mlsanityData to 7 Oct 2026

Multi-domain Integrative Swin Transformer network for Sparse-View Tomographic Reconstruction

arXiv 2111.14831 ↗First posted 28 Nov 2021eess.IV cs.CV cs.LGcited by 15

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Abstract (arXiv)

Decreasing projection views to lower X-ray radiation dose usually leads to severe streak artifacts. To improve image quality from sparse-view data, a Multi-domain Integrative Swin Transformer network (MIST-net) was developed in this article. First, MIST-net incorporated lavish domain features from data, residual-data, image, and residual-image using flexible network architectures, where residual-data and residual-image sub-network was considered as data consistency module to eliminate interpolation and reconstruction errors. Second, a trainable edge enhancement filter was incorporated to detect and protect image edges. Third, a high-quality reconstruction Swin transformer (i.e., Recformer) was designed to capture image global features. The experiment results on numerical and real cardiac clinical datasets with 48-views demonstrated that our proposed MIST-net provided better image quality with more small features and sharp edges than other competitors.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 23 of its 57 references that are in the map. First posted on arXiv 28 Nov 2021.

Builds on

23 of 57 references.

References · 23

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11 more
  1. 2021nnFormer: Interleaved Transformer for Volumetric Segmentationcited by 179
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 4; 2023: 5; 2024: 1; 2025: 4; 2026: 1.

15 papers.

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  1. 2022Transformers in Medical Imaging: A Surveycited by 245
  2. 2023Transformers in Healthcare: A Surveycited by 17
  3. 2024Multi-modal Deep Learningcited by 15
  4. 2022Unsupervised Contrastive Learning based Transformer for Lung Nodule Detectioncited by 11
  5. 2022Vision Transformers in Medical Imaging: A Reviewcited by 8
  6. 2023Two-and-a-half Order Score-based Model for Solving 3D Ill-posed Inverse Problemscited by 5
  7. 2023Data-iterative Optimization Score Model for Stable Ultra-Sparse-View CT Reconstructioncited by 3
  8. 2022A Deep Learning Approach Using Masked Image Modeling for Reconstruction of Undersampled K-spacescited by 1
  9. 2023SdCT-GAN: Reconstructing CT from Biplanar X-Rays with Self-driven Generative Adversarial Networkscited by 1
  10. 2025Physics-informed DeepCT: Sinogram Wavelet Decomposition Meets Masked Diffusioncited by 1
  11. 2025Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CTcited by 1
  12. 2023Topology-inspired Cross-domain Network for Developmental Cervical Stenosis Quantificationcited by 0
3 more
  1. 2025Ordered-subsets Multi-diffusion Model for Sparse-view CT Reconstructioncited by 0
  2. 2025Clinical Metadata Guided Limited-Angle CT Image Reconstructioncited by 0
  3. 2026Visible Singularities Guided Correlation Network for Limited-Angle CT Reconstructioncited by 0