22 citations · 53 across the 15 of their papers we have counts for
6 papers · 1 filter
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction
Chen Qin, Jo Schlemper, Jose Caballero +3
Accelerating the data acquisition of dynamic magnetic resonance imaging (MRI) leads to a challenging ill-posed inverse problem, which has received great interest from both the sign…
Extended Phase Graph formalism for systems with Magnetization Transfer and Chemical Exchange
Shaihan J. Malik, Rui P. A. G. Teixeira, Joseph V. Hajnal
An Extended Phase Graph framework for modelling systems with exchange or magnetization transfer (MT) is proposed. The framework, referred to as EPG-X, models coupled two-compartmen…
3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images
Benjamin Hou, Bishesh Khanal, Amir Alansary +7
Limited capture range, and the requirement to provide high quality initialization for optimization-based 2D/3D image registration methods, can significantly degrade the performance…
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction
Jo Schlemper, Jose Caballero, Joseph V. Hajnal +2
Inspired by recent advances in deep learning, we propose a framework for reconstructing dynamic sequences of 2D cardiac magnetic resonance (MR) images from undersampled data using…
Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion
Benjamin Hou, Amir Alansary, Steven McDonagh +6
This paper aims to solve a fundamental problem in intensity-based 2D/3D registration, which concerns the limited capture range and need for very good initialization of state-of-the…
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction
Jo Schlemper, Jose Caballero, Joseph V. Hajnal +2
The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from under…