1 citations · 3 across the 11 of their papers we have counts for
5 papers · 1 filter
Automated Fetal Biometry Assessment with Deep Ensembles using Sparse-Sampling of 2D Intrapartum Ultrasound Images
Jayroop Ramesh, Valentin Bacher, Mark C. Eid +6
The International Society of Ultrasound advocates Intrapartum Ultrasound (US) Imaging in Obstetrics and Gynecology (ISUOG) to monitor labour progression through changes in fetal he…
Automated quality assessment using appearance-based simulations and hippocampus segmentation on low-field paediatric brain MR images
Vaanathi Sundaresan, Nicola K Dinsdale
Understanding the structural growth of paediatric brains is a key step in the identification of various neuro-developmental disorders. However, our knowledge is limited by many fac…
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos
Jayroop Ramesh, Nicola K Dinsdale, the INTERGROWTH-21st Consortium +2
Accurately localizing two-dimensional (2D) ultrasound (US) fetal brain images in the 3D brain, using minimal computational resources, is an important task for automated US analysis…
TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations
Madeleine K. Wyburd, Nicola K. Dinsdale, Ana I. L. Namburete +1
Accurate topology is key when performing meaningful anatomical segmentations, however, it is often overlooked in traditional deep learning methods. In this work we propose TEDS-Net…
Challenges for machine learning in clinical translation of big data imaging studies
Nicola K Dinsdale, Emma Bluemke, Vaanathi Sundaresan +3
The combination of deep learning image analysis methods and large-scale imaging datasets offers many opportunities to imaging neuroscience and epidemiology. However, despite the su…