• Corpus ID: 232404016

Fully Automated 2D and 3D Convolutional Neural Networks Pipeline for Video Segmentation and Myocardial Infarction Detection in Echocardiography

@article{Hamila2021FullyA2,
  title={Fully Automated 2D and 3D Convolutional Neural Networks Pipeline for Video Segmentation and Myocardial Infarction Detection in Echocardiography},
  author={Oumaima Hamila and Sheela Ramanna and Christopher J. Henry and Serkan Kiranyaz and Ridha Hamila and Rashid Mazhar and Tahir Hamid},
  journal={ArXiv},
  year={2021},
  volume={abs/2103.14734}
}
Cardiac imaging known as echocardiography is a non-invasive tool utilized to produce data including images and videos, which cardiologists use to diagnose cardiac abnormalities in general and myocardial infarction (MI) in particular. Echocardiography machines can deliver abundant amounts of data that need to be quickly analyzed by cardiologists to help them make a diagnosis and treat cardiac conditions. However, the acquired data quality varies depending on the acquisition conditions and the… 

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