output
19942026
most citedQuantum Transport in Semiconductor Nanostructures

1.2k citations

Showing 2019Show all

7 papers · 1 filter

eess.SP2019★ 4 cited

Adaptive Ultrasound Beamforming using Deep Learning

Ben Luijten, Regev Cohen, Frederik J. de Bruijn +4

Biomedical imaging is unequivocally dependent on the ability to reconstruct interpretable and high-quality images from acquired sensor data. This reconstruction process is pivotal…

eess.IV2019★ 10 cited

Synthetic CT Generation from MRI Using Improved DualGAN

Denis Prokopenko, Joël Valentin Stadelmann, Heinrich Schulz +2

Synthetic CT image generation from MRI scan is necessary to create radiotherapy plans without the need of co-registered MRI and CT scans. The chosen baseline adversarial model with…

eess.IV2019★ 27 cited

Perceptual Image Anomaly Detection

Nina Tuluptceva, Bart Bakker, Irina Fedulova +1

We present a novel method for image anomaly detection, where algorithms that use samples drawn from some distribution of "normal" data, aim to detect out-of-distribution (abnormal)…

cs.CY2019★ 126 cited

Artificial Intelligence in Clinical Health Care Applications: Viewpoint

Michael van Hartskamp, Sergio Consoli, Wim Verhaegh +2

The idea of Artificial Intelligence (AI) has a long history. It turned out, however, that reaching intelligence at human levels is more complicated than originally anticipated. Cur…

eess.IV2019★ 23 cited

Hierarchical Bayesian myocardial perfusion quantification

Cian M. Scannell, Amedeo Chiribiri, Adriana D. M. Villa +2

Purpose: Tracer-kinetic models can be used for the quantitative assessment of contrast-enhanced MRI data. However, the model-fitting can produce unreliable results due to the limit…

cs.CV2019

Improving Catheter Segmentation & Localization in 3D Cardiac Ultrasound Using Direction-Fused FCN

Hongxu Yang, Caifeng Shan, Alexander F. Kolen +1

Fast and accurate catheter detection in cardiac catheterization using harmless 3D ultrasound (US) can improve the efficiency and outcome of the intervention. However, the low image…