480 citations · 539 across the 8 of their papers we have counts for
8 papers
Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision
Patrick M. Jensen, Niels Jeppesen, Anders B. Dahl +1
Minimum cut/maximum flow (min-cut/max-flow) algorithms solve a variety of problems in computer vision and thus significant effort has been put into developing fast min-cut/max-flow…
Sparse-View Spectral CT Reconstruction Using Deep Learning
Wail Mustafa, Christian Kehl, Ulrik Lund Olsen +4
Spectral computed tomography (CT) is an emerging technology capable of providing high chemical specificity, which is crucial for many applications such as detecting threats in lugg…
Shape from Projections via Differentiable Forward Projector for Computed Tomography
Jakeoung Koo, Anders B. Dahl, J. Andreas Bærentzen +3
In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D…
Guiding 3D U-nets with signed distance fields for creating 3D models from images
Kristine Aavild Juhl, Rasmus Reinhold Paulsen, Anders Bjorholm Dahl +4
Morphological analysis of the left atrial appendage is an important tool to assess risk of ischemic stroke. Most deep learning approaches for 3D segmentation is guided by binary la…
Multi-Spectral Imaging via Computed Tomography (MUSIC) - Comparing Unsupervised Spectral Segmentations for Material Differentiation
Christian Kehl, Wail Mustafa, Jan Kehres +2
Multi-spectral computed tomography is an emerging technology for the non-destructive identification of object materials and the study of their physical properties. Applications of…
Content-based Propagation of User Markings for Interactive Segmentation of Patterned Images
Vedrana Andersen Dahl, Monica Jane Emerson, Camilla Himmelstrup Trinderup +1
Efficient and easy segmentation of images and volumes is of great practical importance. Segmentation problems that motivate our approach originate from microscopy imaging commonly…