DeepFluoroLabeling-IPCAI2020

该集合包含与 IPCAI/IJCARS 2020 论文“荧光透视中髋关节解剖学的自动注释以实现稳健和高效的 2D/3D 配准”相关的数据和代码。此处托管的数据由实际髋部透视、CT 的注释数据集和来自六个下躯干尸体标本的衍生数据组成。还包括使用数据集和 Python 代码来训练和测试建议模型的文档和示例。更高级别的信息，包括临床动机、先前的工作、算法细节、2D/3D 配准的应用和实验细节，可以在 https://arxiv.org/abs/1911.07042 或 https 的配套论文中找到://doi.org/10.1007/s11548-020-02162-7。我们希望这些代码和数据将有助于开发利用透视的新计算机辅助功能。

This collection contains data and code associated with the IPCAI/IJCARS 2020 paper entitled "Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration". The data hosted herein comprises annotated datasets of real hip fluoroscopy and CT scans, as well as derived data from six lower-torso cadaver specimens. Documentation and examples for utilizing the dataset and Python code to train and test the proposed model are also included. Higher-level information, including clinical motivation, prior work, algorithmic details, applications of 2D/3D registration, and experimental details, can be found in the accompanying paper at https://arxiv.org/abs/1911.07042 or https://doi.org/10.1007/s11548-020-02162-7. We hope that this code and data will facilitate the development of novel computer-aided functionalities leveraging fluoroscopy.

搜集汇总

背景与挑战

背景概述

DeepFluoroLabeling-IPCAI2020数据集包含髋部透视和CT的注释数据，以及用于训练和测试模型的Python代码，旨在支持2D/3D配准的研究。