mlsanityData to 14 Oct 2026

SAM & SAM 2 in 3D Slicer: SegmentWithSAM Extension for Annotating Medical Images

arXiv 2408.15224 ↗First posted 27 Aug 2024eess.IV cs.CV cs.SEcited by 3

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Abstract (arXiv)

Creating annotations for 3D medical data is time-consuming and often requires highly specialized expertise. Various tools have been implemented to aid this process. Segment Anything Model 2 (SAM 2) offers a general-purpose prompt-based segmentation algorithm designed to annotate videos. In this paper, we adapt this model to the annotation of 3D medical images and offer our implementation in the form of an extension to the popular annotation software: 3D Slicer. Our extension allows users to place point prompts on 2D slices to generate annotation masks and propagate these annotations across entire volumes in either single-directional or bi-directional manners. Our code is publicly available on https://github.com/mazurowski-lab/SlicerSegmentWithSAM and can be easily installed directly from the Extension Manager of 3D Slicer as well.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 12 of its 21 references that are in the map. First posted on arXiv 27 Aug 2024.

Builds on

12 of 21 references.

References · 12

  1. 2023Segment Anythingcited by 8,234
  2. 2024SAM 2: Segment Anything in Images and Videoscited by 2,863
  3. 2019Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentationcited by 260
  4. 2020Medical Image Segmentation Using Deep Learning: A Surveycited by 164
  5. 2023SAM3D: Segment Anything Model in Volumetric Medical Imagescited by 34
  6. 2023MeLo: Low-rank Adaptation is Better than Fine-tuning for Medical Image Diagnosiscited by 33
  7. 2023SAMM (Segment Any Medical Model): A 3D Slicer Integration to SAMcited by 31
  8. 2024Segment anything model 2: an application to 2D and 3D medical imagescited by 28
  9. 2024SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRIcited by 14
  10. 2024FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Imagescited by 14
  11. 2023TomoSAM: a 3D Slicer extension using SAM for tomography segmentationcited by 5
  12. 2024FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantificationcited by 1

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025SAM2 for Image and Video Segmentation: A Comprehensive Surveycited by 13
  2. 2025Accelerating Volumetric Medical Image Annotation via Short-Long Memory SAM 2cited by 5
  3. 2025Towards Better Ultrasound Video Segmentation Foundation Model: An Empirical study on SAM2 Finetuning from Data Perspectivecited by 0