@inproceedings{d0fb6ad4b3004b2fb831e23df724fb8f,
title = "Vertebra-Focused Landmark Detection for Scoliosis Assessment",
abstract = "Adolescent idiopathic scoliosis (AIS) is a lifetime disease that arises in children. Accurate estimation of Cobb angles of the scoliosis is essential for clinicians to make diagnosis and treatment decisions. The Cobb angles are measured according to the vertebrae landmarks. Existing regression-based methods for the vertebra landmark detection typically suffer from large dense mapping parameters and inaccurate landmark localization. The segmentation-based methods tend to predict connected or corrupted vertebra masks. In this paper, we propose a novel vertebra-focused landmark detection method. Our model first localizes the vertebra centers, based on which it then traces the four corner landmarks of the vertebra through the learned corner offset. In this way, our method is able to keep the order of the landmarks. The comparison results demonstrate the merits of our method in both Cobb angle measurement and landmark detection on low-contrast and ambiguous X-ray images. Code is available at: https://github.com/yijingru/Vertebra-Landmark-Detection.",
keywords = "Scoliosis, keypoint, landmark detection",
author = "Jingru Yi and Pengxiang Wu and Qiaoying Huang and Hui Qu and Metaxas, {Dimitris N.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 17th IEEE International Symposium on Biomedical Imaging, ISBI 2020 ; Conference date: 03-04-2020 Through 07-04-2020",
year = "2020",
month = apr,
doi = "10.1109/ISBI45749.2020.9098675",
language = "English (US)",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "736--740",
booktitle = "ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging",
address = "United States",
}