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

Although tested on a tissue phantom, these findings highlight the potential of combining speckle imaging with deep learning for accessible, rapid stroke detection. Our next steps involve direct <i>in vivo</i> experiments targeting cerebral arteries, acknowledging that additional factors such as the skull's optical properties and the likely need for near-infrared illumination must be addressed before achieving true intracranial applicability. We also note that examining the carotid artery <i>in vivo</i> remains a valuable and practical step, given its superficial location and direct relevance to stroke risk.