Artificial intelligence, machine learning, and cardiovascular disease

P Mathur, S Srivastava, X Xu… - Clinical Medicine …, 2020 - journals.sagepub.com
Artificial intelligence (AI)-based applications have found widespread applications in many
fields of science, technology, and medicine. The use of enhanced computing power of …

[HTML][HTML] Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future

F Yasmin, SMI Shah, A Naeem… - Reviews in …, 2021 - imrpress.com
Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as
Machine Learning, and its subtype Deep Learning. AI has incorporated itself in the field of …

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 …

Automated artery localization and vessel wall segmentation using tracklet refinement and polar conversion

L Chen, J Sun, G Canton, N Balu, DS Hippe… - IEEE …, 2020 - ieeexplore.ieee.org
Quantitative analysis of blood vessel wall structures is important to study atherosclerotic
diseases and assess cardiovascular event risks. To achieve this, accurate identification of …

[HTML][HTML] Ex vivo vessel wall thickness measurements of the human circle of Willis using 7T MRI

AA Harteveld, NP Denswil, W Van Hecke, HJ Kuijf… - Atherosclerosis, 2018 - Elsevier
Background and aims MRI can detect intracranial vessel wall thickening before any luminal
stenosis is present. Apart from representing a vessel wall lesion, wall thickening could also …

Domain adaptive and fully automated carotid artery atherosclerotic lesion detection using an artificial intelligence approach (LATTE) on 3D MRI

L Chen, H Zhao, H Jiang, N Balu… - Magnetic …, 2021 - Wiley Online Library
Purpose To develop and evaluate a domain adaptive and fully automated review workflow
(lesion assessment through tracklet evaluation, LATTE) for assessment of atherosclerotic …

Learning‐based automated segmentation of the carotid artery vessel wall in dual‐sequence MRI using subdivision surface fitting

S Gao, R van 't Klooster, PH Kitslaar… - Medical …, 2017 - Wiley Online Library
Purpose The quantification of vessel wall morphology and plaque burden requires vessel
segmentation, which is generally performed by manual delineations. The purpose of our …

Fully automated and robust analysis technique for popliteal artery vessel wall evaluation (FRAPPE) using neural network models from standardized knee MRI

L Chen, G Canton, W Liu, DS Hippe… - Magnetic resonance …, 2020 - Wiley Online Library
Purpose To develop a fully automated vessel wall (VW) analysis workflow (fully automated
and robust analysis technique for popliteal artery evaluation, FRAPPE) on the popliteal …

Automated cardiovascular segmentation in patients with congenital heart disease from 3D CMR scans: combining multi-atlases and level-sets

R Shahzad, S Gao, Q Tao, O Dzyubachyk… - … , and Analysis of Medical …, 2017 - Springer
This paper presents an automatic method that enables segmentation of the whole heart and
the great vessels from 3D MRI scans. The proposed method is built upon a multi-atlas-based …

Uncertainty quantification of the wall thickness and stiffness in an idealized dissected aorta

L Gheysen, L Maes, A Caenen, P Segers… - Journal of the …, 2024 - Elsevier
Personalized treatment informed by computational models has the potential to markedly
improve the outcome for patients with a type B aortic dissection. However, existing …