1 citations · 2 across the 4 of their papers we have counts for
4 papers
Model-based Dynamic 3D MRI Reconstructions using Neural Fields and Tensor Product Expansions
Ray Sheombarsing, Max van Riel, David Heesterbeek +2
Conventional MRI reconstruction methods treat images and coil sensitivities as discrete objects, leading to high memory demands and limited structural awareness that hamper effecti…
Kandinsky Conformal Prediction: Efficient Calibration of Image Segmentation Algorithms
Joren Brunekreef, Eric Marcus, Ray Sheombarsing +2
Image segmentation algorithms can be understood as a collection of pixel classifiers, for which the outcomes of nearby pixels are correlated. Classifier models can be calibrated us…
Constrained Empirical Risk Minimization: Theory and Practice
Eric Marcus, Ray Sheombarsing, Jan-Jakob Sonke +1
Deep Neural Networks (DNNs) are widely used for their ability to effectively approximate large classes of functions. This flexibility, however, makes the strict enforcement of cons…
Subpixel object segmentation using wavelets and multi resolution analysis
Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke +1
We propose a novel deep learning framework for fast prediction of boundaries of two-dimensional simply connected domains using wavelets and Multi Resolution Analysis (MRA). The bou…