3 papers
cs.CV2026
Improved cystic hygroma detection from prenatal imaging using ultrasound-specific self-supervised representation learning
Youssef Megahed, Robin Ducharme, Inok Lee +4
Cystic hygroma is a high-risk prenatal ultrasound finding that portends high rates of chromosomal abnormalities, structural malformations, and adverse pregnancy outcomes. Automated…
eess.IV2025
Self-Supervised Ultrasound Representation Learning for Renal Anomaly Prediction in Prenatal Imaging
Youssef Megahed, Inok Lee, Robin Ducharme +4
Prenatal ultrasound is the cornerstone for detecting congenital anomalies of the kidneys and urinary tract, but diagnosis is limited by operator dependence and suboptimal imaging c…
eess.IV2025
Deep Learning Analysis of Prenatal Ultrasound for Identification of Ventriculomegaly
Youssef Megahed, Inok Lee, Robin Ducharme +7
The proposed study aimed to develop a deep learning model capable of detecting ventriculomegaly on prenatal ultrasound images. Ventriculomegaly is a prenatal condition characterize…