Speckle pattern analysis with deep learning for low-cost stroke detection: a phantom-based feasibility study.

Journal: Journal of biomedical optics
PMID: 40337176

Abstract

SIGNIFICANCE: Stroke is a leading cause of disability worldwide, necessitating rapid and accurate diagnosis to limit irreversible brain damage. However, many advanced imaging modalities (computerized tomography, magnetic resonance imaging) remain inaccessible in remote or resource-constrained settings due to high costs and logistical barriers.

Authors

  • Avraham Yosovich
    Bar Ilan University, Faculty of Engineering and Nanotechnology Center, Ramat Gan, Israel.
  • Sergey Agdarov
    Bar-Ilan University, Faculty of Engineering, Ramat Gan, Israel.
  • Yafim Beiderman
    Bar-Ilan University, Faculty of Engineering, Nanotechnology Center, Ramat-Gan, Israel.
  • Yevgeny Beiderman
    Bar-Ilan University, Faculty of Engineering, Nanotechnology Center, Ramat-Gan, Israel.
  • Zeev Zalevsky
    Faculty of Engineering and the Nano-Technology Center, Bar-Ilan University, Ramat Gan, 52900 Israel.

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