ArticleProceedings of SPIE--the International Society for Optical Engineering
Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglement.
Article in Proceedings of SPIE--the International Society for Optical Engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The trial behind it
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Who cites it
4 citing papers in PubMed.
- Scan-wise generalized PET denoising with contrastive adversarial learning.Physics in medicine and biology · 2026Article
- Tagged-to-Cine MRI Sequence Synthesis via Light Spatial-Temporal Transformer.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2024Article
- Tagged-MRI Sequence to Audio Synthesis via Self Residual Attention Guided Heterogeneous Translator.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2022Article
- Brain MR Atlas Construction Using Symmetric Deep Neural Inpainting.IEEE journal of biomedical and health informatics · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Cycle reconstruction regularized adversarial training-e.g., CycleGAN, DiscoGAN, and DualGAN-has been widely used for image style transfer with unpaired training data. Several recent works, however, have shown that local distortions are frequent, and structural consistency cannot be guaranteed. Targeting this issue, prior works usually relied on additional segmentation or consistent feature extraction steps that are task-specific. To counter this, this work aims to learn a general add-on structural feature extractor, by explicitly enforcing the structural alignment between an input and its synthesized image. Specifically, we propose a novel input-output image patches self-training scheme to achieve a disentanglement of underlying anatomical structures and imaging modalities. The translator and structure encoder are updated, following an alternating training protocol. In addition, the information w.r.t. imaging modality can be eliminated with an asymmetric adversarial game. We train, validate, and test our network on 1,768, 416, and 1,560 unpaired subject-independent slices of tagged and cine magnetic resonance imaging from a total of twenty healthy subjects, respectively, demonstrating superior performance over competing methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.