It is well known that the density of neurons varies within the adult brain. In neocortex, this includes variations in neuronal density between different lamina as well as between different regions. Yet the concomitant variation of the microvessels is largely uncharted. Here, we present automated histological, imaging, and analysis tools to simultaneously map the locations of all neuronal and non-neuronal nuclei and the centerlines and diameters of all blood vessels within thick slabs of neocortex from mice. Based on total inventory measurements of different cortical regions ( approximately 10(7) cells vectorized across brains), these methods revealed: (1) In three dimensions, the mean distance of the center of neuronal somata to the closest microvessel was 15 mum. (2) Volume samples within lamina of a given region show that the density of microvessels does not match the strong laminar variation in neuronal density. This holds for both agranular and granular cortex. (3) Volume samples in successive radii from the midline to the ventral-lateral edge, where each volume summed the number of cells and microvessels from the pia to the white matter, show a significant correlation between neuronal and microvessel densities. These data show that while neuronal and vascular densities do not track each other on the 100 mum scale of cortical lamina, they do track each other on the 1-10 mm scale of the cortical mantle. The absence of a disproportionate density of blood vessels in granular lamina is argued to be consistent with the initial locus of functional brain imaging signals.

https://www.jneurosci.org/content/jneuro/29/46/14553.full.pdf

Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels.

Pore structure characterization of coal by synchrotron radiation nano-CT

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

/pdf/blockwise-processing-applied-to-brain-microvascular-network-1paa0c2opw.pdf

Blockwise processing applied to brain microvascular network study

Improving microstructural quantification in FIB/SEM nanotomography.

We report the results of pore-network analysis of high resolution synchrotron microtomographic images of Fontainebleau and Berea Sandstones. We segment the gray-scale images of the rocks into constituent phases, and analyze the geometry of the pore network. The network consists of pores situated at the corner of grains and serve as the junction between elongated throats along grain edges. Our analysis indicates that the number of pores, their median coordination number, and fraction of connected pore space increases with an increase in porosity. In contrast, the width and length of throats decrease with an increase in total porosity. In each sample, the coordination number of pores is directly related to the radius of the pores, while the length of throats are also positively correlated with the throat radius. The permeability determined from the images increase with the total connected porosity of the samples and there is a change in the modeled permeability for each sample with flow direction. We observe that the dimensionless coefficient of variation of the throat lengths in all samples are nearly uniform around an average value of 0.64. The coefficient of variation of throat radii are generally higher than that of the radius of pores.

Image Segmentation and Analysis of Pore Network Geometry in Two Natural Sandstones

Skeletons are compact representations that allow mathematical analysis of objects. A skeleton must be homotopic, thin and medial in relation to the object it represents. Numerous approaches already exist which focus on computational efficiency. However, when dealing with data too large to be loaded into the main memory of a personal computer, such approaches can no longer be used. We present in this article a skeletonization algorithm that processes the data locally (in sub-images) while preserving global properties (medial localization). Our privileged application is the study of the cerebral micro-vascularisation, and we show some results obtained on a mosaic of 3-D images acquired by confocal microscopy.

/pdf/skeletonization-by-blocks-for-large-3d-datasets-application-2hfubcujmf.pdf

Skeletonization by blocks for large 3D datasets: application to brain microcirculation

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Skeletonization by blocks for large 3D datasets: application to brain microcirculation