Spatial registration of neuron morphologies based on maximization of volume overlap.

ABSTRACT:

Background

Morphological features are widely used in the study of neuronal function and pathology. Invertebrate neurons are often structurally stereotypical, showing little variance in gross spatial features but larger variance in their fine features. Such variability can be quantified using detailed spatial analysis, which however requires the morphologies to be registered to a common frame of reference.

Results

We outline here new algorithms - Reg-MaxS and Reg-MaxS-N - for co-registering pairs and groups of morphologies, respectively. Reg-MaxS applies a sequence of translation, rotation and scaling transformations, estimating at each step the transformation parameters that maximize spatial overlap between the volumes occupied by the morphologies. We test this algorithm wit

SUBMITTER: Kumaraswamy A 

PROVIDER: S-EPMC5907365 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature