Abstract
The detailed architectural examination of the neuronal nuclei in any brain region, using confocal microscopy, requires quantification of fluorescent signals in three-dimensional stacks of confocal images. An essential prerequisite to any quantification is the segmentation of the nuclei which are typically tightly packed in the tissue, the extreme being the hippocampal dentate gyrus (DG), in which nuclei frequently appear to overlap due to limitations in microscope resolution. Segmentation in DG is a challenging task due to the presence of a significant amount of image artifacts and densely packed nuclei. Accordingly, we established an algorithm based on continuous boundary tracing criterion aiming to reconstruct the nucleus surface and to separate the adjacent nuclei. The presented algorithm neither uses a pre-built nucleus model, nor performs image thresholding, which makes it robust against variations in image intensity and poor contrast. Further, the reconstructed surface is used to study morphology and spatial arrangement of the nuclear interior. The presented method is generally dedicated to segmentation of crowded, overlapping objects in 3D space. In particular, it allows us to study quantitatively the architecture of the neuronal nucleus using confocal-microscopic approach.
Highlights
The morphological changes in neuronal cell nuclei and the analysis of details of their architecture have recently become an important issue in contemporary neuroscience
An automated segmentation and surface reconstruction of neuronal nuclei is a crucial procedure required for quantitative studies of neuronal architecture
The presented method, which relies on very mild assumptions on the nuclear shapes, is capable of resolving a large number of nuclei allowing further quantitative analysis
Summary
The morphological changes in neuronal cell nuclei and the analysis of details of their architecture have recently become an important issue in contemporary neuroscience. A crucial prerequisite to any quantification is a 3D segmentation and reconstruction of neuronal nuclei, which are sometimes tightly packed within the cell layer. In the case of studies of densely packed neurons, the automatic segmentation of their nuclei is a challenging task. This is mostly due to the fact that the nuclei can lie very close to one another, in such a way that their segmentation is very difficult because of the limited resolution of the light microscopes (especially in the z-direction) and various image artifacts
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