@inproceedings{b309dd8f085a44148440f3ca731c218a,
title = "Detecting vertebra landmarks from ultrasound image using single shot multibox detector",
abstract = "In the diagnosis of scoliosis, the position and geometric parameters of the vertebra or spine are important to doctors' diagnoses. Many imaging techniques such as X-ray and Magnetic Resonance Imaging (MRI) can be used for scoliosis detection. Ultrasound imaging (US) is a radiation-free and low-cost way on clinical application in contrast to other imaging techniques. Many methods on Ultrasound imaging were reported to assess the severity of scoliosis. In this paper, we employ Single Shot MutilBox Detector, an end-to-end object detection algorithm based on deep learning, on detecting the vertebra landmarks with ultrasound image. The automatic detection and location of vertebra landmarks is important basis for further analysis and diagnosis of scoliosis and contributes to development on computer aided diagnosis system. The preliminary experiment results on phantom show that our method is high accuracy and feasible in detecting vertebra landmarks.",
keywords = "Object detection, SSD, Ultrasound image, Vertebra landmarks",
author = "Qifeng Deng and Qinghua Huang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th International Conference on Systems and Informatics, ICSAI 2019 ; Conference date: 02-11-2019 Through 04-11-2019",
year = "2019",
month = nov,
doi = "10.1109/ICSAI48974.2019.9010161",
language = "英语",
series = "2019 6th International Conference on Systems and Informatics, ICSAI 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "757--761",
editor = "Wanqing Wu and Lipo Wang and Chunlei Ji and Niansheng Chen and Sun Qiang and Xiaoyong Song and Xin Wang",
booktitle = "2019 6th International Conference on Systems and Informatics, ICSAI 2019",
}