9 papers
Benchmarking Self-Supervised Models for Cardiac Ultrasound View Classification
Youssef Megahed, Salma I. Megahed, Robin Ducharme +4
Reliable interpretation of cardiac ultrasound images is essential for accurate clinical diagnosis and assessment. Self-supervised learning has shown promise in medical imaging by l…
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…
Automated Classification of First-Trimester Fetal Heart Views Using Ultrasound-Specific Self-Supervised Learning
Youssef Megahed, Aylin Erman, Robin Ducharme +3
Congenital heart disease remains the most common congenital anomaly and a leading cause of neonatal morbidity and mortality. Although first-trimester fetal echocardiography offers…
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…
Automated Histopathologic Assessment of Hirschsprung Disease Using a Multi-Stage Vision Transformer Framework
Youssef Megahed, Saleh Abou-Alwan, Anthony Fuller +3
Hirschsprung Disease is characterized by the absence of ganglion cells in the myenteric plexus. Therefore, the correct identification of ganglion cells is crucial for diagnosing Hi…
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…
USF-MAE: Ultrasound Self-Supervised Foundation Model with Masked Autoencoding
Youssef Megahed, Robin Ducharme, Aylin Erman +3
Ultrasound imaging is one of the most widely used diagnostic modalities, offering real-time, radiation-free assessment across diverse clinical domains. However, interpretation of u…
Knowledge-Driven Vision-Language Model for Plexus Detection in Hirschsprung's Disease
Youssef Megahed, Atallah Madi, Dina El Demellawy +1
Hirschsprung's disease is defined as the congenital absence of ganglion cells in some segment(s) of the colon. The muscle cannot make coordinated movements to propel stool in that…
Segmentation of Muscularis Propria in Colon Histopathology Images Using Vision Transformers for Hirschsprung's Disease
Youssef Megahed, Anthony Fuller, Saleh Abou-Alwan +2
Hirschsprung's disease (HD) is a congenital birth defect diagnosed by identifying the lack of ganglion cells within the colon's muscularis propria, specifically within the myenteri…