AIMC Topic: Myocardium

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Temporally coherent cardiac motion tracking from cine MRI: Traditional registration method and modern CNN method.

Medical physics Jul 6, 2020
PURPOSE: Cardiac motion tracking enables quantitative evaluation of myocardial strain, which is clinically interesting in cardiovascular disease research. However, motion tracking is difficult to perform manually. In this paper, we aim to develop and...
Magnetic Resonance Imaging Myocardium Heart Magnetic Resonance Imaging, Cine Humans Neural Networks, Computer Algorithms
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Fast and accurate calculation of myocardial T and T values using deep learning Bloch equation simulations (DeepBLESS).

Magnetic resonance in medicine May 16, 2020
PURPOSE: To propose and evaluate a deep learning model for rapid and accurate calculation of myocardial T /T values based on a previously proposed Bloch equation simulation with slice profile correction (BLESSPC) method.
Myocardium Heart Phantoms, Imaging Reproducibility of Results Deep Learning Magnetic Resonance Imaging
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Cardiac MR segmentation based on sequence propagation by deep learning.

PloS one Apr 9, 2020
Accurate segmentation of myocardial in cardiac MRI (magnetic resonance image) is key to effective rapid diagnosis and quantitative pathology analysis. However, a low-quality CMR (cardiac magnetic resonance) image with a large amount of noise makes it...
Heart Ventricles Datasets as Topic Cardiac Imaging Techniques Magnetic Resonance Imaging Myocardium Heart Humans Neural Networks, Computer Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted
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An integrated deep learning framework for joint segmentation of blood pool and myocardium.

Medical image analysis Mar 5, 2020
Simultaneous and automatic segmentation of the blood pool and myocardium is an important precondition for early diagnosis and pre-operative planning in patients with complex congenital heart disease. However, due to the high diversity of cardiovascul...
Humans Magnetic Resonance Imaging Myocardium Deep Learning Imaging, Three-Dimensional
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Bioinspired Soft Robot with Incorporated Microelectrodes.

Journal of visualized experiments : JoVE Feb 28, 2020
Bioinspired soft robotic systems that mimic living organisms using engineered muscle tissue and biomaterials are revolutionizing the current biorobotics paradigm, especially in biomedical research. Recreating artificial life-like actuation dynamics i...
Robotics Myocardium Polyethylene Glycols Hydrogels Animals Rats Rats, Sprague-Dawley Microelectrodes Myocardial Contraction Myocytes, Cardiac Biocompatible Materials Tissue Engineering Biomimetics Tissue Scaffolds Nanotubes, Carbon
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Accuracy, uncertainty, and adaptability of automatic myocardial ASL segmentation using deep CNN.

Magnetic resonance in medicine Nov 14, 2019
PURPOSE: To apply deep convolution neural network to the segmentation task in myocardial arterial spin labeled perfusion imaging and to develop methods that measure uncertainty and that adapt the convolution neural network model to a specific false-p...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Magnetic Resonance Imaging Myocardium Uncertainty
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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...
Cardiomyopathy, Hypertrophic Myocardium Heart Image Interpretation, Computer-Assisted Imaging, Three-Dimensional Magnetic Resonance Imaging Cicatrix Aged, 80 and over Young Adult Female Adult Adolescent Reproducibility of Results Child Humans Aged Male Neural Networks, Computer Middle Aged Retrospective Studies
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Automatic myocardial segmentation in dynamic contrast enhanced perfusion MRI using Monte Carlo dropout in an encoder-decoder convolutional neural network.

Computer methods and programs in biomedicine Oct 22, 2019
BACKGROUND AND OBJECTIVE: Cardiac perfusion magnetic resonance imaging (MRI) with first pass dynamic contrast enhancement (DCE) is a useful tool to identify perfusion defects in myocardial tissues. Automatic segmentation of the myocardium can lead to...
Monte Carlo Method Magnetic Resonance Angiography Myocardium Humans Datasets as Topic Neural Networks, Computer Automation Contrast Media
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Machine learning in cardiovascular magnetic resonance: basic concepts and applications.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Oct 7, 2019
Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR where ML, and deep learning in particular, can assist clinicians and engineers in improvi...
Coronary Circulation Myocardial Perfusion Imaging Magnetic Resonance Imaging, Cine Myocardium Supervised Machine Learning Image Interpretation, Computer-Assisted Humans Diagnosis, Computer-Assisted Deep Learning Unsupervised Machine Learning Predictive Value of Tests Machine Learning Reproducibility of Results Cardiovascular Diseases
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A non-linear mathematical model using optical sensor to predict heart decellularization efficacy.

Scientific reports Aug 21, 2019
One of the main problems of the decellularization technique is the subjectivity of the final evaluation of its efficacy in individual organs. This problem can result in restricted cell repopulation reproducibility and worse responses to transplant ti...
Models, Theoretical Image Processing, Computer-Assisted Machine Learning Myocardium Rats, Wistar Animals Optical Imaging Rats Male
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