39 citations · 51 across the 9 of their papers we have counts for
5 papers · 1 filter
Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment
Paraskevas Pegios, Manxi Lin, Nina Weng +6
Obstetric ultrasound image quality is crucial for accurate diagnosis and monitoring of fetal health. However, acquiring high-quality standard planes is difficult, influenced by the…
Shortcut Learning in Medical Image Segmentation
Manxi Lin, Nina Weng, Kamil Mikolaj +5
Shortcut learning is a phenomenon where machine learning models prioritize learning simple, potentially misleading cues from data that do not generalize well beyond the training se…
An Automatic Guidance and Quality Assessment System for Doppler Imaging of Umbilical Artery
Chun Kit Wong, Manxi Lin, Alberto Raheli +5
Examination of the umbilical artery with Doppler ultrasonography is performed to investigate blood supply to the fetus through the umbilical cord, which is vital for the monitoring…
Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries
Carla Sendra-Balcells, Víctor M. Campello, Jordina Torrents-Barrena +17
Most artificial intelligence (AI) research have concentrated in high-income countries, where imaging data, IT infrastructures and clinical expertise are plentiful. However, slower…
DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentation
Manxi Lin, Zahra Bashir, Martin Grønnebæk Tolsgaard +2
Curvilinear structure segmentation is important in medical imaging, quantifying structures such as vessels, airways, neurons, or organ boundaries in 2D slices. Segmentation via pix…