An automated approach for cerebral microvascularity labeling in microscopy images

Morphological observation and analysis of cerebral microvascular network is an essential way to study cerebral function. Automated labeling of cerebral microvascular in microscopy images is one of the key steps for quantitative analysis of microvascular network in the specimens of brain mantle. It is presented in this work that an automated image processing approach based on curvilinear structure detector is applied to label and analyze the microvascular in the image. Steerable filter is also introduced to address the detecting confusion in branching regions. And then the vascular morphology analysis, such as average microvascular density, is also performed after image processing. Validation has demonstrated that the results from proposed approach are satisfied. The proposed method is finally applied in the study of cerebral microvascular dysfunction induced by γ-ray irradiation.