NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks

Marwan Abdellah, Juan Hernando, Stefan Eilemann, Samuel Lapere, Nicolas Antille, Henry Markram, Felix Schürmann

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Motivation \nFrom image stacks to computational models, processing digital representations of neuronal morphologies is essential to neuroscientific research. Workflows involve various techniques and tools, leading in certain cases to convoluted and fragmented pipelines. The existence of an integrated, extensible and free framework for processing, analysis and visualization of those morphologies is a challenge that is still largely unfulfilled. \n \nResults \nWe present NeuroMorphoVis, an interactive, extensible and cross-platform framework for building, visualizing and analyzing digital reconstructions of neuronal morphology skeletons extracted from microscopy stacks. Our framework is capable of detecting and repairing tracing artifacts, allowing the generation of high fidelity surface meshes and high resolution volumetric models for simulation and in silico imaging studies. The applicability of NeuroMorphoVis is demonstrated with two case studies. The first simulates the construction of three-dimensional profiles of neuronal somata and the other highlights how the framework is leveraged to create volumetric models of neuronal circuits for simulating different types of in vitro imaging experiments.
Original languageEnglish (US)
Pages (from-to)i574-i582
Number of pages1
JournalBioinformatics
Volume34
Issue number13
DOIs
StatePublished - Jun 27 2018
Externally publishedYes

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