activity
20172020
most citedImproving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study

7 citations · 8 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV20207 cited

Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study

Coen de Vente, Luuk H. Boulogne, Kiran Vaidhya Venkadesh +5

Amidst the ongoing pandemic, several studies have shown that COVID-19 classification and grading using computed tomography (CT) images can be automated with convolutional neural ne…

eess.IV2020

Random smooth gray value transformations for cross modality learning with gray value invariant networks

Nikolas Lessmann, Bram van Ginneken

Random transformations are commonly used for augmentation of the training data with the goal of reducing the uniformity of the training samples. These transformations normally aim…

eess.IV2019

Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network

Nikolas Lessmann, Jelmer M. Wolterink, Majd Zreik +3

Thin-plate splines can be used for interpolation of image values, but can also be used to represent a smooth surface, such as the boundary between two structures. We present a meth…

eess.IV2019

Automatic brain tissue segmentation in fetal MRI using convolutional neural networks

N. Khalili, N. Lessmann, E. Turk +6

MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in fetal MRI is segment…

cs.CV20171 cited

Direct and Real-Time Cardiovascular Risk Prediction

Bob D. de Vos, Nikolas Lessmann, Pim A. de Jong +2

Coronary artery calcium (CAC) burden quantified in low-dose chest CT is a predictor of cardiovascular events. We propose an automatic method for CAC quantification, circumventing i…