Improving diagnostic value of CT examinations in hyperacute ischemic stroke

This paper presents a computer assisted support of ischemic stroke diagnosis based on nonenhanced CT examinations acquired in the hyperacute phase of stroke. Computational analysis, recognition, and image understanding methods were used for extraction of the subtlest signs of hypodensity in diagnostically important areas. Starting from perception improvement, suggestive and coarse image data visualization was designed as a complement of the standard diagnosis procedure based on CT scan soft-copy review. The proposed method includes an evidence-based description of ischemic conditions and changes, de-skulling and segmenting of unusual areas, the analysis of hypodensity signs across scales and subbands with noise reduction, and hypodensity extraction. Following visualization, forms of empowered hypodensity symptoms localize suggested ischemic areas in source brain image space. Increased visibility of cerebral ischemia for difficult-to-diagnose cases was experimentally noticed and improved diagnostic value of CT was concluded.