3 citations · 10 across the 18 of their papers we have counts for
9 papers · 1 filter
Rendering Novel Views of MRI Using 3D Gaussian Splatting
Robin Y. Park, Mark C. Eid, Rhydian Windsor +4
The objective of this paper is to improve radiological gradings measured on MRIs of spines, by resampling scans so that the new view planes are better aligned with the target anato…
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…
UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumes
Mark C. Eid, Ana I. L. Namburete, João F. Henriques
Ultrasound imaging is widely used due to its safety, affordability, and real-time capabilities, but its 2D interpretation is highly operator-dependent, leading to variability and i…
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…
RapidVol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scans
Mark C. Eid, Pak-Hei Yeung, Madeleine K. Wyburd +2
Two-dimensional (2D) freehand ultrasonography is one of the most commonly used medical imaging modalities, particularly in obstetrics and gynaecology. However, it only captures 2D…
Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images
Pak-Hei Yeung, Moska Aliasi, Monique Haak +3
Two-dimensional (2D) freehand ultrasound is the mainstay in prenatal care and fetal growth monitoring. The task of matching corresponding cross-sectional planes in the 3D anatomy f…
ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representation
Pak-Hei Yeung, Linde Hesse, Moska Aliasi +4
The objective of this work is to achieve sensorless reconstruction of a 3D volume from a set of 2D freehand ultrasound images with deep implicit representation. In contrast to the…
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…