified conditional disentanglement framework to synthesize any arbitrary modality from an input modality. Our framework hinges on a cycle-constrained conditional adversarial training approach, where it can extract a modality-invariant anatomical feature with a modality-agnostic encoder and generate a target modality with a conditioned decoder. We validate our framework on four MRI modalities, including T1-weighted, T1 contrast enhanced, T2-weighted, and FLAIR MRI, from the BraTS'18 database, showing superior performance on synthesis quality over the comparison methods. In addition, we report results from experiments on a tumor segmentation task carried out with synthesized data.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 14 of its 23 references that are in the map. First posted on arXiv 14 Jan 2021.

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14 of 23 references.

References · 14

  1. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  2. 2017StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translationcited by 1,039
  3. 2018Multimodal Unsupervised Image-to-Image Translationcited by 795
  4. 2016Improving Variational Inference with Inverse Autoregressive Flowcited by 640
  5. 2017Unsupervised Image-to-Image Translation Networkscited by 603
  6. 2016Conditional Image Synthesis With Auxiliary Classifier GANscited by 565
  7. 2015Autoencoding beyond pixels using a learned similarity metriccited by 407
  8. 2018MedGAN: Medical Image Translation using GANscited by 152
  9. 2018Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networkscited by 132
  10. 2016Disentangling factors of variation in deep representations using adversarial trainingcited by 87
  11. 2019Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localizationcited by 38
  12. 2020Multi-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesiscited by 12
2 more
  1. 2018SingleGAN: Image-to-Image Translation by a Single-Generator Network using Multiple Generative Adversarial Learningcited by 7
  2. 2019Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Imagescited by 7

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Citing papers per year: 2021: 2; 2022: 9; 2023: 3; 2024: 3; 2025: 2.

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  1. 2022Diffusion Models for Medical Image Analysis: A Comprehensive Surveycited by 273
  2. 2022Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectivescited by 98
  3. 2021Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentationcited by 39
  4. 2022A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completioncited by 23
  5. 2021Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesiscited by 19
  6. 2023A Deep Learning Approach for Virtual Contrast Enhancement in Contrast Enhanced Spectral Mammographycited by 12
  7. 2023Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRIcited by 11
  8. 2024Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Surveycited by 11
  9. 2022Review of Disentanglement Approaches for Medical Applications -- Towards Solving the Gordian Knot of Generative Models in Healthcarecited by 9
  10. 2022Cross-Modality Neuroimage Synthesis: A Surveycited by 7
  11. 2022Unsupervised Domain Adaptation for Segmentation with Black-box Source Modelcited by 7
  12. 2022Variational Inference for Quantifying Inter-observer Variability in Segmentation of Anatomical Structurescited by 4
7 more
  1. 2023fRegGAN with K-space Loss Regularization for Medical Image Translationcited by 3
  2. 2022Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglementcited by 2
  3. 2022Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priorscited by 1
  4. 2024Disentangled Multimodal Brain MR Image Translation via Transformer-based Modality Infusercited by 1
  5. 2025Layer Separation: Adjustable Joint Space Width Images Synthesis in Conventional Radiographycited by 1
  6. 2024Principled Feature Disentanglement for High-Fidelity Unified Brain MRI Synthesiscited by 0
  7. 2025Predicting before Reconstruction: A generative prior framework for MRI accelerationcited by 0