title: Towards automatic reconstruction of dendrite morphology from live neurons.
abstract: The recent advent of optical imaging methods to capture both structural and functional data from living neurons holds the promise of improving our understanding of neuronal function. An important technical advance would be to use computer simulations to determine the optimal locations for high-speed functional imaging and electrical recording on an individual neuron. However, such simulations require a precise reconstruction of the dendritic morphology. Thus, the currently available time-consuming, semi-manual methods for morphological reconstruction prevent integration of cell-specific simulations into the experiments. Our work focuses on implementing a fast, robust method for extracting dendrite morphology from confocal or two-photon images to enable concurrent simulation and functional imaging of individual neurons. We discuss the current implementation of the morphological reconstruction, our approach to validation, and our initial results.
authors.affiliation: Department of CS, University of Houston, Houston, TX, USA.
authors.forename: Christian
authors.initials: C
authors.lastname: Uehara
authors.forename: Costa
authors.initials: C
authors.lastname: Colbert
authors.forename: Peter
authors.initials: P
authors.lastname: Saggau
authors.forename: Ioannis
authors.initials: I
authors.lastname: Kakadiaris