3 citations · 10 across the 18 of their papers we have counts for
4 papers · 1 filter
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…
Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning
Pak-Hei Yeung, Ana I. L. Namburete, Weidi Xie
The objective of this work is to segment any arbitrary structures of interest (SOI) in 3D volumes by only annotating a single slice, (i.e. semi-automatic 3D segmentation). We show…