Advisor:

Rudy Gleason, Ph.D.                   Mechanical Engineering, Georgia Tech

Committee:

Brandon Dixon, Ph.D.                  Mechanical Engineering, Georgia Tech

Wilbur Lam, Ph.D.                        Biomedical Engineering, Georgia Tech

May Wang, Ph.D.                         Biomedical Engineering, Georgia Tech

Mike Weiler, Ph.D.                      LymphaTech, Inc.

Real-time risk-assessment of Cephalopelvic Disproportion (CPD) in pregnant women using longitudinal shape modeling of 3D scans.

Cephalopelvic disproportion (CPD) is a mismatch in the size of the maternal pelvis and the fetus, which often leads to obstructed labor. Most cases of CPD require C-section for successful delivery and in low resource settings like Ethiopia, there is a lack of adequate facilities with the infrastructure or expertise to perform a C-section. Currently, obstructed labor is known to account for 11 – 22% of maternal deaths in Ethiopia. Early assessment of the risk of CPD would enable women in these settings to access the proper healthcare services and improve the overall maternal health. This thesis aims to develop a point-of-care tool that would use longitudinal shape modeling to analyze, in real-time, 3D scans of pregnant women and assess the risk of CPD-related obstructed labor at the earliest possible stages of gestation. The longitudinal shape model would be trained on 3D scans of pregnant women across different periods of gestation and would be optimized to run on devices with low computational power. The developed tool is envisioned to be used by nurses and midwife personnel as part of routine antenatal care in low-resource settings.