Aariz Cephalometric Dataset

<b>Abstract</b>We proposed a new state-of-the-art dataset to facilitate the development of robust AI solutions for quantitative morphometric analysis. The dataset includes 1000 lateral cephalometric radiographs (LCRs) obtained from 7 different radiographic imaging devices with varying resolutions, making it the most diverse and comprehensive cephalometric dataset to date. The clinical experts of our team meticulously annotated each radiograph with 29 cephalometric landmarks, including the most significant soft tissue landmarks ever marked in any publicly available dataset. Additionally, our experts also labelled the cervical vertebral maturation (CVM) stage of the patient in a radiograph, making this dataset the first standard resource for CVM classification.<b>Citation</b>If you use this dataset in your research, please consider citing our papers:Khalid, M. A., Zulfiqar, K., Bashir, U., Shaheen, A., Iqbal, R., Rizwan, Z., Rizwan, G., &amp; Fraz, M. M. <b><i>A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification</i></b>. <i>Scientific Data </i><b>12</b>, 1336 (2025). https://doi.org/10.1038/s41597-025-05542-3Khalid, M. A., Zulfiqar, K., Bashir, U., Shaheen, A., Iqbal, R., Rizwan, Z., Rizwan, G., &amp; Fraz, M. M. (2022). <b><i>CEPHA29: Automatic Cephalometric Landmark Detection Challenge 2023</i></b>. arXiv preprint arXiv:2212.04808.<br>