mlsanityData to 7 Oct 2026

Volumetric Attention for 3D Medical Image Segmentation and Detection

arXiv 2004.01997 ↗First posted 4 Apr 2020eess.IV cs.CVcited by 29

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Abstract (arXiv)

A volumetric attention(VA) module for 3D medical image segmentation and detection is proposed. VA attention is inspired by recent advances in video processing, enables 2.5D networks to leverage context information along the z direction, and allows the use of pretrained 2D detection models when training data is limited, as is often the case for medical applications. Its integration in the Mask R-CNN is shown to enable state-of-the-art performance on the Liver Tumor Segmentation (LiTS) Challenge, outperforming the previous challenge winner by 3.9 points and achieving top performance on the LiTS leader board at the time of paper submission. Detection experiments on the DeepLesion dataset also show that the addition of VA to existing object detectors enables a 69.1 sensitivity at 0.5 false positive per image, outperforming the best published results by 6.6 points.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Apr 2020.

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Citing papers per year: 2021: 12; 2022: 6; 2023: 4; 2024: 3; 2025: 3; 2026: 1.

29 papers.

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  1. 2021Medical Transformer: Gated Axial-Attention for Medical Image Segmentationcited by 319
  2. 2021Recent advances and clinical applications of deep learning in medical image analysiscited by 104
  3. 2021Pyramid Medical Transformer for Medical Image Segmentationcited by 20
  4. 2024Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretationcited by 18
  5. 2021Asymmetric 3D Context Fusion for Universal Lesion Detectioncited by 14
  6. 2021T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imagingcited by 11
  7. 2023Attention Mechanisms in Medical Image Segmentation: A Surveycited by 9
  8. 2023Towards Simultaneous Segmentation of Liver Tumors and Intrahepatic Vessels via Cross-attention Mechanismcited by 8
  9. 2021PA-ResSeg: A Phase Attention Residual Network for Liver Tumor Segmentation from Multi-phase CT Imagescited by 7
  10. 2022Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rayscited by 7
  11. 2023CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentationcited by 7
  12. 2021Conditional Training with Bounding Map for Universal Lesion Detectioncited by 5
17 more
  1. 2022Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future Directionscited by 5
  2. 2021RECIST-Net: Lesion detection via grouping keypoints on RECIST-based annotationcited by 4
  3. 2021BezierSeg: Parametric Shape Representation for Fast Object Segmentation in Medical Imagescited by 4
  4. 2021Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientationscited by 3
  5. 2021Voxel-level Siamese Representation Learning for Abdominal Multi-Organ Segmentationcited by 3
  6. 2024Medical Image Segmentation Using Directional Window Attentioncited by 3
  7. 20223D Shuffle-Mixer: An Efficient Context-Aware Vision Learner of Transformer-MLP Paradigm for Dense Prediction in Medical Volumecited by 2
  8. 2022Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT imagescited by 2
  9. 2024Few-Shot 3D Volumetric Segmentation with Multi-Surrogate Fusioncited by 2
  10. 2025The Missing Piece: A Case for Pre-Training in 3D Medical Object Detectioncited by 2
  11. 2022DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detectioncited by 1
  12. 2023BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervisioncited by 1
  13. 2025MOSAIC: A Multi-View 2.5D Organ Slice Selector with Cross-Attentional Reasoning for Anatomically-Aware CT Localization in Medical Organ Segmentationcited by 1
  14. 2026DyABD: The Abdominal Muscle Segmentation in Dynamic MRI Benchmarkcited by 1
  15. 2021MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentationcited by 0
  16. 2022A Survey on Causal Representation Learning and Future Work for Medical Image Analysiscited by 0
  17. 2025AI-CNet3D: An Anatomically-Informed Cross-Attention Network with Multi-Task Consistency Fine-tuning for 3D Glaucoma Classificationcited by 0