metadata

license: cc-by-nc-4.0
task_categories:
  - image-feature-extraction
language:
  - en
tags:
  - medical
  - image
  - biometry
  - biometrics
  - measurement
  - x-ray
  - cephalogram
  - head
  - neck
pretty_name: ceph-biometrics-400
size_categories:
  - n<1K

About

This is a modified version of data for the paper: Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms

Dataset Summary:

400 head and neck X-ray scans and 19 landmarks for each image

What's new?

We saved the original 2D .bmp images into pseudo 3D .nii.gz files in a manner that the original 2D sagittal slices can be extracted from the 3D NIfTI files correctly assuming the standard RAS+ orientation of .nii.gz files. A pseudo voxel size [0.1, 0.1, 0.1] is set in the NIfTI header, according to the data description in the paper: "The image resolution was 1935 × 2400 pixels with a pixel spacing of 0.1 mm."
We used the landmark annotations from the folder 400_senior in the original dataset.
We changed the landmarks coordinates to 3D, making it consistent with the new 3D NIfTI files.
Figures of image and landmarks are added for visual inspection.
Images (.nii.gz files), landmarks (.json files) and figures (.png files) are saved in Images, Landmarks, and Landmarks-fig folders.

Changelog 🔥

[8 May, 2025] Update the JSON files in Landmarks.zip to use 0-based slice indices. ‼️
[6 Mar, 2025] Update landmark coordinates to 0-based indices. ‼️
[3 Mar, 2025] Update the data structure of JSON files within Landmarks.zip. Landmarks coordinates remain unchanged.
[1 Mar, 2025]
- Update Landmarks.zip: correct the coordinates in JSON files. It's recommended to redownload all compressed files.
- Add a data preparation script get_dataset.py.
- Add data usage agreement.

Data Usage Agreement

By using the dataset, you agree to the terms as follow.

You must cite the paper: Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms
You must refer to the source of this dataset in any publication: https://huggingface.co/datasets/YongchengYAO/Ceph-Biometrics-400

Download from Huggingface

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

# python
from huggingface_hub import snapshot_download
snapshot_download(repo_id="YongchengYAO/Ceph-Biometrics-400", repo_type='dataset', local_dir="/your/local/folder")

Landmarks Labels

landmarks_map = {
    "P1": "sella",
    "P2": "nasion",
    "P3": "orbitale",
    "P4": "porion",
    "P5": "subspinale",
    "P6": "supramentale",
    "P7": "pogonion",
    "P8": "menton",
    "P9": "gnathion",
    "P10": "gonion",
    "P11": "incision inferius",
    "P12": "incision superius",
    "P13": "upper lip",
    "P14": "lower lip",
    "P15": "subnasale",
    "P16": "soft tissue pogonion",
    "P17": "posterior nasal spine",
    "P18": "anterior nasal spine",
    "P19": "articulare",
}

From Raw Data

You can replicate the data processing step by running the script:

python get_dataset.py -d <datasets_folder> -n Ceph-Biometrics-400

License

This dataset is released under the CC BY-NC 4.0 license.