mlsanityData to 7 Oct 2026

nnInteractive: Redefining 3D Promptable Segmentation

arXiv 2503.08373 ↗First posted 11 Mar 2025cs.CVcited by 39

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Abstract (arXiv)

Accurate and efficient 3D segmentation is essential for both clinical and research applications. While foundation models like SAM have revolutionized interactive segmentation, their 2D design and domain shift limitations make them ill-suited for 3D medical images. Current adaptations address some of these challenges but remain limited, either lacking volumetric awareness, offering restricted interactivity, or supporting only a small set of structures and modalities. Usability also remains a challenge, as current tools are rarely integrated into established imaging platforms and often rely on cumbersome web-based interfaces with restricted functionality. We introduce nnInteractive, the first comprehensive 3D interactive open-set segmentation method. It supports diverse prompts-including points, scribbles, boxes, and a novel lasso prompt-while leveraging intuitive 2D interactions to generate full 3D segmentations. Trained on 120+ diverse volumetric 3D datasets (CT, MRI, PET, 3D Microscopy, etc.), nnInteractive sets a new state-of-the-art in accuracy, adaptability, and usability. Crucially, it is the first method integrated into widely used image viewers (e.g., Napari, MITK), ensuring broad accessibility for real-world clinical and research applications. Extensive benchmarking demonstrates that nnInteractive far surpasses existing methods, setting a new standard for AI-driven interactive 3D segmentation. nnInteractive is publicly available: https://github.com/MIC-DKFZ/napari-nninteractive (Napari plugin), https://www.mitk.org/MITK-nnInteractive (MITK integration), https://github.com/MIC-DKFZ/nnInteractive (Python backend).

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Builds on 50 of its 132 references that are in the map. First posted on arXiv 11 Mar 2025.

Builds on

50 of 132 references.

References · 50

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38 more
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  13. 2023ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Imagecited by 47
  14. 2023MultiTalent: A Multi-Dataset Approach to Medical Image Segmentationcited by 45
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 19; 2026: 20.

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  1. 2025MedSAM2: Segment Anything in 3D Medical Images and Videoscited by 88
  2. 2025Render-FM: Feedforward Model for Real-time Photorealistic Volumetric Renderingcited by 3
  3. 2025Rethinking Whole-Body CT Image Interpretation: An Abnormality-Centric Approachcited by 2
  4. 2025ENSAM: an efficient foundation model for interactive segmentation of 3D medical imagescited by 2
  5. 2025K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Modelcited by 2
  6. 2025Dynamic Prompt Generation for Interactive 3D Medical Image Segmentation Trainingcited by 2
  7. 2025MeisenMeister: A Simple Two Stage Pipeline for Breast Cancer Classification on MRIcited by 2
  8. 2025BackSplit: The Importance of Sub-dividing the Background in Biomedical Lesion Segmentationcited by 2
  9. 2025Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentationcited by 2
  10. 2026On The Robustness of Foundational 3D Medical Image Segmentation Models Against Imprecise Visual Promptscited by 2
  11. 2025PolyPose: Deformable 2D/3D Registration via Polyrigid Transformationscited by 1
  12. 2025TopoSculpt: Betti-Steered Topological Sculpting of 3D Fine-grained Tubular Shapescited by 1
27 more
  1. 2025Efficient Universal Models for Medical Image Segmentation via Weakly Supervised In-Context Learningcited by 1
  2. 2025Medal S: Spatio-Textual Prompt Model for Medical Segmentationcited by 1
  3. 2026Finally Outshining the Random Baseline: A Simple and Effective Solution for Active Learning in 3D Biomedical Imagingcited by 1
  4. 2026Universality Reconsidered: Rethinking the Validation of Foundation Models for General-Purpose 3D Medical Segmentationcited by 1
  5. 2026Developing Foundation Models for Universal Segmentation from 3D Whole-Body Positron Emission Tomographycited by 1
  6. 2025RAPS-3D: Efficient interactive segmentation for 3D radiological imagingcited by 0
  7. 2025Promptable Longitudinal Lesion Segmentation in Whole-Body CTcited by 0
  8. 2025Visionerves: Automatic and Reproducible Hybrid AI for Peripheral Nervous System Recognition Applied to Endometriosis Casescited by 0
  9. 2025MOIS-SAM2: Exemplar-based Segment Anything Model 2 for multilesion interactive segmentation of neurofibromas in whole-body MRIcited by 0
  10. 2025Domain-Specialized Interactive Segmentation Framework for Meningioma Radiotherapy Planningcited by 0
  11. 2025Resource-efficient Automatic Refinement of Segmentations via Weak Supervision from Light Feedbackcited by 0
  12. 20263DLAND: 3D Lesion Abdominal Anomaly Localization Datasetcited by 0
  13. 2026CLoPA: Continual Low Parameter Adaptation of Interactive Segmentation for Medical Image Annotationcited by 0
  14. 2026Foundation Model-guided Iteratively Prompting and Pseudo-Labeling for Partially Labeled Medical Image Segmentationcited by 0
  15. 2026Why Invariance is Not Enough for Biomedical Domain Generalization and How to Fix Itcited by 0
  16. 2026CrossPan: A Comprehensive Benchmark for Cross-Sequence Pancreas MRI Segmentation and Generalizationcited by 0
  17. 2026RoadGIE: Towards A Global-Scale Aerial Benchmark for Generalizable Interactive Road Extractioncited by 0
  18. 2026POPSICLE: Benchmark Datasets for Segmentation and Localization in CryoETcited by 0
  19. 2026LETT-NeXt: A Lightweight RECIST-Guided Model for 3D CT Lesion Segmentationcited by 0
  20. 2026UniMedSeg: Unified In-Context Learning for Multi-Paradigm 2D/3D Medical Image Segmentationcited by 0
  21. 2026SLIP: Segmentation with Low-latency Interactive Prompting for 3D Medical Imagescited by 0
  22. 2026Effect of User-Prompted Priors on Semi-Automated Cancer Lesion Segmentation in Whole-Body Computed Tomographycited by 0
  23. 2026MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentationcited by 0
  24. 2026Prompt-Guided Interactive Segmentation of Interstitial Lung Disease in Thoracic CTcited by 0
  25. 2026Whole-Body MRI Classification via Prompt-Based Clinical Conditioningcited by 0
  26. 2026BS: Take the Hint - Interactive Multitracer PET/CT Lesion Segmentation with a Scribble-Conditioned ResEnc U-Netcited by 0
  27. 2026IMVS: Interactive Medical Volume Segmentation with Test-Time Adaptation - A New Method for Annotating Radiology Datasetscited by 0