14 citations · 14 across the 2 of their papers we have counts for
3 papers
A Divide-and-Conquer Approach towards Understanding Deep Networks
Weilin Fu, Katharina Breininger, Roman Schaffert +2
Deep neural networks have achieved tremendous success in various fields including medical image segmentation. However, they have long been criticized for being a black-box, in that…
Metric-Driven Learning of Correspondence Weighting for 2-D/3-D Image Registration
Roman Schaffert, Jian Wang, Peter Fischer +2
Registration of pre-operative 3-D volumes to intra-operative 2-D X-ray images is important in minimally invasive medical procedures. Rigid registration can be performed by estimati…
Frangi-Net: A Neural Network Approach to Vessel Segmentation
Weilin Fu, Katharina Breininger, Tobias Würfl +3
In this paper, we reformulate the conventional 2-D Frangi vesselness measure into a pre-weighted neural network ("Frangi-Net"), and illustrate that the Frangi-Net is equivalent to…