| Literature DB >> 25574428 |
Steve Bégin1, Olivier Dupont-Therrien2, Erik Bélanger1, Amy Daradich1, Sophie Laffray2, Yves De Koninck3, Daniel C Côté1.
Abstract
A fully automated method for large-scale segmentation of nerve fibers from coherent anti-Stokes Raman scattering (CARS) microscopy images is presented. The method is specifically designed for CARS images of transverse cross sections of nervous tissue but is also suitable for use with standard light microscopy images. After a detailed description of the two-part segmentation algorithm, its accuracy is quantified by comparing the resulting binary images to manually segmented images. We then demonstrate the ability of our method to retrieve morphological data from CARS images of nerve tissue. Finally, we present the segmentation of a large mosaic of CARS images covering more than half the area of a mouse spinal cord cross section and show evidence of clusters of neurons with similar g-ratios throughout the spinal cord.Entities:
Keywords: (000.1430) Biology and medicine; (100.2960) Image analysis; (170.3880) Medical and biological imaging; (170.4580) Optical diagnostics for medicine; (180.4315) Nonlinear microscopy; (180.6900) Three-dimensional microscopy; (300.6230) Spectroscopy, coherent anti-Stokes Raman scattering
Year: 2014 PMID: 25574428 PMCID: PMC4285595 DOI: 10.1364/BOE.5.004145
Source DB: PubMed Journal: Biomed Opt Express ISSN: 2156-7085 Impact factor: 3.732