Vessel extraction in X-ray angiograms using deep learning

  title={Vessel extraction in X-ray angiograms using deep learning},
  author={Ebrahim Nasr-Esfahani and Shadrokh Samavi and Nader Karimi and S. Mohamad R. Soroushmehr and Kevin Ward and M. Jafari and Banafsheh Felfeliyan and Brahmajee. K. Nallamothu and Kayvan Najarian},
  journal={2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  • E. Nasr-EsfahaniS. Samavi K. Najarian
  • Published 1 August 2016
  • Computer Science
  • 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Coronary artery disease (CAD) is the most common type of heart disease which is the leading cause of death all over the world. X-ray angiography is currently the gold standard imaging technique for CAD diagnosis. These images usually suffer from low quality and presence of noise. Therefore, vessel enhancement and vessel segmentation play important roles in CAD diagnosis. In this paper a deep learning approach using convolutional neural networks (CNN) is proposed for detecting vessel regions in… 

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