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Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-ventricular Short-axis Cardiac MR Data
2021
IEEE journal of biomedical and health informatics
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Automatic quantification of the left ventricle (LV) from cardiac magnetic resonance (CMR) images plays an important role in making the diagnosis procedure efficient, reliable, and alleviating the laborious ...
Considerable efforts have been devoted to LV quantification using different strategies that include segmentation-based (SG) methods and the recent direct regression (DR) methods. ...
ACKNOWLEDGMENTS The paper is partially supported by the Natural Science ...
doi:10.1109/jbhi.2021.3064353
pmid:33684050
pmcid:PMC7611810
fatcat:2dpv72thbfcbrerxtdjmzyrtkq
A review of approaches investigated for right ventricular segmentation using short‐axis cardiac MRI
2021
IET Image Processing
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The right ventricular assessment is crucial to heart disease diagnosis. ...
Enhanced by our expert's interpretation, the results of over forty research papers were evaluated based on several metrics such as the dice metric and the Hausdorff distance. ...
They considered, thus, three pathological cases: myocardial infarction, dilated cardiomyopathy, and hypertrophy. The highest reported error is related to the RV dilated cardiomyopathy case. ...
doi:10.1049/ipr2.12165
fatcat:37s7d737hberdcbwhi2j6aospq
Automated Diagnosis of Cardiovascular Diseases from Cardiac Magnetic Resonance Imaging Using Deep Learning Models: A Review
[article]
2022
arXiv
pre-print
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Coupled with all the advantages of CMR data, CVDs diagnosis is challenging for physicians due to many slices of data, low contrast, etc. ...
Next, the discussion section discusses the results of this review, and future work in CVDs diagnosis from CMR images and DL techniques are outlined. ...
Sunnybrook Cardiac Data (SCD) The SCD dataset contains cine-CMR images of 45 individuals with four pathologies, namely, healthy, hypertrophy, heart failure with infarction and heart failure without infarction ...
arXiv:2210.14909v1
fatcat:5bls3nuovjempl4sd4l7lvhjqu
An Overview of Deep Learning Methods for Left Ventricle Segmentation
2023
Computational Intelligence and Neuroscience
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Due to automatic segmentation and good promising results, the left ventricle segmentation using deep learning has attracted a lot of attention. ...
The left ventricle is a vital part of the cardiovascular system where the boundary and size perform a significant role in the evaluation of cardiac function. ...
Acknowledgments Tis work was supported by the Fundamental Research Grant Scheme (FRGS), Ministry of Higher Education Malaysia, and University Malaya under the project no. FRGS/1/2019/TK04/UM/01/2. ...
doi:10.1155/2023/4208231
pmid:36756163
pmcid:PMC9902166
fatcat:eqo2f77m3bcbndbn75mhe2vomu
Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report
2022
Journal of Cardiovascular Development and Disease
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Radiological imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound were selected for imaging of the vasculature infected by COVID-19. ...
Further, the study presents recommendations for improving AI-based architectures for vascular studies. ...
Researchers in Italy reported a study of 28 patients with verified COVID-19 who had undergone a coronary angiogram for diagnosis of STelevation myocardial infarction. ...
doi:10.3390/jcdd9080268
pmid:36005433
pmcid:PMC9409845
fatcat:6wtmt3xv3zcx5aqe3a7fsjijti