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D4Recon: Dual-Stage Deformation and Dual-Scale Depth Guidance for Endoscopic Reconstruction

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Deformable tissue reconstruction in endoscopy is vital for surgery, yet current methods struggle with high-fidelity reconstruction of irreversible tissue deformations. To this end, we present D4Recon, a novel framework for real-time and high-fidelity endoscopic reconstruction, addressing crucial challenges in surgical applications. A The image shows a stylized letter "D" in a light blue color.ual-stage The image shows a stylized, light blue letter "D" with a subtle glow effect, set against a white background.eformation modeling and a A blue, pixelated letter "D" on a white background. The letter is stylized with a blocky, digital appearance, resembling a symbol or icon.ual-scale A stylized letter "D" in a light blue color with a subtle glow effect, set against a white background. The design emphasizes the letter's shape and color, creating a visually striking symbol.epth guidance ( The image shows a mathematical notation with the letter "D" followed by a superscript "4". This represents D^4 , indicating the fourth power of D.) are proposed in a dynamic 3D Gaussian Splatting paradigm along with lightweight multi-layer perception (MLP) to model dynamics in endoscopic scenes. In the dual-stage deformation modeling, we introduce a spatial deformation model to correct multiview inconsistencies, accompanied by a temporal deformation model that accurately represents tissue distortion and dynamic tissue interaction with surgical tools in the reference frames. In the dual-scale depth guidance, we propose to balance local error correction with absolute depth consistency, enabling precise depth refinement while preserving fine-grained color accuracy. D4Recon generates accurate 3D reconstructions with superior PSNR, SSIM, and LPIPS scores, outperforming existing methods in terms of geometric coherence and photorealism with real-time rendering speed, as demonstrated by extensive experiments on diverse endoscopic datasets. Reconstruction videos are in the supplementary file. Website.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention, MICCAI 2025 - 28th International Conference, 2025, Proceedings
EditorsJames C. Gee, Jaesung Hong, Carole H. Sudre, Polina Golland, Jinah Park, Daniel C. Alexander, Juan Eugenio Iglesias, Archana Venkataraman, Jong Hyo Kim
PublisherSpringer Science and Business Media Deutschland GmbH
Pages159-169
Number of pages11
ISBN (Print)9783032051134
DOIs
StatePublished - 2026
Event28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025 - Daejeon, Korea, Republic of
Duration: Sep 23 2025Sep 27 2025

Publication series

NameLecture Notes in Computer Science
Volume15968 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025
Country/TerritoryKorea, Republic of
CityDaejeon
Period09/23/2509/27/25

Keywords

  • 3D Reconstruction
  • Endoscopy
  • Gaussian Splatting

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