AI in medical imaging informatics: current challenges and future directions

AS Panayides, A Amini, ND Filipovic… - IEEE journal of …, 2020 - ieeexplore.ieee.org
This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …

Automated segmentation of tissues using CT and MRI: a systematic review

L Lenchik, L Heacock, AA Weaver, RD Boutin… - Academic radiology, 2019 - Elsevier
Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …

Automatic cardiac disease assessment on cine-MRI via time-series segmentation and domain specific features

F Isensee, PF Jaeger, PM Full, I Wolf… - Statistical Atlases and …, 2018 - Springer
Cardiac magnetic resonance imaging improves on diagnosis of cardiovascular diseases by
providing images at high spatiotemporal resolution. Manual evaluation of these time-series …

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 …

Machine learning of three-dimensional right ventricular motion enables outcome prediction in pulmonary hypertension: a cardiac MR imaging study

TJW Dawes, A de Marvao, W Shi, T Fletcher… - Radiology, 2017 - pubs.rsna.org
Purpose To determine if patient survival and mechanisms of right ventricular failure in
pulmonary hypertension could be predicted by using supervised machine learning of three …

Improving the generalizability of convolutional neural network-based segmentation on CMR images

C Chen, W Bai, RH Davies, AN Bhuva… - Frontiers in …, 2020 - frontiersin.org
Background: Convolutional neural network (CNN) based segmentation methods provide an
efficient and automated way for clinicians to assess the structure and function of the heart in …

Quantification of LV function and mass by cardiovascular magnetic resonance: multi-center variability and consensus contours

A Suinesiaputra, DA Bluemke, BR Cowan… - Journal of …, 2015 - Springer
Background High reproducibility of LV mass and volume measurement from cine
cardiovascular magnetic resonance (CMR) has been shown within single centers. However …

MinION™ nanopore sequencing of environmental metagenomes: a synthetic approach

BL Brown, M Watson, SS Minot, MC Rivera… - …, 2017 - academic.oup.com
Background Environmental metagenomic analysis is typically accomplished by assigning
taxonomy and/or function from whole genome sequencing or 16S amplicon sequences …

A bi-ventricular cardiac atlas built from 1000+ high resolution MR images of healthy subjects and an analysis of shape and motion

W Bai, W Shi, A de Marvao, TJW Dawes… - Medical image …, 2015 - Elsevier
Atlases encode valuable anatomical and functional information from a population. In this
work, a bi-ventricular cardiac atlas was built from a unique data set, which consists of high …

Radiomics signatures of cardiovascular risk factors in cardiac MRI: results from the UK biobank

I Cetin, Z Raisi-Estabragh, SE Petersen… - Frontiers in …, 2020 - frontiersin.org
Cardiovascular magnetic resonance (CMR) radiomics is a novel technique for advanced
cardiac image phenotyping by analyzing multiple quantifiers of shape and tissue texture. In …