Left ventricle segmentation in cardiac MR: A systematic map** of the past decade
Left ventricle segmentation in short-axis cardiac magnetic resonance images is important to
diagnose heart disease. However, repetitive manual segmentation of these images requires …
diagnose heart disease. However, repetitive manual segmentation of these images requires …
Automatic cardiac cine MRI segmentation and heart disease classification
Cardiac cine magnetic resonance imaging (MRI) continues to be recognized as an
established modality for non-invasive assessment of the function and structure of the …
established modality for non-invasive assessment of the function and structure of the …
Encoder modified U-net and feature pyramid network for multi-class segmentation of cardiac magnetic resonance images
Cardiovascular diseases are leading cause of death worldwide. Timely and accurate
detection of disease is required to reduce load on healthcare system and number of deaths …
detection of disease is required to reduce load on healthcare system and number of deaths …
A deep learning segmentation approach in free‐breathing real‐time cardiac magnetic resonance imaging
F Yang, Y Zhang, P Lei, L Wang, Y Miao… - BioMed research …, 2019 - Wiley Online Library
Objectives. The purpose of this study was to segment the left ventricle (LV) blood pool, LV
myocardium, and right ventricle (RV) blood pool of end‐diastole and end‐systole frames in …
myocardium, and right ventricle (RV) blood pool of end‐diastole and end‐systole frames in …
A novel approach for left ventricle segmentation in tagged MRI
X Zou, Q Wang, T Luo - Computers and Electrical Engineering, 2021 - Elsevier
Automatic left ventricle (LV) segmentation from tagged cardiac magnetic resonance imaging
is significant for evaluating heart function and providing follow-up treatments in clinical …
is significant for evaluating heart function and providing follow-up treatments in clinical …
A deep learning-based approach with image-driven active contour loss for medical image segmentation
Medical image segmentation based on deep learning technics has been more and more
prevalent in recent years. The primary reasons lead to success of those methods are radical …
prevalent in recent years. The primary reasons lead to success of those methods are radical …
A new probabilistic active contour region-based method for multiclass medical image segmentation
ER Arce-Santana, AR Mejia-Rodriguez… - Medical & biological …, 2019 - Springer
In medical imaging, the availability of robust and accurate automatic segmentation methods
is very important for a user-independent and time-saving delineation of regions of interest. In …
is very important for a user-independent and time-saving delineation of regions of interest. In …
Segmentation of the cardiac ventricle using two layer level sets with prior shape constraint
Abstract The cardiac Left Ventricle (LV) segmentation is still challengeable due to the
complex anatomical structure surrounding the LV and intensity overlaps caused by intensity …
complex anatomical structure surrounding the LV and intensity overlaps caused by intensity …
Combined metaheuristic algorithm and radiomics strategy for the analysis of neuroanatomical structures in schizophrenia and schizoaffective disorders
Objectives Schizophrenia (SZ) is the most chronic disabling psychotic brain disorder. It is
characterized by delusions and auditory hallucinations, as well as impairments in memory …
characterized by delusions and auditory hallucinations, as well as impairments in memory …
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 …