49 citations · 58 across the 6 of their papers we have counts for
6 papers
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…
Explainable fetal ultrasound quality assessment with progressive concept bottleneck models
Manxi Lin, Aasa Feragen, Kamil Mikolaj +3
The quality of fetal ultrasound screening scans directly influences the precision of biometric measurements. However, acquiring high-quality scans is labor-intensive and highly rel…
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…
Was that so hard? Estimating human classification difficulty
Morten Rieger Hannemose, Josefine Vilsbøll Sundgaard, Niels Kvorning Ternov +2
When doctors are trained to diagnose a specific disease, they learn faster when presented with cases in order of increasing difficulty. This creates the need for automatically esti…
Multi-modal data generation with a deep metric variational autoencoder
Josefine Vilsbøll Sundgaard, Morten Rieger Hannemose, Søren Laugesen +6
We present a deep metric variational autoencoder for multi-modal data generation. The variational autoencoder employs triplet loss in the latent space, which allows for conditional…
Complex-valued neural networks for machine learning on non-stationary physical data
Jesper Sören Dramsch, Mikael Lüthje, Anders Nymark Christensen
Deep learning has become an area of interest in most scientific areas, including physical sciences. Modern networks apply real-valued transformations on the data. Particularly, con…