TY - GEN
T1 - D4Recon
T2 - 28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025
AU - Basak, Hritam
AU - Yin, Zhaozheng
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - 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.
AB - 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.
KW - 3D Reconstruction
KW - Endoscopy
KW - Gaussian Splatting
UR - https://www.scopus.com/pages/publications/105017974166
U2 - 10.1007/978-3-032-05114-1_16
DO - 10.1007/978-3-032-05114-1_16
M3 - Conference contribution
AN - SCOPUS:105017974166
SN - 9783032051134
T3 - Lecture Notes in Computer Science
SP - 159
EP - 169
BT - Medical Image Computing and Computer Assisted Intervention, MICCAI 2025 - 28th International Conference, 2025, Proceedings
A2 - Gee, James C.
A2 - Hong, Jaesung
A2 - Sudre, Carole H.
A2 - Golland, Polina
A2 - Park, Jinah
A2 - Alexander, Daniel C.
A2 - Iglesias, Juan Eugenio
A2 - Venkataraman, Archana
A2 - Kim, Jong Hyo
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 23 September 2025 through 27 September 2025
ER -