133 citations · 493 across the 30 of their papers we have counts for
9 papers · 1 filter
Generalizing Deep Learning MRI Reconstruction across Different Domains
Cheng Ouyang, Jo Schlemper, Carlo Biffi +5
We look into the robustness of deep learning based MRI reconstruction when tested on unseen contrasts and organs. We then propose to generalize the network by training with large p…
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
Benjamin Hou, Nina Miolane, Bishesh Khanal +7
Pose estimation, i.e. predicting a 3D rigid transformation with respect to a fixed co-ordinate frame in, SE(3), is an omnipresent problem in medical image analysis with application…
Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks
Matthew Sinclair, Christian F. Baumgartner, Jacqueline Matthew +9
Measurement of head biometrics from fetal ultrasonography images is of key importance in monitoring the healthy development of fetuses. However, the accurate measurement of relevan…
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…
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…
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI
Amir Alansary, Bernhard Kainz, Martin Rajchl +8
In this paper we present a novel method for the correction of motion artifacts that are present in fetal Magnetic Resonance Imaging (MRI) scans of the whole uterus. Contrary to cur…