Stroke: Quantitative Imaging-Guided Approaches
A special issue of Tomography (ISSN 2379-139X).
Deadline for manuscript submissions: 31 December 2024 | Viewed by 7132
Special Issue Editor
2. Berlin Institute of Health (BIH), BIH Biomedical Innovation Academy, Berlin, Germany
Interests: ischemic stroke; hemorrhagic stroke; outcome prediction; diagnosis prediction; quantitative-imaging-based models for prediction; computed tomography imaging-based radiomic models; deep learning in the imaging study of stroke
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Stroke remains a major cause of morbidity and mortality worldwide. While imaging-guided therapy in acute ischemic stroke is aimed at identifying further subpopulations to benefit from endovascular interventions, imaging-guided tailored treatment in hemorrhagic stroke has mainly focused on evaluating acute hematoma expansion as it presents a potentially therapeutic target. In quantitative imaging (QI), components of the pathological mechanisms involved in both stroke types can be used as potential biomarkers to further improve the current limitations of imaging-guided therapies; thus, further studies investigating biomarkers are needed. At the same time, artificial intelligence (AI) will lead to significant advances in the QI of stroke within the next decade by exploring even deeper image information. This Special Issue focuses on the development and clinical role of QI and AI advances in the precise diagnosis and individualized treatment decision in acute ischemic and hemorrhagic stroke patients.
Dr. Jawed Nawabi
Guest Editor
Manuscript Submission Information
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Keywords
- ischemic stroke
- hemorrhagic stroke
- intracerebral hemorrhage
- quantitative imaging
- outcome prediction
- intelligent segmentation
- focus detection
- lesion prediction
- machine learning
- deep learning
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