61 citations · 111 across the 22 of their papers we have counts for
4 papers · 1 filter
Extremely weakly-supervised blood vessel segmentation with physiologically based synthesis and domain adaptation
Peidi Xu, Olga Sosnovtseva, Charlotte Mehlin Sørensen +2
Accurate analysis and modeling of renal functions require a precise segmentation of the renal blood vessels. Micro-CT scans provide image data at higher resolutions, making more sm…
Localise to segment: crop to improve organ at risk segmentation accuracy
Abraham George Smith, Denis Kutnár, Ivan Richter Vogelius +2
Increased organ at risk segmentation accuracy is required to reduce cost and complications for patients receiving radiotherapy treatment. Some deep learning methods for the segment…
Deep Learning-Assisted Localisation of Nanoparticles in synthetically generated two-photon microscopy images
Rasmus Netterstrøm, Nikolay Kutuzov, Sune Darkner +4
Tracking single molecules is instrumental for quantifying the transport of molecules and nanoparticles in biological samples, e.g., in brain drug delivery studies. Existing intensi…
A Hybrid Approach to Full-Scale Reconstruction of Renal Arterial Network
Peidi Xu, Niels-Henrik Holstein-Rathlou, Stinne Byrholdt Søgaard +5
The renal vasculature, acting as a resource distribution network, plays an important role in both the physiology and pathophysiology of the kidney. However, no imaging techniques a…