@article{43181bcc473c4c1687e1418956322fd1,
title = "A semi-automated analysis method of small sensory nerve fibers in human skin-biopsies",
abstract = "Computerized detection method (CDM) software programs have been extensively developed in the field of astronomy to process and analyze images from nearby bright stars to tiny galaxies at the edge of the Universe. These object-recognition algorithms have potentially broader applications, including the detection and quantification of cutaneous small sensory nerve fibers (SSNFs) found in the dermal and epidermal layers, and in the intervening basement membrane of a skin punch biopsy. Here, we report the use of astronomical software adapted as a semi-automated method to perform density measurements of SSNFs in skin-biopsies imaged by Laser Scanning Confocal Microscopy (LSCM). In the first half of the paper, we present a detailed description of how the CDM is applied to analyze the images of skin punch biopsies. We compare the CDM results to the visual classification results in the second half of the paper. Abbreviations used in the paper, description of each astronomical tools, and their basic settings and how-tos are described in the appendices. Comparison between the normalized CDM and the visual classification results on identical images demonstrates that the two density measurements are comparable. The CDM therefore can be used - at a relatively low cost - as a quick (a few hours for entire processing of a single biopsy with 8-10 scans) and reliable (high-repeatability with minimum user-dependence) method to determine the densities of SSNFs.",
keywords = "Basement membrane, Computerized detection method, Confocal images, Small sensory nerve fibers, Visual classification",
author = "Kazuyuki Tamura and Mager, {Violet A.} and Burnett, {Lindsey A.} and Olson, {John H.} and Brower, {Jeremy B.} and Casano, {Ashley R.} and Debra Baluch and Targovnik, {Jerome H.} and Rogier Windhorst and Herman, {Richard M.}",
note = "Funding Information: We thank Stephen Odewahn (McDonald Observatory, Fort Davis, TX, USA) for helping design the research. R.M.H. acknowledges Dr. William Kennedy (University of Minnesota) for his advice and teaching. This work was supported by a grant from the Palms Clinic and Hospital Corporation Foundation, the Arizona State University College of Liberal Arts and Science, the Arizona State University Department of Physics, the Arizona State University Department of Bioengineering, and the Arizona State University Vice President for Research funds. Funding Information: IRAF is maintained and distributed by the National Optical Astronomy Observatory (NOAO), which is operated by the Association of Universities for Research in Astronomy (AURA), Inc. under the National Science Foundation (NSF). http://iraf.noao.edu/ . ( Stefl, 1990 , and references therein) is a collection of software packages written by astronomers all over the world. The framework of IRAF is provided by National Optical Astronomy Observatory (NOAO), and many individual packages for specific IRAF tasks — most of which are publicly available — are developed and added by astronomers all over the world. IRAF is used to analyze and process images in a pixel array form, or more commonly knows as digital images taken by CCD cameras at astronomical telescopes. Many IRAF tasks use DS9 as an interactive display to analyze FITS images. ",
year = "2010",
month = jan,
day = "15",
doi = "10.1016/j.jneumeth.2009.10.011",
language = "English (US)",
volume = "185",
pages = "325--337",
journal = "Journal of Neuroscience Methods",
issn = "0165-0270",
publisher = "Elsevier",
number = "2",
}