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A Joint 2D-3D Statistical Shape Model for Orthopedic Reconstruction

Paper recorded by Signals 4 on 2026-09-08 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-08 on arXiv · recorded by Signals 4 on 2026-09-09

Category: cs.CV · 计算机视觉 · first seen 2026-09-09

Abstract

Three-dimensional femoral reconstruction from radiographs supports surgical planning, implant sizing, and post-operative follow-up, but remains ill-posed as X-ray projections discard depth information. Existing methods often incorporate a 3D statistical shape model (SSM) as a shape prior to guide reconstructions toward anatomically plausible shapes, relying on iterative 3D-to-2D projection matchin

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#119 most recent of 237 cs.CV papers we have recorded · ↑ newer: Spheriverse: 3D Scene Understanding from Spherical Observations in the · ↓ older: DXPR: Depth-Based Vision-LiDAR Cross-Modal Place Recognition Using Vis
Cite this page: A Joint 2D-3D Statistical Shape Model for Orthopedic Reconstruction: the #119 most recent of 237 cs.CV papers we have recorded (as of 2026-09-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-joint-2d-3d-statistical-shape-model-for-orthopedic-reconstruction.html
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