activity
20162023
most citedAttention U-Net: Learning Where to Look for the Pancreas

4.6k citations · 14.9k across the 210 of their papers we have counts for

collaborators
Showing 2017Show all

16 papers · 1 filter

cs.CV2017★ 29 cited

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…

cs.CV2017★ 74 cited

DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images

Nick Pawlowski, Sofia Ira Ktena, Matthew C. H. Lee +4

We present DLTK, a toolkit providing baseline implementations for efficient experimentation with deep learning methods on biomedical images. It builds on top of TensorFlow and its…

cs.CV2017★ 60 cited

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante +8

Deep learning approaches such as convolutional neural nets have consistently outperformed previous methods on challenging tasks such as dense, semantic segmentation. However, the v…

cs.CV2017★ 4 cited

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks

Wenjia Bai, Matthew Sinclair, Giacomo Tarroni +20

Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accura…

cs.CV2017

Is human face processing a feature- or pattern-based task? Evidence using a unified computational method driven by eye movements

Carlos E. Thomaz, Vagner Amaral, Gilson A. Giraldi +2

Research on human face processing using eye movements has provided evidence that we recognize face images successfully focusing our visual attention on a few inner facial regions,…

cs.CV2017★ 9 cited

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…