61 citations · 111 across the 22 of their papers we have counts for
24 papers
MERA: Multimodal and Multiscale Self-Explanatory Model with Considerably Reduced Annotation for Lung Nodule Diagnosis
Jiahao Lu, Chong Yin, Silvia Ingala +3
Lung cancer, a leading cause of cancer-related deaths globally, emphasises the importance of early detection for better patient outcomes. Pulmonary nodules, often early indicators…
Neural Kinematic Bases for Fluids
Yibo Liu, Zhixin Fang, Sune Darkner +4
We propose mesh-free fluid simulations that exploit a kinematic neural basis for velocity fields represented by an MLP. We design a set of losses that ensures that these neural bas…
Locally orderless networks
Jon Sporring, Peidi Xu, Jiahao Lu +2
We present Locally Orderless Networks (LON) and its theoretic foundation which links it to Convolutional Neural Networks (CNN), to Scale-space histograms, and measurement theory. T…
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…