Three-dimensional reconstruction and visualization of the cerebral cortex in primates

We present a prototype interactive application for the direct analysis in three dimensions of the cerebral cortex in primates. The paper provides an overview of the current prototype system and presents the techniques used for reconstructing the cortex shape from data derived from histological sections as well as for rendering it at interactive rates. Results are evaluated by discussing the analysis of the right hemisphere of the brain of a macaque monkey used for neuroanatomical tract-tracing experiments.147-15

Convex Structuring Element Decomposition for Single Scan Binary Mathematical Morphology

International audienceThis paper presents a structuring element decomposition method and a corresponding morphological erosion algorithm able to compute the binary erosion of an image using a single regular pass whatever the size of the convex structuring element. Similarly to classical dilation-based methods, the proposed decomposition is iterative and builds a growing set of structuring elements. The novelty consists in using the set union instead of the Minkowski sum as the elementary structuring element construction operator. At each step of the construction, already-built elements can be joined together in any combination of translations and set unions. There is no restrictions on the shape of the structuring element that can be built. Arbitrary shape decompositions can be obtained with existing genetic algorithms with an homogeneous construction method. This paper, however, addresses the problem of convex shape decomposition with a deterministic method

3D Volume Reconstruction by Serially Acquired 2D Slices Using a Distance Transform-Based Global Cost Function

Abstract. An accurate, computationally eÆcient and fully-automated algorithm for the alignment of 2D serially acquired sections forming a 3D volume is presented. The method accounts for the main shortcomings of 3D image alignment: corrupted data (cuts and tears), dissimilarities or discontinuities between slices, missing slices. The approach relies on the optimization of a global energy function, based on the object shape, measuring the similarity between a slice and its neighborhood in the 3D volume. Slice similarity is computed using the distance transform measure in both directions. No particular direction is privileged in the method avoiding global osets, biases in the estimation and error prop-agation. The method was evaluated on real images (medical, biological and other CT scanned 3D data) and the experimental results demon-strated the method's accuracy as reconstuction errors are less than 1 degree in rotation and less than 1 pixel in translation.

Three-Dimensional Analysis of Spiny Dendrites Using Straightening and Unrolling Transforms

Current understanding of the synaptic organization of the brain depends to a large extent on knowledge about the synaptic inputs to the neurons. Indeed, the dendritic surfaces of pyramidal cells (the most common neuron in the cerebral cortex) are covered by thin protrusions named dendritic spines. These represent the targets of most excitatory synapses in the cerebral cortex and therefore, dendritic spines prove critical in learning, memory and cognition. This paper presents a new method that facilitates the analysis of the 3D structure of spine insertions in dendrites, providing insight on spine distribution patterns. This method is based both on the implementation of straightening and unrolling transformations to move the analysis process to a planar, unfolded arrangement, and on the design of DISPINE, an interactive environment that supports the visual analysis of 3D patterns

Automated Three-Dimensional Detection and Shape Classification of Dendritic Spines from Fluorescence Microscopy Images

A fundamental challenge in understanding how dendritic spine morphology controls learning and memory has been quantifying three-dimensional (3D) spine shapes with sufficient precision to distinguish morphologic types, and sufficient throughput for robust statistical analysis. The necessity to analyze large volumetric data sets accurately, efficiently, and in true 3D has been a major bottleneck in deriving reliable relationships between altered neuronal function and changes in spine morphology. We introduce a novel system for automated detection, shape analysis and classification of dendritic spines from laser scanning microscopy (LSM) images that directly addresses these limitations. The system is more accurate, and at least an order of magnitude faster, than existing technologies. By operating fully in 3D the algorithm resolves spines that are undetectable with standard two-dimensional (2D) tools. Adaptive local thresholding, voxel clustering and Rayburst Sampling generate a profile of diameter estimates used to classify spines into morphologic types, while minimizing optical smear and quantization artifacts. The technique opens new horizons on the objective evaluation of spine changes with synaptic plasticity, normal development and aging, and with neurodegenerative disorders that impair cognitive function

Elpusztított emlékhelyek

A Magyar Királyi Csendőrségnek négy emlékhelye volt, közülük hármat Budapesten helyezték el a két világháború között, a negyediket Nyitra vármegyében a dualizmus időszakában hozták létre