arXiv Computer Vision

THA-Flow Generative Model: Prosthesis Geometry Prediction from Preoperative CT

THA-Flow is a conditional flow-matching model that generates 3‑D prosthesis geometry directly from preoperative CT scans for total hip arthroplasty. It uses separate AutoencoderKL models to compress bone anatomy and prosthesis shapes, and a 3‑D UNet to learn a flow from Gaussian noise to the prosthesis latent space conditioned on bone geometry. In a retrospective cohort of 1,355 hips, the model produced accurate acetabular and femoral geometries for 93.4% of cases, preserving component position and alignment while allowing limited local variation.

arXiv Computer Vision
Sep 7

Towards patient-specific optimization for mandibular reconstruction planning based on predicted bone-union propensity

The paper introduces OsteoOpt++, an image‑to‑decision loop that uses pre‑operative CT scans to build a personalized digital twin of a patient’s mandible and then applies Bayesian optimization to adjust six surgical variables for improved bone‑union propensity at the donor‑host interface. In both generic defect models and patient‑specific cases, the optimized plans increased donor‑mandible apposition by up to 29 % and 26 % respectively compared to surgeon‑generated plans, and the predicted apposition closely matched year‑1 bone formation (Dice overlap 70–85 %). The study demonstrates the feasibility of using apposition‑derived predictions to evaluate and compare reconstruction options and provides open‑source code for further development.

By Hamidreza Aftabi, John E. Lloyd, Amanda Ding, Benedikt Sagl, Eitan Prisman, Antony Hodgson, Sidney Fels
arXiv AI
Aug 3

TAVI-TEC: An AI-Based Tool for Procedural Planning of Transcatheter Aortic Valve Implantation

arXiv:2607. 29243v1 Announce Type: cross Abstract: Computed tomography angiography (CTA) is crucial for preprocedural TAVI planning, providing the anatomical information required for prosthesis sizing and vascular access assessment.

By Alessandra Zerillo, Stefano Cannata, Diego Bellavia, Daniele Ciriello, Simone Manini, Salvatore Pasta, Caterina Gandolfo
arXiv Machine Learning
Aug 4

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation

arXiv:2608. 00195v1 Announce Type: cross Abstract: High-resolution 3D segmentation of hip and shoulder anatomy from CT and MRI is essential for surgical planning, yet frozen segmentation models often fail under domain shift.

By John Garcia Henao, Nicholas B\"unger, Benedikt Herzog, Cindy Guerrero Toro, Benjamin Vella, Matthias Biner, Rico Br\"utsch, Carmen Castroviejo Fernandez, Felix \"Ottl, Norman Juchler, Armando Hoch, Bettina Hochreiter, Sven Hirsch, Sebastiano Caprara
arXiv AI
Aug 10

Measurements Automatically Extracted from Zero Echo Time MRI Using Deep Learning Image Segmentation and Geometric Modeling Agree with Expert Manual Readings

arXiv:2608. 07368v1 Announce Type: cross Abstract: Computed tomography (CT) remains the reference for 3D osseous morphometry in femoroacetabular impingement (FAI) but requires ionizing radiation and manual measurement.

By Jack Consolini, Eric A. Bogner, Meghan Sahr, Matthew F. Koff, Kevin M. Koch, Hollis G. Potter
arXiv AI
4d ago

Automated Screw Planning for Reduced Pelvic Fractures Based on Statistical Shape Models and Deep Learning

The article presents a fully automated pipeline for preoperative iliosacral screw planning in pelvic fracture patients, utilizing patient-specific 3D anatomy to identify safe screw corridors and generate individualized insertion trajectories. In a study of 200 clinical cases, the automated method increased the safety margin of safe insertion corridors by 2% across four screw types, reduced mean planning time by over 90%, and achieved a 95% clinical acceptance rate compared to conventional manual measurements.

By Yang Gao, Sutuke Yibulayimu, Yanzhen Liu, Zian Zhao, Yudi Sang
arXiv Computer Vision
Aug 21

PhysSFI-Net: Physics-informed Geometric Learning of Skeletal and Facial Interactions for Orthognathic Surgical Outcome Prediction

arXiv:2601. 02088v3 Announce Type: replace Abstract: Orthognathic surgery repositions jaw bones to restore occlusion and enhance facial aesthetics.

By Jiahao Bao, Huazhen Liu, Yu Zhuang, Leran Tao, Xinyu Xu, Yongtao Shi, Mengjia Cheng, Yiming Wang, Congshuang Ku, Ting Zeng, Yilang Du, Siyi Chen, Shunyao Shen, Suncheng Xiang, Hongbo Yu