Deep learning-based automatic segmentation of images in cardiac radiography: a promising challenge
Background Due to the advancement of medical imaging and computer technology,
machine intelligence to analyze clinical image data increases the probability of disease …
machine intelligence to analyze clinical image data increases the probability of disease …
Cardiac magnetic resonance imaging (CMRI) applications in patients with chest pain in the emergency department: a narrative review
CMRI is the exclusive imaging technique capable of identifying myocardial edema,
endomyocardial fibrosis, pericarditis accompanied by pericardial effusions, and apical …
endomyocardial fibrosis, pericarditis accompanied by pericardial effusions, and apical …
When seeing is not believing: application-appropriate validation matters for quantitative bioimage analysis
A key step toward biologically interpretable analysis of microscopy image-based assays is
rigorous quantitative validation with metrics appropriate for the particular application in use …
rigorous quantitative validation with metrics appropriate for the particular application in use …
Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging
Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function
assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However …
assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However …
Cardiac MRI segmentation with sparse annotations: ensembling deep learning uncertainty and shape priors
The performance of deep learning for cardiac magnetic resonance imaging (MRI)
segmentation is oftentimes degraded when using small datasets and sparse annotations for …
segmentation is oftentimes degraded when using small datasets and sparse annotations for …
Stochastic co-teaching for training neural networks with unknown levels of label noise
Label noise hampers supervised training of neural networks. However, data without label
noise is often infeasible to attain, especially for medical tasks. Attaining high-quality medical …
noise is often infeasible to attain, especially for medical tasks. Attaining high-quality medical …
A comparative study of state-of-the-art skin image segmentation techniques with CNN
Skin cancer is caused by genetic uncertainty or an irregular growth of cells, mostly grows
when our skin is exposed to sun. In people, melanoma is a common type of cancer …
when our skin is exposed to sun. In people, melanoma is a common type of cancer …
[HTML][HTML] From accuracy to reliability and robustness in cardiac magnetic resonance image segmentation: a review
Since the rise of deep learning (DL) in the mid-2010s, cardiac magnetic resonance (CMR)
image segmentation has achieved state-of-the-art performance. Despite achieving inter …
image segmentation has achieved state-of-the-art performance. Despite achieving inter …
Estimating uncertainty in neural networks for cardiac MRI segmentation: a benchmark study
Objective: Convolutional neural networks (CNNs) have demonstrated promise in automated
cardiac magnetic resonance image segmentation. However, when using CNNs in a large …
cardiac magnetic resonance image segmentation. However, when using CNNs in a large …
ViT-FRD: A vision transformer model for cardiac MRI image segmentation based on feature recombination distillation
C Fan, Q Su, Z Xiao, H Su, A Hou, B Luan - IEEE Access, 2023 - ieeexplore.ieee.org
Cardiac magnetic resonance imaging analysis has been a useful tool in screening patients
for heart disease. Early, timely and accurate diagnosis of diseases of the heart series is the …
for heart disease. Early, timely and accurate diagnosis of diseases of the heart series is the …