AIMC Topic: Cicatrix
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Improved Quantification of Myocardium Scar in Late Gadolinium Enhancement Images: Deep Learning Based Image Fusion Approach.
Journal of magnetic resonance imaging : JMRI
Feb 17, 2021
BACKGROUND: Quantification of myocardium scarring in late gadolinium enhanced (LGE) cardiac magnetic resonance imaging can be challenging due to low scar-to-background contrast and low image quality. To resolve ambiguous LGE regions, experienced read...
Robotic CSP Resection and Hysterotomy Repair.
Journal of minimally invasive gynecology
Nov 27, 2020
STUDY OBJECTIVE: To demonstrate a technique for the robot-assisted laparoscopic surgical management of cesarean section scar ectopic pregnancy (CSP) and hysterotomy repair.
Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification.
European radiology
Nov 21, 2020
OBJECTIVES: The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification.
Detecting myocardial scar using electrocardiogram data and deep neural networks.
Biological chemistry
Oct 2, 2020
Ischaemic heart disease is among the most frequent causes of death. Early detection of myocardial pathologies can increase the benefit of therapy and reduce the number of lethal cases. Presence of myocardial scar is an indicator for developing ischae...
Non-ischemic endocardial scar geometric remodeling toward topological machine learning.
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Jul 10, 2020
Scar tissues have been important factors in determining the progression of myocardial diseases and the development of adverse cardiac failure outcomes. Accurate segmentation of the scar tissues can be helpful to the clinicians for risk prediction and...
Atrial scar quantification via multi-scale CNN in the graph-cuts framework.
Medical image analysis
Nov 16, 2019
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the quantification and analysis of atrial scars can be challenging due to...
Three-dimensional Deep Convolutional Neural Networks for Automated Myocardial Scar Quantification in Hypertrophic Cardiomyopathy: A Multicenter Multivendor Study.
Radiology
Nov 12, 2019
Background Cardiac MRI late gadolinium enhancement (LGE) scar volume is an important marker for outcome prediction in patients with hypertrophic cardiomyopathy (HCM); however, its clinical application is hindered by a lack of measurement standardizat...
Image Interpretation, Computer-Assisted
Cardiomyopathy, Hypertrophic
Cicatrix
Myocardium
Heart
Child
Imaging, Three-Dimensional
Magnetic Resonance Imaging
Aged
Aged, 80 and over
Middle Aged
Neural Networks, Computer
Young Adult
Adult
Humans
Female
Adolescent
Retrospective Studies
Male
Reproducibility of Results
[Robot-assisted transaxillary thyroid surgery; 5 years later].
Nederlands tijdschrift voor geneeskunde
Mar 14, 2019
Five years ago, robot-assisted transaxillary thyroidectomy (RATT) was introduced in the Netherlands. The major advantage of this technique, when compared to the conventional approach, is the prevention of a potentially disfiguring scar in the neck. I...
Development and testing of a deep learning-based strategy for scar segmentation on CMR-LGE images.
Magma (New York, N.Y.)
Nov 20, 2018
OBJECTIVE: The aim of this paper is to investigate the use of fully convolutional neural networks (FCNNs) to segment scar tissue in the left ventricle from cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) images.
Automated Cardiac MR Scar Quantification in Hypertrophic Cardiomyopathy Using Deep Convolutional Neural Networks.
JACC. Cardiovascular imaging
Aug 15, 2018
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