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https://github.com/jianqingzheng/path_planning_for_FEVAR

Code for "Towards 3d path planning from a single 2d fluoroscopic image for robot assisted fenestrated endovascular aortic repair" (ICRA 2019)
https://github.com/jianqingzheng/path_planning_for_FEVAR

endovascular-treatment image-guided-interventions reconstruction surgery-navigation surgery-planning surgical-robotics

Last synced: 3 months ago
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Code for "Towards 3d path planning from a single 2d fluoroscopic image for robot assisted fenestrated endovascular aortic repair" (ICRA 2019)

Host: GitHub
URL: https://github.com/jianqingzheng/path_planning_for_FEVAR
Owner: jianqingzheng
License: apache-2.0
Created: 2019-02-01T14:32:04.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2024-02-17T23:13:11.000Z (5 months ago)
Last Synced: 2024-02-18T00:22:45.431Z (5 months ago)
Topics: endovascular-treatment, image-guided-interventions, reconstruction, surgery-navigation, surgery-planning, surgical-robotics
Language: MATLAB
Homepage: https://doi.org/10.1109/ICRA.2019.8793918
Size: 34 MB
Stars: 21
Watchers: 2
Forks: 5
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Lists

awesome_medical - path_planning_for_FEVAR

README

        


 Path_planning_for_FEVAR 

  

[![DOI](https://img.shields.io/badge/DOI-10.1109%2FICRA.2019.8793918-darkyellow)](https://ieeexplore.ieee.org/abstract/document/8793918/) \|

[![arXiv](https://img.shields.io/badge/arXiv-1809.05955-b31b1b.svg)](https://arxiv.org/abs/1809.05955)



Code for *ICRA'2019* paper [Towards 3d path planning from a single 2d fluoroscopic image for robot assisted fenestrated endovascular aortic repair](https://ieeexplore.ieee.org/abstract/document/8793918)

---

### Contents ###

- [0. Brief Introduction](#0-brief-intro)

- [1. Requirement](#1-requirement)

- [2. Usage](#2-usage)

  - [2.1. Script 'demo_2D3Dregist.m'](#21-script-demo_2d3dregistm)

  - [2.2. Folder 'function'](#22-folder-function)

  - [2.3. Folder 'data'](#23-folder-data)

  - [2.4. Folder 'external'](#24-folder-external)

- [3. Citing this work](#3-citing-this-work)

---

## 0. Brief Intro ##

* The segmented shape of the abdominal aorta from a CT scan:



![header](imgs/aorta_seg.gif)



> The segmentation process is implemented following this work: [Abdominal Aortic Aneurysm Segmentation

with a Small Number of Training Subjects](https://arxiv.org/pdf/1804.02943.pdf)

* The 3D abdominal aorta shape and the center line recovered from one 2D X-ray image:



![header](imgs/demo-recover.gif)



* How it looks like when a catheter moves through the recovered center line of the aorta:



  

![header](imgs/demo-visual.gif)



---

## 1. Requirement ##

[![OS-WIN](https://img.shields.io/badge/OS-Windows%7CLinux-darkblue)]()

[![Matlab](https://img.shields.io/badge/Matlab-R2016a%7CR2017a-blue)](https://www.mathworks.com/products/matlab.html)

> Other Matlab version could be also applicable

---

## 2. Usage ##

```

$DOWNLOAD_DIR/

├── data/

|   ├── IMG26.JPG

|   ├── Label_save_P26.mat

|   ├── Skeleton3D_P26.mat

|   └── ...

├── external/

|   ├── TPS3D/

|   ├── distance2curve/

|   └── phi-max-skeleton3d-matlab-a98ad07/

├── function/

|   ├── array2str.m

|   ├── branch_classify.m

|   ├── branch_node_assign.m

|   ├── node_classification.m

|   ├── placement_match.m

|   ├── points_dist.m

|   ├── project3D22D.m

|   ├── regist2D3D.m

|   ├── regist_energy.m

|   └── trunk_node_assign.m

└── demo_2D3Dregist.m

```

### 2.1. Script 'demo_2D3Dregist.m': ###

This demonstrates how to recover a 3D skeleton for the robotic path from a 2D intra-operative segmented aneurysm shape and a 3D pre-operative skeleton. It will import a 2D jpg image of pre-operative fluoroscopy, a 2D segmentation label, and a 3D skeleton. It will display the time cost for registration of 2D/3D skeletons, the intra-operative (ground truth) skeleton, the pre-operative skeleton, and our prediction, as well as the evaluated distance errors in 2D and 3D.

### 2.2. Folder 'function': ###

It includes all the codes written for the deformable registration between 2D and 3D skeletons.

> Please kindly read the license in each file.

### 2.3. Folder 'data': ###

It includes the imported data used in the demonstration.

### 2.4. Folder 'external': ###

It includes redistributed codes used in the demonstration.

> Please kindly read the license in each file.

## 3. Citing this work

For any academic publication using the codes in this folder, please kindly cite:

- J. Q. Zheng, X. Y. Zhou, C. Riga and G. Z. Yang, "Towards 3d path planning from a single 2d fluoroscopic image for robot assisted fenestrated endovascular aortic repair", IEEE International Conference on Robotics and Automation (ICRA), 2019.

```bibtex

@inproceedings{zheng2019towards,

  title={Towards 3d path planning from a single 2d fluoroscopic image for robot assisted fenestrated endovascular aortic repair},

  author={Zheng, Jian-Qing and Zhou, Xiao-Yun and Riga, Celia and Yang, Guang-Zhong},

  booktitle={2019 International Conference on Robotics and Automation (ICRA)},

  pages={8747--8753},

  year={2019},

  organization={IEEE},

  doi={10.1109/ICRA.2019.8793918},

}

```

and, if applicable, the aorta segmentation work:

- J. Q. Zheng, X. Y. Zhou, Q. B. Li, C. Riga and G. Z. Yang, "Abdominal aortic aneurysm segmentation with a small number of training subjects." arXiv preprint arXiv:1804.02943.

```bibtex

@article{zheng2018abdominal,

  title={Abdominal aortic aneurysm segmentation with a small number of training subjects},

  author={Zheng, Jian-Qing and Zhou, Xiao-Yun and Li, Qing-Biao and Riga, Celia and Yang, Guang-Zhong},

  journal={arXiv preprint arXiv:1804.02943},

  year={2018}

}

```