Datasets:

mtoan65
/

Pelvic_Bone_Fragments_with_Injuries_Segmentation_Challenge

	---
	title: Pelvic Bone Fragments with Injuries Segmentation Challenge
	description: Pelvic fracture segmentation challenge for CT scans and synthetic X-ray images
	authors:
	- name: Minh Toan Dinh
	email: mtoan65@proton.me
	github: mtoan65
	orcid: 0009-0000-3405-4638
	version: 1.0.0
	license: cc-by-4.0
	dataset:
	- name: PENGWIN Task 1
	description: Pelvic Fracture Segmentation on CT
	doi: 10.5281/zenodo.10927452
	- name: PENGWIN Task 2
	description: Pelvic Fragment Segmentation on Synthetic X-ray Images
	doi: 10.5281/zenodo.10913196
	tags:
	- medical-imaging
	- segmentation
	- pelvic-fracture
	- CT
	- X-ray
	---


	# 🦴 Pelvic Bone Fragments with Injuries Segmentation Challenge 🏥

	![PENGWIN Challenge Banner](./assets/PENGWIN_banner_vp9y9n3.x10.jpeg)

	## 🌟 Welcome to the [PENGWIN segmentation challenge](https://pengwin.grand-challenge.org/)!

	<div align="justify">

	Pelvic fractures, typically resulting from high-energy traumas, are among the most severe injuries, characterized by a disability rate over 50% and a mortality rate over 13%, ranking them as the deadliest of all compound fractures. The complexity of pelvic anatomy, along with surrounding soft tissues, makes surgical interventions especially challenging. Recent years have seen a shift towards the use of robotic-assisted closed fracture reduction surgeries, which have shown improved surgical outcomes. Accurate segmentation of pelvic fractures is essential, serving as a critical step in trauma diagnosis and image-guided surgery. In 3D CT scans, fracture segmentation is crucial for fracture typing, pre-operative planning for fracture reduction, and screw fixation planning. For 2D X-ray images, segmentation plays a vital role in transferring the surgical plan to the operating room via registration, a key step for precise surgical navigation.

	</div>

	## 📊 Challenge Overview

	<div align="justify">

	As a MICCAI 2024 challenge, the PENGWIN segmentation challenge is designed to advance the development of automated pelvic fracture segmentation techniques in both 3D CT scans (Task 1) and 2D X-ray images (Task 2), aiming to enhance their accuarcy and robustness. Our dataset comprises CT scans from 150 patients scheduled for pelvic reduction surgery, collected from multiple institutions using a variety of scanning equipment. This dataset represents a diverse range of patient cohorts and fracture types. Ground-truth segmentations for sacrum and hipbone fragments have been semi-automatically annotated and subsequently validated by medical experts. Furthermore, we have generated high-quality, realistic X-ray images and corresponding 2D labels from the CT data using the DeepDRR method, incorporating a range of virtual C-arm camera positions and surgical tools.

	</div>

	The PENGWIN segmentation challenge consists of two main tasks:

	1. [Task 1: Pelvic fragment segmentation on 3D CT](./Raw/Task_01/README.MD)
	- Segment pelvic fractures in 3D CT scans
	- Dataset: 150 CT scans from diverse patient cohorts

	2. [Task 2: Pelvic fragment segmentation on 2D X-ray](./Raw/Task_02/README.MD)
	- Segment pelvic fragments in 2D synthetic X-ray images
	- Dataset: 50,000 synthetic X-ray images derived from 100 CT scans

	## 🗂️ Repository Structure

	This repository is organized as follows:

	```
	./
	├── assets/
	│ ├── PENGWIN_banner_vp9y9n3.x10.jpeg
	│ ├── task_1.1.jpg
	│ ├── task_1.2.jpg
	│ ├── task_2.1.png
	│ └── task_2.2.png
	├── Raw/
	│ ├── Task_01/ # Task 1 dataset and utilities
	│ │ ├── PENGWIN_CT_train_images_part1.zip
	│ │ ├── PENGWIN_CT_train_images_part2.zip
	│ │ ├── PENGWIN_CT_train_labels.zip
	│ │ └── README.MD # Detailed information about Task 1
	│ └── Task_02/ # Task 2 dataset and utilities
	│ ├── archive_subfolders.sh
	│ ├── pengwin_utils.py
	│ ├── README.MD # Detailed information about Task 2
	│ ├── requirements.txt
	│ └── train/
	│ ├── input/
	│ │ └── images/
	│ │ └── x-ray/
	│ │ ├── 001-010.tar.gz
	│ │ ├── 011-020.tar.gz
	│ │ └── ...
	│ └── output/
	│ └── images/
	│ └── x-ray/
	│ ├── 001-010.tar.gz
	│ ├── 011-020.tar.gz
	│ └── ...
	└── README.md # This file
	```

	## 🚀 Getting Started

	To participate in the PENGWIN challenge 🏆:

	1. 📥 Download the dataset from the provided Zenodo links or follow the steps below:

	1. 🔧 Setup Git LFS:
	```sh
	curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh \| sudo bash
	sudo apt-get install git-lfs
	```

	2. 📂 Create and navigate to the Dataset directory:
	```sh
	mkdir Pelvic_Bone_Fragments_with_Injuries_Segmentation_Challenge
	cd ./Pelvic_Bone_Fragments_with_Injuries_Segmentation_Challenge
	```

	3. 🔗 Initialize Git and add the repository:
	```sh
	git init
	git remote add origin https://mtoan65:<HF_token>@huggingface.co/datasets/mtoan65/Pelvic_Bone_Fragments_with_Injuries_Segmentation_Challenge
	```

	4. ⚙️ Install Git LFS hook for the repository:
	```sh
	git lfs install
	```

	5. ⬇️ Pull the repository:
	```sh
	git checkout -b main
	git pull origin main
	```

	2. 🔍 Choose the task you want to work on (Task 1, Task 2, or both).

	3. 📖 Follow the instructions in the respective README files:
	- [Task 1 README](./Raw/Task_01/README.MD)
	- [Task 2 README](./Raw/Task_02/README.MD)

	4. 📦 Install the required dependencies for each task.

	5. 🚀 Start developing your segmentation algorithms!

	## 📚 Citation

	If you use the PENGWIN datasets or challenge in your research, please cite the following:

	For Task 1:
	```bibtex
	@dataset{sang_yudi_2024_10927452,
	author = {Sang, Yudi and
	Liu, Yanzhen and
	Yibulayimu, Sutuke and
	Zhu, Gang and
	Wang, Yu and
	Killeen, Benjamin and
	Liu, Mingxu and
	Ku, Ping-Cheng and
	Armand, Mehran and
	Unberath, Mathias and
	Wu, Xinbao and
	Zhao, Chunpeng},
	title = {{PENGWIN Task 1: Pelvic Fracture Segmentation on
	CT}},
	month = apr,
	year = 2024,
	publisher = {Zenodo},
	version = {v1},
	doi = {10.5281/zenodo.10927452},
	url = {https://doi.org/10.5281/zenodo.10927452}
	}
	```

	For Task 2:
	```bibtex
	@dataset{killeen_benjamin_2024_10913196,
	author = {Killeen, Benjamin and
	Liu, Mingxu and
	Ku, Ping-Cheng and
	Yudi, Sang and
	Liu, Yanzhen and
	Yibulayimu, Sutuke and
	Zhu, Gang and
	Wu, Xinbao and
	Zhao, Chunpeng and
	Wang, Yu and
	Armand, Mehran and
	Unberath, Mathias},
	title = {{PENGWIN Task 2: Pelvic Fragment Segmentation on
	Synthetic X-ray Images}},
	month = apr,
	year = 2024,
	publisher = {Zenodo},
	version = {1.0.0},
	doi = {10.5281/zenodo.10913196},
	url = {https://doi.org/10.5281/zenodo.10913196}
	}
	```

	## 🔗 Additional Information

	For more details about the PENGWIN challenge, please visit the [official challenge webpage](https://grand-challenge.org).

	## 📄 License

	The PENGWIN datasets are distributed under the Creative Commons Attribution 4.0 International License.

	---

	## 👤 About me

	<div align="center">

	[![Owner](https://img.shields.io/badge/Owner-@mtoan65-blue?style=for-the-badge&logo=github)](https://github.com/mtoan65)
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	</div>