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Updated: Aug 15, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
Abstract:
Most contemporary neuron tracing systems are semi-automatic; that is, an operator follows neuron branches in a microscope or on a data tablet and instructs a computer when to record a spatial sample. A list of such samples is then used to generate a display of the neuron and to summarize statistically its structure. The tracing is tedious, and the operator must make subjective decisions about point types, thus biasing the results. A fully automatic system in which the computer views the image through a television digitizing system has been constructed. The computer follows the fibers and recognizes branchpoints and fiber endings. The coordinates, types of points, and fiber diameters are recorded in computer memory. An operator is required only to start the tracing of a fiber and to help the computer when it becomes "confused". The results are mixed. The computer can follow fibers quite successfully and can determine branches and endings with some success, but the procedure is an order of magnitude more slow than that of a skilled operator using a well-designed semi-automatic system.
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