YongchengYAO/OAIZIB-CM

Source	link
Google Drive	here
Huggingface	here

About

This is the official release of OAIZIB-CM dataset

• OAIZIB-CM is based on the OAIZIB dataset
  • OAIZIB paper: Automated Segmentation of Knee Bone and Cartilage combining Statistical Shape Knowledge and Convolutional Neural Networks: Data from the Osteoarthritis Initiative
• Tibial cartilage is split into medial and lateral tibial cartilages in segmentation masks.
• It is compulsory to cite these papers if you use the dataset
  • CartiMorph: A framework for automated knee articular cartilage morphometrics
  • Quantifying Knee Cartilage Shape and Lesion: From Image to Metrics

Changelog 🔥

• [15 Feb, 2025] Update file imagesTs/oaizib_454_0000.nii.gz
• [14 Feb, 2025] Identify corrupted files: case 454

Files

Images & Labels

• imagesTr: training images (#404)
• labelsTr: training segmentation masks (#404)
• imagesTs: testing images (#103)
• labelsTs: testing segmentation masks (#103)

Data Split & Info

• subInfo_train.xlsx: list of training data
• subInfo_test.xlsx: list of testing data
• kneeSideInfo.csv: a file containing knee side information, used in CartiMorph Toolbox

Download from Huggingface

#!/bin/bash
pip install huggingface-hub[cli]
huggingface-cli login --token $HF_TOKEN

# python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="YongchengYAO/OAIZIB-CM", repo_type='dataset', local_dir="/your/local/folder")

Segmentation Labels

labels_map = {
    "1": "Femur",
    "2": "Femoral Cartilage",
    "3": "Tibia",
    "4": "Medial Tibial Cartilage",
    "5": "Lateral Tibial Cartilage",
}

Papers

The dataset originates from these projects:

• CartiMorph: https://github.com/YongchengYAO/CartiMorph
• CartiMorph Toolbox:
  • https://github.com/YongchengYAO/CartiMorph-Toolbox
  • https://github.com/YongchengYAO/CMT-AMAI24paper

@article{YAO2024103035,
title = {CartiMorph: A framework for automated knee articular cartilage morphometrics},
journal = {Medical Image Analysis},
author = {Yongcheng Yao and Junru Zhong and Liping Zhang and Sheheryar Khan and Weitian Chen},
volume = {91},
pages = {103035},
year = {2024},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2023.103035}
}

@InProceedings{10.1007/978-3-031-82007-6_16,
author="Yao, Yongcheng
and Chen, Weitian",
editor="Wu, Shandong
and Shabestari, Behrouz
and Xing, Lei",
title="Quantifying Knee Cartilage Shape and Lesion: From Image to Metrics",
booktitle="Applications of Medical Artificial Intelligence",
year="2025",
publisher="Springer Nature Switzerland",
address="Cham",
pages="162--172"
}