RT Journal Article
SR Electronic
T1 Smart Region-Growing: a novel algorithm for the segmentation of 3D clarified confocal image stacks
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 287029
DO 10.1101/287029
A1 Callara, Alejandro
A1 Magliaro, Chiara
A1 Ahluwalia, Arti
A1 Vanello, Nicola
YR 2018
UL http://biorxiv.org/content/early/2018/03/22/287029.abstract
AB Motivation: Accurately mapping the brain at the micro-scale is still a challenge in cellular neuroscience. While notable success has been reached in the field of tissue clarification and confocal imaging to obtain high-fidelity maps of three-dimensional neuron organization, neuron segmentation is still far away of ground-truth and manual segmentation performed by experts may be needed. The need of an expert is in part related to the limited success of the algorithms and tools performing single-neuron segmentation from 3D microscopic image data available in the State of Art, in part to the non-complete information given by these methods, which typically perform neuron tracing and thus limit the interpretability of results. Results: In this paper, a novel algorithm for segmenting single neurons in their own arrangement within the brain is presented. The algorithm performs a region growing procedure with local thresholds based on the pixel intensity statistics typical of confocal acquisitions of biological samples and described by a mixture model. The algorithm is developed and tested on 3D confocal datasets obtained from clarified tissues. We compare the result of our algorithm with those obtained by manual segmentation performed by 6 different experts in terms of neuron surface area, volume and Sholl profiles. Statistical analysis performed on morphologic features extracted from the segmented structures confirms the feasibility of our approach. Availability: The Smart Region Growing (SmRG) algorithm used in the analysis along with test confocal image stacks is available on request to the authors. Contact: alejandrocallara@gmail.com Supplementary information: Supplementary data are available on request to the authors.