mlsanityData to 7 Oct 2026

Real Time Multi Organ Classification on Computed Tomography Images

arXiv 2404.18731 ↗First posted 29 Apr 2024cs.CV cs.AI cs.LGcited by 3

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Abstract (arXiv)

Organ segmentation is a fundamental task in medical imaging since it is useful for many clinical automation pipelines. However, some tasks do not require full segmentation. Instead, a classifier can identify the selected organ without segmenting the entire volume. In this study, we demonstrate a classifier based method to obtain organ labels in real time by using a large context size with a sparse data sampling strategy. Although our method operates as an independent classifier at query locations, it can generate full segmentations by querying grid locations at any resolution, offering faster performance than segmentation algorithms. We compared our method with existing segmentation techniques, demonstrating its superior runtime potential for practical applications in medical imaging.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 14 of its 20 references that are in the map. First posted on arXiv 29 Apr 2024.

Builds on

14 of 20 references.

References · 14

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,518
  3. 2021Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentationcited by 1,218
  4. 2021UNETR: Transformers for 3D Medical Image Segmentationcited by 954
  5. 2022Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Imagescited by 823
  6. 2021MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classificationcited by 682
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  8. 2022UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentationcited by 112
  9. 2022Masked Image Modeling Advances 3D Medical Image Analysiscited by 71
  10. 2020SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Imagescited by 66
  11. 2023Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentationcited by 30
  12. 2023vox2vec: A Framework for Self-supervised Contrastive Learning of Voxel-level Representations in Medical Imagescited by 19
2 more
  1. 2023SAM++: Enhancing Anatomic Matching using Semantic Information and Structural Inferencecited by 5
  2. 2023A Hierarchical Descriptor Framework for On-the-Fly Anatomical Location Matching between Longitudinal Studiescited by 4

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Citing papers per year: 2025: 3.

3 papers.

  1. 2025BodyGPS: Anatomical Positioning Systemcited by 0
  2. 2025Consistent Point Matchingcited by 0
  3. 2025Fast Multi-Organ Fine Segmentation in CT Images with Hierarchical Sparse Sampling and Residual Transformercited by 0