We provide a list of awesome papers in medical multimodel brain image systhesis.
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- Deep learning of brain magnetic resonance images: A brief review [Methods, 2021]
- Generative adversarial network in medical imaging: A review [MedIA, 2019]
Supervised
- ABCnet: Adversarial bias correction network for infant brain MR images [MedIA, 2021]
- Contrast-Enhanced Brain MRI Synthesis With Deep Learning: Key Input Modalities and Asymptotic Performance [ISBI, 2021]
- Hi-Net: Hybrid-Fusion Network for Multi-Modal MR Image Synthesis [TMI, 2020]
- A Unified Conditional Disentanglement Framework For Multimodal Brain Mr Image Translation [ISBI, 2021]
- mustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesis [MedIA, 2021]
- DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images [JBHI, 2021]
- MCMT-GAN: Multi-Task Coherent Modality Transferable GAN for 3D Brain Image Synthesis [TIP, 2020]
- Missing MRI Pulse Sequence Synthesis Using Multi-Modal Generative Adversarial Network [TMI, 2020]
- Multi-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesis [ISBI, 2020]
- Sample-Adaptive GANs: Linking Global and Local Mappings for Cross-Modality MR Image Synthesis [TMI, 2020]
- CoCa-GAN: Common-Feature-Learning-Based Context-Aware Generative Adversarial Network for Glioma Grading [MICCAI, 2019]
- Image Synthesis in Multi-Contrast MRI With Conditional Generative Adversarial Networks [TMI, 2019]
- Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks [MICCAI, 2019]
- CollaGAN: Collaborative GAN for Missing Image Data Imputation [CVPR, 2019]
- DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis [MICCAI, 2019]
- Multimodal MR Synthesis via Modality-Invariant Latent Representation [TMI, 2018]
- 3D cGAN based cross-modality MR image synthesis for brain tumor segmentation [ISBI, 2018]
- DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI [MICCAI,2017]
- Random forest regression for magnetic resonance image synthesis [MedIA, 2017]
- Robust Multi-modal MR Image Synthesis [MICCAI, 2017]
Weakly-supervised
- Multi-Domain Image Completion for Random Missing Input Data [TMI, 2021]
- Simultaneous Super-Resolution and Cross-Modality Synthesis in Magnetic Resonance Imaging [ACVPR, 2019]
- Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning [TMI, 2018]
Unsupervised
- Autoencoder based self-supervised test-time adaptation for medical image analysis [MedIA, 2021]
- A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation [MICCAI, 2021]
- Anatomic and Molecular MR Image Synthesis Using Confidence Guided CNNs [TMI, 2021]
- Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation [TMI, 2021]
- MRI cross-modality image-to-image translation [Nature, Scientific Reports, 2021]
- Super-Resolution and Inpainting with Degraded and Upgraded Generative Adversarial Networks [IJCAI, 2020]
- An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection [JBHI, 2020]
- Multimodal brain MRI translation focused on lesions [ICMLC, 2020]
- Mri image-to-image translation for cross-modality image registration and segmentation [arXiv, 2018]
- DDA-Net: Unsupervised cross-modality medical image segmentation via dual domain adaptation [CMPB, 2013]
Supervised
- DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images [JBHI, 2021]
- Estimating CT image from MRI data using structured random forest and auto-context model [TMI, 2015]
Weakly-supervised
- Deep Generative Model for Synthetic-CT Generation with Uncertainty Predictions [MICCAI, 2020]
Unsupervised
- Imitation learning for improved 3D PET/MR attenuation correction [MedIA, 2022]
- Unsupervised MR-to-CT Synthesis Using Structure-Constrained CycleGAN [TMI, 2020]
- SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth [TMI, 2019]
- Hybrid Generative Adversarial Networks for Deep MR to CT Synthesis Using Unpaired Data [MICCAI, 2019]
- Medical Image Synthesis with Context-Aware Generative Adversarial Networks [MICCAI, 2017]
Supervised
- Bidirectional Mapping Generative Adversarial Networks for Brain MR to PET Synthesis [TMI, 2022]
- Assessing clinical progression from subjective cognitive decline to mild cognitive impairment with incomplete multi-modal neuroimages [MedIA, 2022]
- BPGAN: Brain PET synthesis from MRI using generative adversarial network for multi-modal Alzheimer’s disease diagnosis [CMPB, 2022]
- Disease-image-specific Learning for Diagnosis-oriented Neuroimage Synthesis with Incomplete Multi-Modality Data. [TPAMI, 2021]
- DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images [JBHI, 2021]
- Brain MR to PET Synthesis via Bidirectional Generative Adversarial Network [MICCAI, 2020 ]
- GANDALF: Generative Adversarial Networks with Discriminator-Adaptive Loss Fine-tuning for Alzheimer's Disease Diagnosis from MRI [MICCAI, 2020]
- Disease-Image Specific Generative Adversarial Network for Brain Disease Diagnosis with Incomplete Multi-modal Neuroimages [MICCAI, 2019]
- Locality Adaptive Multi-modality GANs for High-Quality PET Image Synthesis [MICCAI, 2018]
- Synthesizing Missing PET from MRI with Cycle-consistent Generative Adversarial Networks for Alzheimer's Disease Diagnosis [MICCAI, 2018]
- Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training [MICCAI, 2018]
Unsupervised
- Demystifying T1-MRI to FDG18 -PET Image Translation via Representational Similarity [MICCAI, 2021]
Supervised
- Imitation learning for improved 3D PET/MR attenuation correction [MedIA, 2021]
Unsupervised
- Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis [TMI, 2020]
Supervised
- Synthesizing Multi-Tracer PET Images for Alzheimer's Disease Patients using a 3D Unified Anatomy-aware Cyclic Adversarial Network [MICCAI, 2021]
- 3D Auto-Context-Based Locality Adaptive Multi-Modality GANs for PET Synthesis [TMI, 2019]
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Deep Generative Models in the Real-World: An Open Challenge from Medical Imaging [arXiv, 2018]
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Learning to synthesise the ageing brain without longitudinal data [MedIA, 2021]
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SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation [MICCAI, 2021]
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TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation [MICCAI, 2021]
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Spatial-Intensity Transform GANs for High Fidelity Medical Image-to-Image Translation [MICCAI, 2020]
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Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression [MICCAI, 2019]
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Generative Adversarial Network for Segmentation of Motion Affected Neonatal Brain MRI [MICCAI, 2019]
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Anatomy-Constrained Contrastive Learning for Synthetic Segmentation without Ground-truth [MICCAI, 2021]
