CNN-Res: deep learning framework for segmentation of acute ischemic stroke lesions on multimodal MRI images.

Journal: BMC medical informatics and decision making
Published Date: Sep 26, 2023

Abstract

BACKGROUND: Accurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation helps clinicians to better diagnose and evaluation of any treatment risks. However, manual segmentation of brain lesions relies on the experience of neurologists and is also a very tedious and time-consuming process. So, in this study, we proposed a novel deep convolutional neural network (CNN-Res) that automatically performs the segmentation of ischemic stroke lesions from multimodal MRIs.

Authors

  • Yousef Gheibi
    Department of Artificial Intelligence, Faculty of Computer Engineering, University of Tabriz, Tabriz, Iran.
  • Kimia Shirini
    Department of Software Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, East Azerbaijan, Iran.
  • Seyed Naser Razavi
    Department of Computer Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, 51666-16471, Iran. n.razavi@tabrizu.ac.ir.
  • Mehdi Farhoudi
    Neurosciences Research Center (NSRC), Tabriz University of Medical Sciences, Tabriz, Iran.
  • Taha Samad-Soltani
    Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.

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