Live neuron morphology automatically reconstructed from multiphoton and confocal imaging data.
We have developed a fully automated procedure for extracting dendritic morphology from multiple three-dimensional image stacks produced by laser scanning microscopy. By eliminating human intervention, we ensure that the results are objective, quickly generated, and accurate. The software suite accounts for typical experimental conditions by reducing background noise, removing pipette artifacts, and aligning multiple overlapping image stacks. The output morphology is appropriate for simulation in compartmental simulation environments. In this report, we validate the utility of this procedure by comparing its performance on live neurons and test specimens with other fully and semiautomated reconstruction tools.
Losavio
Bradley E
BE
Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.
Liang
Yong
Y
Santamaría-Pang
Alberto
A
Kakadiaris
Ioannis A
IA
Colbert
Costa M
CM
Saggau
Peter
P
D000818:Animals; D002196:Capillaries / Q000502:physiology / Q000648:ultrastructure; D003198:Computer Simulation; D003712:Dendrites / Q000502:physiology / Q000648:ultrastructure; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D018613:Microscopy, Confocal / Q000379:methods*; D009474:Neurons / Q000502:physiology* / Q000648:ultrastructure*; D017966:Pyramidal Cells / Q000502:physiology / Q000648:ultrastructure; D051381:Rats; D017207:Rats, Sprague-Dawley; D013569:Synapses / Q000502:physiology