AIMC Topic: Heart Ventricles
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An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net).
Sensors (Basel, Switzerland)
Mar 8, 2022
Accurate segmentation of the myocardial scar may supply relevant advancements in predicting and controlling deadly ventricular arrhythmias in subjects with cardiovascular disease. In this paper, we propose the architecture of inclusion and classifica...
Fully automated intracardiac 4D flow MRI post-processing using deep learning for biventricular segmentation.
European radiology
Feb 17, 2022
OBJECTIVES: 4D flow MRI allows for a comprehensive assessment of intracardiac blood flow, useful for assessing cardiovascular diseases, but post-processing requires time-consuming ventricular segmentation throughout the cardiac cycle and is prone to ...
Improving robustness of automatic cardiac function quantification from cine magnetic resonance imaging using synthetic image data.
Scientific reports
Feb 14, 2022
Although having been the subject of intense research over the years, cardiac function quantification from MRI is still not a fully automatic process in the clinical practice. This is partly due to the shortage of training data covering all relevant c...
Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.
Circulation. Heart failure
Dec 24, 2021
BACKGROUND: Prospective studies demonstrate that aggressive pharmacological therapy combined with pump speed optimization may result in myocardial recovery in larger numbers of patients supported with left ventricular assist device (LVAD). This study...
Joint Deep-Learning-Enabled Impact of Holistic Care on Line Coagulation in Hemodialysis.
Journal of healthcare engineering
Dec 16, 2021
In order to investigate the impact of holistic care on line coagulation and safety in hemodialysis and to address limitations of the conventional ultrasound flow vector imaging (VFM) technique, which requires proprietary software to acquire raw Doppl...
Direct left-ventricular global longitudinal strain (GLS) computation with a fully convolutional network.
Journal of biomechanics
Nov 27, 2021
This study's purpose was to develop a direct MRI-based, deep-learning semantic segmentation approach for computing global longitudinal strain (GLS), a known metric for detecting left-ventricular (LV) cardiotoxicity in breast cancer. Displacement Enco...
Automatic deep learning-based myocardial infarction segmentation from delayed enhancement MRI.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 26, 2021
Delayed Enhancement cardiac MRI (DE-MRI) has become indispensable for the diagnosis of myocardial diseases. However, to quantify the disease severity, doctors need time to manually annotate the scar and myocardium. To address this issue, in this pape...
Left ventricular non-compaction cardiomyopathy automatic diagnosis using a deep learning approach.
Computer methods and programs in biomedicine
Nov 23, 2021
BACKGROUND AND OBJECTIVE: Left ventricular non-compaction (LVNC) is an uncommon cardiomyopathy characterised by a thick and spongy left ventricle wall caused by the high presence of trabeculae (hyper-trabeculation). Recently, the percentage of the tr...
A category attention instance segmentation network for four cardiac chambers segmentation in fetal echocardiography.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 16, 2021
Fetal echocardiography is an essential and comprehensive examination technique for the detection of fetal heart anomalies. Accurate cardiac chambers segmentation can assist cardiologists to analyze cardiac morphology and facilitate heart disease diag...
Automated segmentation of biventricular contours in tissue phase mapping using deep learning.
NMR in biomedicine
Sep 2, 2021
Tissue phase mapping (TPM) is an MRI technique for quantification of regional biventricular myocardial velocities. Despite its potential, clinical use is limited due to the requisite labor-intensive manual segmentation of cardiac contours for all tim...
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