Multi-dimensional data analysis of intracerebral hemorrhage from CT images

Intracranial hemorrhage(ICH) is a very life-threatening situation to human beings for the formation of thrombus, blood lipids or brain trauma as well as chronic hypertension, cerebral amyloid angiopathy (CAA), acute changes in blood pressure and blood flow ect. The numerical characterization of ICH are proposed through by multi-dimensional data analysis(MDDA), such as principal component analysis(PCA), locally linear embedding(LLE) algorithm, which are based on level scale of corresponding pixels and the histograms of the computer tomography images in the paper. Numerical experiments are also showed the results exactly, which would be used to segmentation of the data for diagnosis of ICH, quantitative evaluation of treatment and postoperative situation.