Computer Vision News Computer Vision News 28 Congrats, Doctor Szymon! A promising application of deep learning in the medical field is prenatal care. This vital aspect of healthcare is provided to pregnant women to prevent complications and ensure the well-being of both mother and baby before, during, and after birth. Prenatal care includes regular check-ups with a healthcare provider to monitor the mother's health and the fetus's growth and development. In his PhD thesis, Szymon proposed novel deep learning-based methods to improve the health and wellbeing of mothers and fetuses during pregnancy and delivery. Specifically, he focused on developing an automated method for recognizing standard planes and measuring biometrics during routine fetal ultrasound exams. In this work, he compared the performance of deep learning-based methods against experienced clinicians, showing no significant difference between the deep learning-based method and human readers. Additionally, he designed a method for directly estimating fetal birth weight from ultrasound video scans, which has been enhanced by incorporating multimodal data. The training and testing were done on data acquired 24 hours before delivery. This method is crucial for Szymon Płotka completed his PhD in June. He conducted his research at the Quantitative Healthcare Analysis group at the Informatics Institute, Faculty of Science, University of Amsterdam, and the Sano Centre for Computational Medicine. His work was supervised by Clara I. Sánchez, Ivana Išgum, and Arkadiusz Sitek from Harvard Med School. Congrats, Doctor Szymon!
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