mlsanityData to 14 Oct 2026

EndoMetric: Near-Light Monocular Metric Scale Estimation in Endoscopy

arXiv 2410.15065 ↗First posted 19 Oct 2024cs.CVcited by 3

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Abstract (arXiv)

Geometric reconstruction and SLAM with endoscopic images have advanced significantly in recent years. In most medical fields, monocular endoscopes are employed, and the algorithms used are typically adaptations of those designed for external environments, resulting in 3D reconstructions with an unknown scale factor. For the first time, we propose a method to estimate the real metric scale of a 3D reconstruction from standard monocular endoscopic images without relying on application-specific learned priors. Our fully model-based approach leverages the near-light sources embedded in endoscopes, positioned at a small but nonzero baseline from the camera, in combination with the inverse-square law of light attenuation, to accurately recover the metric scale from scratch. This enables the transformation of any endoscope into a metric device, which is crucial for applications such as measuring polyps, stenosis, or assessing the extent of diseased tissue.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 9 of its 25 references that are in the map. First posted on arXiv 19 Oct 2024.

Builds on

9 of 25 references.

References · 9

  1. 2023Segment Anythingcited by 8,234
  2. 2020ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAMcited by 878
  3. 2016Direct Sparse Odometrycited by 485
  4. 2022EndoMapper dataset of complete calibrated endoscopy procedurescited by 53
  5. 2019DefSLAM: Tracking and Mapping of Deforming Scenes from Monocular Sequencescited by 37
  6. 2019Direct Sparse Mappingcited by 25
  7. 2020VR-Caps: A Virtual Environment for Capsule Endoscopycited by 23
  8. 2022Photometric single-view dense 3D reconstruction in endoscopycited by 11
  9. 2024CudaSIFT-SLAM: multiple-map visual SLAM for full procedure mapping in real human endoscopycited by 11

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.