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http://dx.doi.org/10.5391/JKIIS.2014.24.3.251

An Automated Technique for Detecting Axon Structure in Time-Lapse Neural Image Sequence  

Kim, Nak Hyun (Department of Digital Information Engineering, Hankuk University of Foreign Studies)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.24, no.3, 2014 , pp. 251-258 More about this Journal
Abstract
The purpose of the neural image analysis is to trace the velocities and the directions of moving mitochondria migrating through axons. This paper proposes an automated technique for detecting axon structure. Previously, the detection process has been carried out using a partially automated technique combined with some human intervention. In our algorithm, a consolidated image is built by taking the maximum intensity value on the all image frames at each pixel Axon detection is performed through vessel enhancement filtering followed by a peak detection procedure. In order to remove errors contained in ridge points, a filtering process is devised using a local reliability measure. Experiments have been performed using real neural image sequences and ground truth data extracted manually. It has been turned out that the proposed algorithm results in high detection rate and precision.
Keywords
Neural Image Analysis; Axon Detection; Mitochondria Tracking; Vessel Enhancement Filtering; Peak Detection;
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