output
20172024
most citedDeep learning cardiac motion analysis for human survival prediction

234 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2018Show all

5 papers · 1 filter

cs.LG2018★ 234 cited

Deep learning cardiac motion analysis for human survival prediction

Ghalib A. Bello, Timothy J. W. Dawes, Jinming Duan +8

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems require…

cs.CV2018

A Comprehensive Approach for Learning-based Fully-Automated Inter-slice Motion Correction for Short-Axis Cine Cardiac MR Image Stacks

Giacomo Tarroni, Ozan Oktay, Matthew Sinclair +7

In the clinical routine, short axis (SA) cine cardiac MR (CMR) image stacks are acquired during multiple subsequent breath-holds. If the patient cannot consistently hold the breath…

cs.CV2018

Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension

Jinming Duan, Jo Schlemper, Wenjia Bai +6

In this paper we introduce a novel and accurate optimisation method for segmentation of cardiac MR (CMR) images in patients with pulmonary hypertension (PH). The proposed method ex…

cs.CV2018

Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling

Carlo Biffi, Ozan Oktay, Giacomo Tarroni +9

Alterations in the geometry and function of the heart define well-established causes of cardiovascular disease. However, current approaches to the diagnosis of cardiovascular disea…

cs.CV2018★ 68 cited

Learning-Based Quality Control for Cardiac MR Images

Giacomo Tarroni, Ozan Oktay, Wenjia Bai +9

The effectiveness of a cardiovascular magnetic resonance (CMR) scan depends on the ability of the operator to correctly tune the acquisition parameters to the subject being scanned…