Variation of 3D Camera Based Anthropometry for Prediction of Cephalopelvic Disproportion in Ethiopia
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Paljug, Elianna
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Abstract
Cephalopelvic disproportion (CPD) is a dangerous pregnancy complication that often leads to maternal and perinatal morbidity or mortality if a cesarean section is not performed. Although for most people in the United States, the cesarean section procedure is easily accessible, this is not the reality for many women throughout the world. In Ethiopia, where the cesarean section procedure is often not easily accessible, obstructed labor occurs in nearly 13% of pregnancies, with nearly 65% of these cases occurring because of CPD. Accurate and timely referral of pregnant women who are at high risk of CPD to referral hospitals where they can obtain a cesarean section has the potential to save lives at birth. The Gleason Lab has investigated the use of 3D-camera based anthropometry as a tool for CPD risk calculation through the development of an algorithm that obtains anthropometric measurements from 3D scans. The 3D Cameras studied are the Occipital Structure Sensor and the Microsoft Kinect sensor, which are cameras in research and commercial use worldwide. This work extends that research by conducting variability and longitudinal studies to evaluate the variation of the measurements obtained by this algorithm for the two 3D-camera based approaches of Structure and Kinect and compares their variation to measurements obtained by traditional anthropometry. Results found that the Structure approach often had similar variation or less variation than traditional anthropometry, and Kinect was often had similar variation or greater variation than traditional anthropometry. These results illustrate the robustness of the approach of using Structure 3D-camera based anthropometric measurements for the prediction of CPD and encourage further development of this approach for eventual use in Ethiopia.
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2021-08-02
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