Author:
He Wenyun,Hamilton Thomas A.,Cohen Andrew R.,Holmes Timothy J.,Pace Christopher,Szarowski Donald H.,Turner James N.,Roysam Badrinath
Abstract
Automated three-dimensional (3-D) image analysis methods are
presented for tracing of dye-injected neurons imaged by fluorescence
confocal microscopy and HRP-stained neurons imaged by transmitted-light
brightfield microscopy. An improved algorithm for adaptive 3-D
skeletonization of noisy images enables the tracing. This algorithm
operates by performing connectivity testing over large N × N
× N voxel neighborhoods exploiting the sparseness of the
structures of interest, robust surface detection that improves upon
classical vacant neighbor schemes, improved handling of process ends or
tips based on shape collapse prevention, and thickness-adaptive
thinning. The confocal image stacks were skeletonized directly. The
brightfield stacks required 3-D deconvolution. The results of
skeletonization were analyzed to extract a graph representation.
Topological and metric analyses can be carried out using this
representation. A semiautomatic method was developed for reconnection
of dendritic fragments that are disconnected due to insufficient dye
penetration, an imaging deficiency, or skeletonization errors.
Publisher
Cambridge University Press (CUP)
Cited by
68 articles.
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