A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI
MR Avendi, A Kheradvar, H Jafarkhani - Medical image analysis, 2016 - Elsevier
Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI)
datasets is an essential step for calculation of clinical indices such as ventricular volume and …
datasets is an essential step for calculation of clinical indices such as ventricular volume and …
Estimation of the volume of the left ventricle from MRI images using deep neural networks
Segmenting human left ventricle (LV) in magnetic resonance imaging images and
calculating its volume are important for diagnosing cardiac diseases. The latter task became …
calculating its volume are important for diagnosing cardiac diseases. The latter task became …
Maintaining filter structure: A Gabor-based convolutional neural network for image analysis
S Molaei, MESA Abadi - Applied Soft Computing, 2020 - Elsevier
In image segmentation and classification tasks, utilizing filters based on the target object
improves performance and requires less training data. We use the Gabor filter as …
improves performance and requires less training data. We use the Gabor filter as …
Myocardial segmentation in cardiac magnetic resonance images using fully convolutional neural networks
Abstract According to the World Health Organization, cardiovascular diseases are the
leading cause of death worldwide. Many coronary diseases involve the left ventricle; …
leading cause of death worldwide. Many coronary diseases involve the left ventricle; …
[HTML][HTML] Fully‑automated deep‑learning segmentation of pediatric cardiovascular magnetic resonance of patients with complex congenital heart diseases
Background For the growing patient population with congenital heart disease (CHD),
improving clinical workflow, accuracy of diagnosis, and efficiency of analyses are …
improving clinical workflow, accuracy of diagnosis, and efficiency of analyses are …
A quick review on cardiac image segmentation
In this study, all of the methods utilized to segment cardiac images have been evaluated.
Recent research reveals that new deep learning approaches using high-speed GPUs …
Recent research reveals that new deep learning approaches using high-speed GPUs …
Deep convolutional neural networks for left ventricle segmentation
Left ventricle (LV) segmentation is crucial for quantitative cardiac function analysis. Manual
segmentation of the endocardium and epicardium is highly cumbersome; physicians limit …
segmentation of the endocardium and epicardium is highly cumbersome; physicians limit …
Feature competition and partial sparse shape modeling for cardiac image sequences segmentation
X Qin, Y Tian, P Yan - Neurocomputing, 2015 - Elsevier
The segmentation of endocardium and epicardium of left ventricle (LV) in cardiac MR image
sequences play a crucial role in clinical applications. Active shape model (ASM) based …
sequences play a crucial role in clinical applications. Active shape model (ASM) based …
Automatic left ventricle segmentation via edge‐shape feature‐based fully convolutional neural network
K Gayathri, N Uma Maheswari… - … Journal of Imaging …, 2024 - Wiley Online Library
Left ventricle (LV) segmentation is essential to identify the cardiac functions for treating
cardiovascular disorders. Cardiovascular magnetic resonance (CMRI) imaging is a non …
cardiovascular disorders. Cardiovascular magnetic resonance (CMRI) imaging is a non …
Fully automatic segmentation of the left ventricle using multi-scale fusion learning
Segmentation of the left ventricle (LV) is essential for quantitative calculation of clinical
indices for analyzing the cardiac contractile function. However, it is challenging to …
indices for analyzing the cardiac contractile function. However, it is challenging to …