Image Classification of Stroke Blood Clot Origin using Deep Convolutional Neural Networks and Visual Transformers

David Azatyan
5/25/2023
cs.CV

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Abstract

Stroke is one of two main causes of death worldwide. Many individuals suffer from ischemic stroke every year. Only in US more over 700,000 individuals meet ischemic stroke due to blood clot blocking an artery to the brain every year. The paper describes particular approach how to apply Artificial Intelligence for purposes of separating two major acute ischemic stroke (AIS) etiology subtypes: cardiac and large artery atherosclerosis. Four deep neural network architectures and simple ensemble method are used in the approach.

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Cite this paper

@article{azatyan2023image,
  title  = {Image Classification of Stroke Blood Clot Origin using Deep Convolutional Neural Networks and Visual Transformers},
  author = {David Azatyan},
  year   = {2023},
  eprint = {2305.16492},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.16492v1}
}

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