DocumentCode
724955
Title
Neuron crawler: An automatic tracing algorithm for very large neuron images
Author
Zhi Zhou ; Sorensen, Staci A. ; Hanchuan Peng
Author_Institution
Allen Inst. for Brain Sci., Seattle, WA, USA
fYear
2015
fDate
16-19 April 2015
Firstpage
870
Lastpage
874
Abstract
Automatic 3D neuron reconstruction for very large 3D light microscopy images remains to be a challenge in neuroscience. Few existing neuron tracing algorithms can be used with commonly available computers (laptops, desktops, or workstations) to efficiently and accurately reconstruct a neuron in image stacks that are tens of gigabytes or greater. We introduce a new automatic tracing algorithm called Neuron Crawler, which works by first tracing a region of interest (e.g., around the soma), and then iteratively tracing in adjacent image tiles to grow the neuron structure in 3D to its termination point within the image. Our experimental results show that Neuron Crawler can achieve reconstruction accuracy that is comparable to several state-of-the-art algorithms, but with much less computational cost.
Keywords
biomedical optical imaging; cellular biophysics; image reconstruction; iterative methods; medical image processing; neurophysiology; optical microscopy; Neuron Crawler algorithm; automatic 3D neuron reconstruction; automatic neuron tracing algorithm; computational cost; image stack; iterative adjacent image tile tracing; large 3D light microscopy image; large neuron image; neuron structure growing; neuroscience; reconstruction accuracy; region of interest tracing; soma; termination point; Computational efficiency; Computers; Crawlers; Image reconstruction; Memory management; Neurons; Three-dimensional displays; 3D neuron reconstruction; Neuron Crawler; all-path-pruning; large-scale image;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
Conference_Location
New York, NY
Type
conf
DOI
10.1109/ISBI.2015.7164009
Filename
7164009
Link To Document