Ischemic Stroke

Ischemic stroke, caused by blocked brain blood vessels, is a leading cause of death and disability, demanding rapid and accurate diagnosis for effective treatment. Current research intensely focuses on improving prediction of infarct size and location using multimodal imaging (CT, MRI, CTA) and clinical data, employing deep learning architectures like U-Nets, 3D convolutional neural networks, and transformers to analyze these data and predict outcomes such as hemorrhage risk and functional recovery. These advancements aim to optimize treatment decisions, such as mechanical thrombectomy, and improve patient outcomes by enabling more precise and timely interventions.