AUTHOR=Callara Alejandro Luis , Magliaro Chiara , Ahluwalia Arti , Vanello Nicola TITLE=A Smart Region-Growing Algorithm for Single-Neuron Segmentation From Confocal and 2-Photon Datasets JOURNAL=Frontiers in Neuroinformatics VOLUME=14 YEAR=2020 URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2020.00009 DOI=10.3389/fninf.2020.00009 ISSN=1662-5196 ABSTRACT=

Accurately digitizing the brain at the micro-scale is crucial for investigating brain structure-function relationships and documenting morphological alterations due to neuropathies. Here we present a new Smart Region Growing algorithm (SmRG) for the segmentation of single neurons in their intricate 3D arrangement within the brain. Its Region Growing procedure is based on a homogeneity predicate determined by describing the pixel intensity statistics of confocal acquisitions with a mixture model, enabling an accurate reconstruction of complex 3D cellular structures from high-resolution images of neural tissue. The algorithm’s outcome is a 3D matrix of logical values identifying the voxels belonging to the segmented structure, thus providing additional useful volumetric information on neurons. To highlight the algorithm’s full potential, we compared its performance in terms of accuracy, reproducibility, precision and robustness of 3D neuron reconstructions based on microscopic data from different brain locations and imaging protocols against both manual and state-of-the-art reconstruction tools.