Auto-differentiable digitally reconstructed radiographs in PyTorch

[CVPR 2024] Intraoperative 2D/3D registration via differentiable X-ray rendering

Library and executables for modeling and registration applications in medical image analysis. Particular emphasis on intraoperative fluoroscopic (X-ray) navigation via 2D/3D registration.

Code and data for the "annotation" component of the IPCAI 2020 paper: "Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration." https://arxiv.org/abs/1911.07042 or https://doi.org/10.1007/s11548-020-02162-7

Code for the registration component of the IPCAI 2020 paper: "Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration." https://arxiv.org/abs/1911.07042 or https://doi.org/10.1007/s11548-020-02162-7

Code for ICASSP 2024 paper"Embedded Feature Similarity Optimization with Specific Parameter Initialization for 2D/3D Medical Image Registration"

Monocular Camera Localization in Prior LiDAR Maps with 2D-3D Line Correspondences

Open-source 2D/3D registration datasets and dataloaders for DiffDRR

Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for 2D/3D registration

Code for ISBI 2024 paper "Fully Differentiable Correlation-driven 2D/3D Registration for X-Ray to CT Image Fusion"

[WACV2022] "Shape-Coded ArUco: Fiducial Marker for Bridging 2D and 3D Modalities".

[ACCV 2024 (Oral)] Official Implementation of "RayEmb: Arbitrary Landmark Detection in X-Ray Images Using Ray Embedding Subspace", Pragyan Shrestha, Chun Xie, Yuichi Yoshii, Itaru Kitahara

MOVED HERE: https://github.com/rg2/xreg