89. Deep learning for computer-assisted perinatal care

Szymon Płotka – Health Informatics Team, Sano Centre for Computational Science, Krakow, PL

Abstract

Perinatal medicine is a branch of medicine that specializes in the care of women during pregnancy and childbirth, as well as the care of newborns.

In this seminar, I will demonstrate how deep learning-based methods can be useful to address limitations in perinatal care. In particular, I will talk about fetal birth weight estimation using ultrasound video scans and fetoscopic laser surgery to cure Twin-to-Twin Transfusion Syndrome (TTTS).

About the author

Szymon Płotka obtained his M.Sc. in Medical Informatics in 2019 from Warsaw University of Technology. His graduation focused on preterm birth prediction from transvaginal ultrasound images. Currently pursuing his Ph.D. in medical image analysis at Sano Centre for Computational Medicine and at the Quantitative Healthcare Analysis (qurAI) group at the Informatics Institute of the University of Amsterdam under the supervision of Clarisa Sánchez, Ivana Išgum, and Arkadiusz Sitek (Harvard Medical School). His main research interests are computer vision, machine learning, and deep learning-based methods applied for fetal ultrasound imaging, image-guided therapy and surgery.