mlsanityData to 7 Oct 2026

Reconstructing Sinus Anatomy from Endoscopic Video -- Towards a Radiation-free Approach for Quantitative Longitudinal Assessment

arXiv 2003.08502 ↗First posted 18 Mar 2020cs.CVcited by 23

Not on the map. Why?

Abstract (arXiv)

Reconstructing accurate 3D surface models of sinus anatomy directly from an endoscopic video is a promising avenue for cross-sectional and longitudinal analysis to better understand the relationship between sinus anatomy and surgical outcomes. We present a patient-specific, learning-based method for 3D reconstruction of sinus surface anatomy directly and only from endoscopic videos. We demonstrate the effectiveness and accuracy of our method on in and ex vivo data where we compare to sparse reconstructions from Structure from Motion, dense reconstruction from COLMAP, and ground truth anatomy from CT. Our textured reconstructions are watertight and enable measurement of clinically relevant parameters in good agreement with CT. The source code is available at https://github.com/lppllppl920/DenseReconstruction-Pytorch.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Mar 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 3; 2023: 4; 2024: 7; 2025: 3; 2026: 1.

23 papers.

Sort:

  1. 2022Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgerycited by 122
  2. 2021E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perceptioncited by 46
  3. 2024Deform3DGS: Flexible Deformation for Fast Surgical Scene Reconstruction with Gaussian Splattingcited by 37
  4. 2024EndoGaussian: Real-time Gaussian Splatting for Dynamic Endoscopic Scene Reconstructioncited by 20
  5. 2024Free-SurGS: SfM-Free 3D Gaussian Splatting for Surgical Scene Reconstructioncited by 20
  6. 2021Adversarial Domain Feature Adaptation for Bronchoscopic Depth Estimationcited by 14
  7. 2024Depth Anything in Medical Images: A Comparative Studycited by 13
  8. 2025From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstructioncited by 10
  9. 2023A Surface-normal Based Neural Framework for Colonoscopy Reconstructioncited by 8
  10. 2023A geometry-aware deep network for depth estimation in monocular endoscopycited by 8
  11. 2021ColDE: A Depth Estimation Framework for Colonoscopy Reconstructioncited by 7
  12. 2021FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videoscited by 5
11 more
  1. 2022SuperPoint features in endoscopycited by 5
  2. 2023RIDE: Self-Supervised Learning of Rotation-Equivariant Keypoint Detection and Invariant Description for Endoscopycited by 5
  3. 2022A comprehensive survey on recent deep learning-based methods applied to surgical datacited by 3
  4. 2024FLex: Joint Pose and Dynamic Radiance Fields Optimization for Stereo Endoscopic Videoscited by 3
  5. 2023A Quantitative Evaluation of Dense 3D Reconstruction of Sinus Anatomy from Monocular Endoscopic Videocited by 2
  6. 2026Diff2DGS: Reliable Reconstruction of Occluded Surgical Scenes via 2D Gaussian Splattingcited by 2
  7. 20213D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Trainingcited by 1
  8. 2024An Endoscopic Chisel: Intraoperative Imaging Carves 3D Anatomical Modelscited by 1
  9. 2024EndoPerfect: High-Accuracy Monocular Depth Estimation and 3D Reconstruction for Endoscopic Surgery via NeRF-Stereo Fusioncited by 1
  10. 2025Feature-EndoGaussian: Feature Distilled Gaussian Splatting in Surgical Deformable Scene Reconstructioncited by 0
  11. 2025ColorGS: High-fidelity Surgical Scene Reconstruction with Colored Gaussian Splattingcited by 0