Automated algorithms for multiscale morphometry of neuronal dendrites.
We describe the synthesis of automated neuron branching morphology and spine detection algorithms to provide multiscale three-dimensional morphological analysis of neurons. The resulting software is applied to the analysis of a high-resolution (0.098 microm x 0.098 microm x 0.081 microm) image of an entire pyramidal neuron from layer III of the superior temporal cortex in rhesus macaque monkey. The approach provides a highly automated, complete morphological analysis of the entire neuron; each dendritic branch segment is characterized by several parameters, including branch order, length, and radius as a function of distance along the branch, as well as by the locations, lengths, shape classification (e.g., mushroom, stubby, thin), and density distribution of spines on the branch. Results for this automated analysis are compared to published results obtained by other computer-assisted manual means.
Weaver
Christina M
CM
Department of Biomathematical Sciences and Computational Neurobiology and Imaging Center, Mount Sinai School of Medicine, New York, NY 10029, USA. christina@camelot.mssm.edu
Hof
Patrick R
PR
Wearne
Susan L
SL
Lindquist
W Brent
WB
D000465:Algorithms; D000818:Animals; D002452:Cell Count / Q000379:methods; D003712:Dendrites / Q000502:physiology*; D001330:Electronic Data Processing / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007211:Indoles / Q000378:metabolism; D008251:Macaca; D018613:Microscopy, Confocal / Q000379:methods; D019579:Neocortex / Q000166:cytology*; D017966:Pyramidal Cells / Q000166:cytology* / Q000378:metabolism
D007211:Indoles; C007293:DAPI