Computational anatomy for multi-organ analysis in medical imaging: A review

JJ Cerrolaza, ML Picazo, L Humbert, Y Sato… - Medical image …, 2019 - Elsevier
The medical image analysis field has traditionally been focused on the development of
organ-, and disease-specific methods. Recently, the interest in the development of more …

Fully automated, quality-controlled cardiac analysis from CMR: validation and large-scale application to characterize cardiac function

B Ruijsink, E Puyol-Antón, I Oksuz, M Sinclair… - Cardiovascular …, 2020 - jacc.org
Objectives This study sought to develop a fully automated framework for cardiac function
analysis from cardiac magnetic resonance (CMR), including comprehensive quality control …

Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control

AG Roy, S Conjeti, N Navab, C Wachinger… - NeuroImage, 2019 - Elsevier
Abstract We introduce Bayesian QuickNAT for the automated quality control of whole-brain
segmentation on MRI T1 scans. Next to the Bayesian fully convolutional neural network, we …

[HTML][HTML] Deep neural network ensemble for on-the-fly quality control-driven segmentation of cardiac MRI T1 mapping

E Hann, IA Popescu, Q Zhang, RA Gonzales… - Medical image …, 2021 - Elsevier
Recent developments in artificial intelligence have generated increasing interest to deploy
automated image analysis for diagnostic imaging and large-scale clinical applications …

[HTML][HTML] Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning

I Oksuz, B Ruijsink, E Puyol-Antón, JR Clough… - Medical image …, 2019 - Elsevier
Good quality of medical images is a prerequisite for the success of subsequent image
analysis pipelines. Quality assessment of medical images is therefore an essential activity …

Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study

R Robinson, VV Valindria, W Bai, O Oktay… - Journal of …, 2019 - Springer
Background The trend towards large-scale studies including population imaging poses new
challenges in terms of quality control (QC). This is a particular issue when automatic …

Real-time prediction of segmentation quality

R Robinson, O Oktay, W Bai, VV Valindria… - … Image Computing and …, 2018 - Springer
Recent advances in deep learning based image segmentation methods have enabled real-
time performance with human-level accuracy. However, occasionally even the best method …

Large-scale quality control of cardiac imaging in population studies: application to UK Biobank

G Tarroni, W Bai, O Oktay, A Schuh, H Suzuki… - Scientific reports, 2020 - nature.com
In large population studies such as the UK Biobank (UKBB), quality control of the acquired
images by visual assessment is unfeasible. In this paper, we apply a recently developed …

Quality control-driven image segmentation towards reliable automatic image analysis in large-scale cardiovascular magnetic resonance aortic cine imaging

E Hann, L Biasiolli, Q Zhang, IA Popescu… - … Image Computing and …, 2019 - Springer
Recent progress in fully-automated image segmentation has enabled efficient extraction of
clinical parameters in large-scale clinical imaging studies, reducing laborious manual …

Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data

L Biasiolli, E Hann, E Lukaschuk, V Carapella… - PLoS …, 2019 - journals.plos.org
Introduction Aortic distensibility can be calculated using semi-automated methods to
segment the aortic lumen on cine CMR (Cardiovascular Magnetic Resonance) images …