3D Reconstruction of Whole Stomach from Endoscope Video Using Structure-from-Motion
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Abstract (arXiv)
Gastric endoscopy is a common clinical practice that enables medical doctors to diagnose the stomach inside a body. In order to identify a gastric lesion's location such as early gastric cancer within the stomach, this work addressed to reconstruct the 3D shape of a whole stomach with color texture information generated from a standard monocular endoscope video. Previous works have tried to reconstruct the 3D structures of various organs from endoscope images. However, they are mainly focused on a partial surface. In this work, we investigated how to enable structure-from-motion (SfM) to reconstruct the whole shape of a stomach from a standard endoscope video. We specifically investigated the combined effect of chromo-endoscopy and color channel selection on SfM. Our study found that 3D reconstruction of the whole stomach can be achieved by using red channel images captured under chromo-endoscopy by spreading indigo carmine (IC) dye on the stomach surface.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 May 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2; 2024: 1; 2025: 3; 2026: 2.
10 papers.
- 2024Leveraging Near-Field Lighting for Monocular Depth Estimation from Endoscopy Videoscited by 14
- 2023BASED: Bundle-Adjusting Surgical Endoscopic Dynamic Video Reconstruction using Neural Radiance Fieldscited by 5
- 2022BDIS: Bayesian Dense Inverse Searching Method for Real-Time Stereo Surgical Image Matchingcited by 4
- 2021Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgerycited by 3
- 2023BDIS-SLAM: A lightweight CPU-based dense stereo SLAM for surgerycited by 2
- 2025Endoscopic Depth Estimation Based on Deep Learning: A Surveycited by 1
- 2025Moving Light Adaptive Colonoscopy Reconstruction via Illumination-Attenuation-Aware 3D Gaussian Splattingcited by 1
- 2025Online camera-pose-free stereo endoscopic tissue deformation recovery with tissue-invariant vision-biomechanics consistencycited by 0
- 2026Automated Assessment of Kidney Ureteroscopy Exploration for Trainingcited by 0
- 2026RAUL: Reference-Assisted Ureteroscopy Localization for Skill Assessmentcited by 0
- 2026RAUL: Reference-Assisted Ureteroscopy Localization for Skill Assessment16 Sep 2026
- 2026Automated Assessment of Kidney Ureteroscopy Exploration for Training17 Feb 2026
- 2025Moving Light Adaptive Colonoscopy Reconstruction via Illumination-Attenuation-Aware 3D Gaussian Splatting21 Oct 2025
- 2025Endoscopic Depth Estimation Based on Deep Learning: A Survey28 Jul 2025
- 2025Online camera-pose-free stereo endoscopic tissue deformation recovery with tissue-invariant vision-biomechanics consistency24 Jun 2025
- 2024Leveraging Near-Field Lighting for Monocular Depth Estimation from Endoscopy Videos26 Mar 2024
- 2023BDIS-SLAM: A lightweight CPU-based dense stereo SLAM for surgery25 Dec 2023
- 2023BASED: Bundle-Adjusting Surgical Endoscopic Dynamic Video Reconstruction using Neural Radiance Fields27 Sep 2023
- 2022BDIS: Bayesian Dense Inverse Searching Method for Real-Time Stereo Surgical Image Matching6 May 2022
- 2021Bayesian dense inverse searching algorithm for real-time stereo matching in minimally invasive surgery14 Jun 2021