An Effective ROI Extracting Method for Color Brain Slice in Assisting the Diagnostic Analysis of Epilepsy

Abstract

For the epilepsy disease, many studies about the thickness of cortex among various brain regions haven been implemented. However, there is few research about the cell distribution of the gray matter of adjacent gyrus and sulcus. Our studies indicate it is possible different that the thickness of the GFAP-IR interlaminar astrocytes somas between in gyri and sulci in epilepsy. Based on this motivation, we proposed a color brain slice image ROI (region of interest) extracting method. A classifying method is imported to compute the comparability between two pixels in the slice image. An improved mechanism of color data query table is designed to accelerate the processing speed. Human brain tissue images acquired during surgical resection for epilepsy are utilized as the experimental object. The regions of most interest can be extracted and the 3D color gradient field can also be visualized. In conclusion, we can not only achieve the information of interlaminar astrocytes, but also provide a technic support for building the information network of epilepsy diseases.