11 citations · 24 across the 9 of their papers we have counts for
9 papers
BugNIST -- a Large Volumetric Dataset for Object Detection under Domain Shift
Patrick Møller Jensen, Vedrana Andersen Dahl, Carsten Gundlach +3
Domain shift significantly influences the performance of deep learning algorithms, particularly for object detection within volumetric 3D images. Annotated training data is essenti…
Deep Active Latent Surfaces for Medical Geometries
Patrick M. Jensen, Udaranga Wickramasinghe, Anders B. Dahl +2
Shape priors have long been known to be effective when reconstructing 3D shapes from noisy or incomplete data. When using a deep-learning based shape representation, this often inv…
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…
Image-Based Alignment of 3D Scans
Dolores Messer, Jakob Wilm, Eythor R. Eiriksson +2
Full 3D scanning can efficiently be obtained using structured light scanning combined with a rotation stage. In this setting it is, however, necessary to reposition the object and…
A Physical Model for Microstructural Characterization and Segmentation of 3D Tomography Data
Elise Otterlei Brenne, Vedrana Andersen Dahl, Peter Stanley Jørgensen
We present a novel method for characterizing the microstructure of a material from volumetric datasets such as 3D image data from computed tomography (CT). The method is based on a…
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…
Dictionary-based Method for Vascular Segmentation for OCTA Images
Astrid M. E. Engberg, Vedrana A. Dahl, Anders B. Dahl
Optical coherence tomography angiography (OCTA) is an imaging technique that allows for non-invasive investigation of the microvasculature in the retina. OCTA uses laser light refl…
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…
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…