Early diagnosis and regular monitoring of osteoporosis is key to prevent further deterioration and fractures in osteoporosis patients. Dual-energy X-ray Absorptiometry (DXA), despite being a gold standard for diagnosing osteoporosis, is not routinely ordered due to limited availability of DXA machine, especially in developing countries. As a result, orthopedists often lack DXA results at the time of examination. This study aims to develop an automated AI system to predict osteoporosis based on a plain x-ray scan of patient’s femur and demographic data, such as age, height and weight. The system first performs instance segmentation on the X-ray scan to locate femur, followed by image processing techniques to measure the inner and outer diameter of the femur, and then compute cortical thickness index (CTI). The CTI value, together with patient’s demographic data, is incorporated into a classification model to predict if the patient is suffering from osteoporosis. We found that the CTI calculated by the AI system is comparable to the manually calculated CTI. The AI system can predict at an accuracy of 85.3% using CTI and patient data.
KEYWORDS: Blood, 3D metrology, Image segmentation, 3D applications, Surgery, Image processing, Calibration, Brain, Information operations, 3D image processing
ICH is a type of stroke caused by internal bleed of the brain. Accurate and fast measurement of the blood clot volume is important for neuro surgeon to make an informed decision if the patient need surgery or not. In this paper, we present a mobile application “ICH 3D”, which is able to measure blood clot volume on-site using a smart phone with improved accuracy and within a minute.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.