Taxonomy of Acute Stroke: Imaging, Processing, and Treatment

Area of Science:

• Neurology
• Radiology
• Medical Imaging
• Biomedical Engineering

Background:

• Stroke management relies on diverse diagnostic imaging, image processing, and treatment strategies.
• Accurate and timely diagnosis is crucial for effective stroke intervention and patient outcomes.

Purpose of the Study:

• To categorize and review state-of-the-art methods in stroke imaging, image processing and analysis, and treatment.
• To provide comprehensive taxonomy diagrams for these stroke management components.

Main Methods:

• Systematic review of current literature on stroke management techniques.
• Categorization of diagnostic imaging modalities (CT, MR), image processing approaches (atlas-based, non-atlas-based, AI/deep learning), and treatment procedures (thrombolysis, thrombectomy).
• Development of taxonomy diagrams illustrating these classifications.

Main Results:

• Computed tomography (CT) and magnetic resonance (MR) are primary imaging modalities.
• Image processing methods include non-atlas/template-based (e.g., AI/deep learning) and atlas/template-based approaches.
• Treatment options encompass intravenous/intraarterial thrombolysis and mechanical thrombectomy.

Conclusions:

• This work presents a structured overview of stroke management technologies.
• The provided taxonomies offer a clear framework for understanding current diagnostic imaging, image processing, and treatment landscapes in stroke care.
• This classification aids in navigating and advancing stroke management strategies.