Classification of arterial and venous cerebral vasculature based on wavelet postprocessing of CT perfusion data - Havla, Lukas; Schneider, Moritz J.; Thierfelder, Kolja M.; Beyer, Sebastian E.; Ertl‐Wagner, Birgit; Reiser, Maximilian F.; Sommer, Wieland H.; Dietrich, Olaf (Medical physics (Lancaster), 2016)
Keywords: Adolescent; Adult; Aged; Aged, 80 and over; angiography; Biological material, e.g. blood, urine; Haemocytometers; biomedical MRI; blood vessels; Cerebral Arteries - diagnostic imaging; Cerebral Arteries - physiopathology; Cerebral Veins - diagnostic imaging; Cerebral Veins - physiopathology; Cerebrovascular stroke; Computed tomography; Computerised tomographs; computerised tomography; diagnostic imaging; Digital computing or data processing equipment or methods, specially adapted for specific applications; discriminant analysis; Female; Humans; image classification; Image data processing or generation, in general; Image Processing, Computer-Assisted - methods; image segmentation; In which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines; Inference methods or devices; Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging; Linear Models; Magnetic resonance imaging; Male; Medical image noise; medical image processing; Middle Aged; Neovascularization, Pathologic; Pathology; perfusion CT; Perfusion Imaging; Probability theory, stochastic processes, and statistics; regression analysis; ROC Curve; Segmentation; Stroke - diagnostic imaging; Stroke - physiopathology; support vector machines; Tomography, X-Ray Computed; Vascular system; Vector calculus; Wave attenuation; Wavelet Analysis; wavelet transform; Wavelets; Young Adult