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An interactive 3D axon tracking and labeling tool to obtain quantitative information by reconstruction of the axonal structures in the entire innervation field. AxonTracker-3D has been developed to facilitate the connectome function analysis in large-scale quantitative neurobiology studies. It can display the three orthogonal views of the current location of the centerline along with a visualization of the tracking results. The workflow consists of three steps: (i) re-slice the axon tubes along its orientation; (ii) extract 2D and 3D features from the slices and spheres rounding the center points; (iii) select samples to train AdaBoost classifier. Questions such as whether the spatial distribution of the axons are random in nature or follow a certain pattern can be answered with this tool.
Represents a deep learning method for segmenting 3D anisotropic brain electron microscopy images. DeepEM3D can efficiently build feature representation and incorporate sufficient multi-scale contextual information. DeepEM3D is able to produce highly accurate 3D neurite boundary probability maps, thereby requiring only a simple watershed method to do segmentation. This tool uses the power of inception and residual structures in the bottom-up path to integrate image information, and combines skip connection techniques with pyramid multi-scale contexture aggregation in the top-down path.
A multi-user web-based collaborative management system for images and volumes which allows users to view multi-terabyte datasets, annotate images with their own annotation schema, and summarize the results. Viking has several key features. (1) It works over the internet using HTTP and supports many concurrent users limited only by hardware. (2) It supports a multi-user, collaborative annotation strategy. (3) It cleanly demarcates viewing and analysis from data collection and hosting. (4) It is capable of applying transformations in real-time. (5) It has an easily extensible user interface, allowing addition of specialized modules without rewriting the viewer.
Amira 3D Software for Life Sciences
Allows users to visualize, manipulate, and understand data from imaging modalities such as computed tomography, microscopy or Magnetic resonance imaging (MRI). Amira 3D Software for Life Sciences provides features to import and process 2D and 3D images data, visualization techniques and tools for visual analysis. Users can also create and share presentations. The base product can be customized by adding functional extensions to fit special needs in different application areas.
NeuroGPS-Tree / NeuronGlobalPositionSystem-Tree
Reconstructs neuronal population from image stacks. NeuroGPS-Tree is built on NeuroGPS software. In NeuroGPS-Tree reconstruction, individual neuronal trees can be identified and quantified. NeuroGPS-Tree reconstructs neuronal populations by partially mimicking the strategy used by experienced annotators and progressively approaches an accurate reconstruction by repetitively using statistical information about neuronal morphology at multiple scales. These features make NeuroGPS-Tree an effective tool for analyzing data sets in which the neurite density is too complex for previously established methods. NeuroGPS-Tree is also suitable for the analysis of large-scale data sets, and it may be useful for mapping neuronal circuits.
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