3D Slicer is: A software platform for the analysis (including registration and interactive segmentation) and visualization (including volume rendering) of medical images and for research in image guided therapy. A free, open source software available on multiple operating systems: Linux, MacOSX and Windows Extensible, with powerful plug-in capabilities for adding algorithms and applications. Features include: Multi organ: from head to toe. Support for multi-modality imaging including, MRI, CT, US, nuclear medicine, and microscopy. Bidirectional interface for devices. There is no restriction on use, but Slicer is not approved for clinical use and intended for research. Permissions and compliance with applicable rules are the responsibility of the user.
siibra-explorer is a browser-based 3D viewer for exploring brain atlases that cover different spatial resolutions and modalities.
siibra-explorer is built around an interactive 3D view of the brain displaying a unique selection of detailed templates and parcellation maps for the human, macaque, rat or mouse brain, including BigBrain as a microscopic resolution human brain model at its full resolution of 20 micrometres.
By selecting brain regions or zooming into user-defined regions of interest, users can find and access data features from different modalities which have been linked to the respective locations in the brain, including structural and functional connectivity, histological features such as cell and neurotransmitter densities, 2D and 3D images, and gene expressions. This way siibra-explorer allows to explore and study brain organization in many different facets.
siibra stands for "software interfaces for interacting with brain atlases" and includes a suite of tools of which siibra-explorer is the most immediate and intuitive entry point. The python library siibra-python provides all the functionality of the explorer and more for developing computational workflows, while the http interface siibra-api can be used for application development.
siibra-explorer has been developed in the frame of the Human Brain Project. The main installation is hosted as a publicly accessible service at https://atlases.ebrains.eu/viewer
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Dendritic spines of pyramidal neurons are the targets of most excitatory synapses in the cerebral cortex and their morphology appears to be critical from the functional point of view. Thus, characterizing this morphology is necessary to link structural and functional spine data and thus interpret and make them more meaningful. We have used a large database of more than 7,000 individually 3D reconstructed dendritic spines from human cortical pyramidal neurons that is first transformed into a set of 54 quantitative features characterizing spine geometry mathematically. The resulting data set is grouped into spine clusters based on a probabilistic model with Gaussian finite mixtures. We uncover six groups of spines whose discriminative characteristics are identified with machine learning methods as a set of rules. The clustering model allows us to simulate accurate spines from human pyramidal neurons to suggest new hypotheses of the functional organization of these cells.
A Structure Tensor Analysis (STA) tool for the characterization of local 3D orientation in TIFF image stacks. This tool is based on the evaluation of local image intensity gradients. In addition to the local 3D orientation, it also provides a full analysis of local gradient strength, structure disarray, shape and fractional anisotropy indices.