Aris Papageorghiou

A comprehensive scoping review on machine learning-based fetal echocardiography analysis. Computers in Biology and Medicine, 186, 109666.https://doi.org/10.1016/j.compbiomed.2025.109666

A Deep Learning Framework for Fetal Heart Tracking in Ultrasound Videos: Toward Enhanced Congenital Heart Defects Detection. In International Conference on Functional Imaging and Modeling of the Heart (pp. 219-230). Cham: Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-94562-5_20

Artificial intelligence-enabled prenatal ultrasound for the detection of fetal cardiac abnormalities: a systematic review and meta-analysis. eClinicalMedicine.https://doi.org/10.1016/j.eclinm.2025.103250

CNSeg-GAN: A Lightweight Generative Adversarial Network For Segmentation of CRL and NT From First-Trimester Fetal Ultrasound. In 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) (pp. 1-4). IEEE.

COMFormer: Classification of Maternal-Fetal and Brain Anatomy using a Residual Cross-Covariance Attention Guided Transformer in Ultrasound. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

Detection of fetal congenital heart defects on three-vessel view ultrasound videos. WFUMB Ultrasound Open, 100075. https://doi.org/10.1016/j.wfumbo.2024.100075

Dual Conditioned Diffusion Models for Out-of-Distribution Detection: Application to Fetal Ultrasound Videos. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 216-226). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43907-0_21

HarmonicEchoNet: Leveraging harmonic convolutions for automated standard plane detection in fetal heart ultrasound videos. Medical Image Analysis, https://doi.org/10.1016/j.media.2025.103758

Machine learning-based method for the detection of dextrocardia in ultrasound video clips. Computer Methods and Programs in Biomedicine, 109023.https://doi.org/10.1016/j.cmpb.2025.109023

MCAT: Visual Query-Based Localization of Standard Anatomical Clips in Fetal Ultrasound Videos Using Multi-Tier Class-Aware Token Transformer. In Proceedings of the AAAI Conference on Artificial Intelligence, 39(27), 28267-28275. https://doi.org/10.1609/aaai.v39i27.35047

Self-supervised Learning of Echocardiographic Video Representations via Online Cluster Distillation. [Advances in Neural Information Processing Systems, 38, 61229-61254.]

Skill, or Style? Classification of Fetal Sonography Eye-Tracking Data. In Annual Conference on Neural Information Processing Systems (pp. 184-198). PMLR.