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dc.contributor.authorLee, Ping-Changen_US
dc.contributor.authorChing, Yu-Taien_US
dc.contributor.authorChang, H. M.en_US
dc.contributor.authorChiang, Ann-Shynen_US
dc.date.accessioned2014-12-08T15:04:23Z-
dc.date.available2014-12-08T15:04:23Z-
dc.date.issued2008en_US
dc.identifier.isbn978-1-4244-2002-5en_US
dc.identifier.issn1945-7928en_US
dc.identifier.urihttp://hdl.handle.net/11536/2885-
dc.description.abstractAn algorithm for extracting the centerlines of neurons from 3-D image stack collected from a laser scanning confocal microscope is presented. Recovery of neuronal structure from image stack is critical for quantitative analysis of neuron-morphology. Many methods have been proposed to extract the centerline from the tubular structure in medical images, such as vessels. But the same methods do not work well in processing of neurons. One of the reasons is that the physical limitations of the spatial resolution of the image stack collect by confocal microscopy in the z-direction is much worse than the resolution in x and y directions. In our studied cases the mean voxel size of the image stack is 0.17 x 0.17 x 1.0 mu m(3) i.e., the resolution in z-direction cannot reflect the fact that the neuron has a tubular structure. In this paper, we propose an almost automatic neuron-tracing algorithm for a set of confocal microscopic images of neuron. The method is designed based on finding a minimal path in the volume to extract the centerlines of a neuron.en_US
dc.language.isoen_USen_US
dc.subjectconfocal microscopyen_US
dc.subjectprojection neuronen_US
dc.subjectneuronal structureen_US
dc.subjectcenterline extractionen_US
dc.subjectminimum path findingen_US
dc.titleA semi-automatic method for neuron centerline extraction in confocal microscopic image stacken_US
dc.typeProceedings Paperen_US
dc.identifier.journal2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4en_US
dc.citation.spage959en_US
dc.citation.epage962en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000258259800241-
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