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Abstract
Image diagnostics is an important step in acute stroke diagnosis. Cerebrovascular cir- culation disruption resulting in ischemia is present in the majority of stroke cases. The sensitivity of cT findings during the first six hours after the onset of symptoms is con- siderably low. The proposed methods of computerized aided diagnosis in the analysis of clinical data and cT imaging were reviewed but they are not a widely used solution' This thesis focuses on CT image-based analysis and processing methods and subtle ischemic changes detection and recognition algorithms. Objective measures were developed and used in the optimization and comparison of selected processing methods. Diagnostic pro- cedure tests with radiologists proved the stroke Monitor image analysis and processing method's ability to improve the sensitivity of subtle, hyperacute findings detection' An algorithm for automatic detection and recognition of stroke suspected regions wa's prg-' posed. Additional selected neurological symptoms were employed to improve recognition rates. The algorithm achieved performance comparable to the radiologist.
