mlsanityData to 14 Oct 2026

A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

arXiv 2111.13300 ↗First posted 26 Nov 2021eess.IV cs.CVcited by 41

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Abstract (arXiv)

We propose a Transformer architecture for volumetric segmentation, a challenging task that requires keeping a complex balance in encoding local and global spatial cues, and preserving information along all axes of the volume. Encoder of the proposed design benefits from self-attention mechanism to simultaneously encode local and global cues, while the decoder employs a parallel self and cross attention formulation to capture fine details for boundary refinement. Empirically, we show that the proposed design choices result in a computationally efficient model, with competitive and promising results on the Medical Segmentation Decathlon (MSD) brain tumor segmentation (BraTS) Task. We further show that the representations learned by our model are robust against data corruptions. hrefhttps://github.com/himashi92/VT-UNetOur code implementation is publicly available.

Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). Builds on 24 of its 30 references that are in the map. First posted on arXiv 26 Nov 2021.

Builds on

24 of 30 references.

References · 24

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  5. 2020End-to-End Object Detection with Transformerscited by 7,414
  6. 2020Training data-efficient image transformers & distillation through attentioncited by 4,586
  7. 2016DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFscited by 3,241
  8. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,292
  9. 2021ViViT: A Video Vision Transformercited by 1,620
  10. 2021TransUNet: Transformers Make Strong Encoders for Medical Image Segmentationcited by 1,558
  11. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,525
  12. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
12 more
  1. 2020Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformerscited by 1,369
  2. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,222
  3. 2021Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetcited by 1,101
  4. 2021Video Swin Transformercited by 1,091
  5. 2021Transformers in Vision: A Surveycited by 1,013
  6. 2021UNETR: Transformers for 3D Medical Image Segmentationcited by 959
  7. 2021The Medical Segmentation Decathloncited by 628
  8. 2021Intriguing Properties of Vision Transformerscited by 446
  9. 2021TransBTS: Multimodal Brain Tumor Segmentation Using Transformercited by 265
  10. 2021CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentationcited by 227
  11. 2019Local Relation Networks for Image Recognitioncited by 210
  12. 2020nnU-Net for Brain Tumor Segmentationcited by 103

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 6; 2023: 12; 2024: 12; 2025: 9; 2026: 2.

41 papers.

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  1. 2023MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentationcited by 162
  2. 2023SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentationcited by 35
  3. 2022Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectivescited by 33
  4. 2022CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentationcited by 24
  5. 2025Primus: Enforcing Attention Usage for 3D Medical Image Segmentationcited by 24
  6. 2023A Recent Survey of Vision Transformers for Medical Image Segmentationcited by 23
  7. 20233D TransUNet: Advancing Medical Image Segmentation through Vision Transformerscited by 20
  8. 2022A survey on attention mechanisms for medical applications: are we moving towards better algorithms?cited by 15
  9. 2024EM-Net: Efficient Channel and Frequency Learning with Mamba for 3D Medical Image Segmentationcited by 12
  10. 2022Recent Progress in Transformer-based Medical Image Analysiscited by 9
  11. 2024D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentationcited by 9
  12. 2025Rethinking Brain Tumor Segmentation from the Frequency Domain Perspectivecited by 9
29 more
  1. 2023CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentationcited by 7
  2. 2022Multi-branch Cascaded Swin Transformers with Attention to k-space Sampling Pattern for Accelerated MRI Reconstructioncited by 4
  3. 2023Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensemblescited by 4
  4. 2022PIP: Positional-encoding Image Priorcited by 3
  5. 2023Boosting Convolution with Efficient MLP-Permutation for Volumetric Medical Image Segmentationcited by 3
  6. 2023RadarFormer: Lightweight and Accurate Real-Time Radar Object Detection Modelcited by 3
  7. 2023Med-Tuning: A New Parameter-Efficient Tuning Framework for Medical Volumetric Segmentationcited by 3
  8. 2025Concentrate on Weakness: Mining Hard Prototypes for Few-Shot Medical Image Segmentationcited by 3
  9. 2023Transformer-based end-to-end classification of variable-length volumetric datacited by 2
  10. 2023Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentationcited by 2
  11. 2024Architecture Analysis and Benchmarking of 3D U-shaped Deep Learning Models for Thoracic Anatomical Segmentationcited by 2
  12. 2024DocParseNet: Advanced Semantic Segmentation and OCR Embeddings for Efficient Scanned Document Annotationcited by 2
  13. 2024Cross-Slice Attention and Evidential Critical Loss for Uncertainty-Aware Prostate Cancer Detectioncited by 2
  14. 2024Spectral U-Net: Enhancing Medical Image Segmentation via Spectral Decompositioncited by 2
  15. 2025GBT-SAM: A Parameter-Efficient Depth-Aware Model for Generalizable Brain tumour Segmentation on mp-MRIcited by 2
  16. 2024UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor Segmentationcited by 1
  17. 2025QMaxViT-Unet+: A Query-Based MaxViT-Unet with Edge Enhancement for Scribble-Supervised Segmentation of Medical Imagescited by 1
  18. 2025Trans2-CBCT: A Dual-Transformer Framework for Sparse-View CBCT Reconstructioncited by 1
  19. 2023CATS v2: Hybrid encoders for robust medical segmentationcited by 0
  20. 2024Modality-Aware and Shift Mixer for Multi-modal Brain Tumor Segmentationcited by 0
  21. 20243D-EffiViTCaps: 3D Efficient Vision Transformer with Capsule for Medical Image Segmentationcited by 0
  22. 2024A dual-task mutual learning framework for predicting post-thrombectomy cerebral hemorrhagecited by 0
  23. 2024Bilateral Hippocampi Segmentation in Low Field MRIs Using Mutual Feature Learning via Dual-Viewscited by 0
  24. 2024End-to-end Triple-domain PET Enhancement: A Hybrid Denoising-and-reconstruction Framework for Reconstructing Standard-dose PET Images from Low-dose PET Sinogramscited by 0
  25. 2025Selective Complementary Feature Fusion and Modal Feature Compression Interaction for Brain Tumor Segmentationcited by 0
  26. 2025MSD-KMamba: Bidirectional Spatial-Aware Multi-Modal 3D Brain Segmentation via Multi-scale Self-Distilled Fusion Strategycited by 0
  27. 2025Pancakes: Consistent Multi-Protocol Image Segmentation Across Biomedical Domainscited by 0
  28. 2026Probing and Inducing Clinical Modality Grounding in Brain Tumor Segmentationcited by 0
  29. 2026MCSeg: Pre-training and Fine-tuning Volumetric Pyramid Transformer for Multi-modal Cardiac Image Segmentationcited by 0