Ensemble of expert deep neural networks for spatio‐temporal denoising of contrast‐enhanced MRI sequences

By Ariel Benou, R. Veksler, A. Friedman, Tammy Riklin-Raviv. 2017

78 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Arvid Lundervold

In Radiology, Nuclear Medicine and Imaging

1. Arvid Lundervold
2. Florian Tramèr
3. Dan Boneh

Citations in the corpus

• An overview of deep learning in medical imaging focusing on MRI (2018, methodology): “[180] addressed spatiotemporal denoising of dynamic contrast-enhanced MRI of the brain with bolus injection of contrast agent (CA), proposing a novel approach using ensembles of deep neural networks for noise reduction.”