Blockwise processing applied to brain microvascular network study

摘要: The study of cerebral microvascular networks requires high-resolution images. However, to obtain statistically relevant results, a large area the brain (several square millimeters) must be analyzed. This leads us consider huge images, too loaded and processed at once in memory standard computer. To area, compact representation vessels is required. medial axis preferred tool for this application. extract it, dedicated skeletonization algorithm proposed. Numerous approaches already exist which focus on computational efficiency. they all implicitly assume that image can completely computer memory, not realistic with images considered here. We present paper processes data locally (in subimages) while preserving global properties (i.e., homotopy). then show some results obtained mosaic three-dimensional acquired by confocal microscopy