A semi-automated analysis method of small sensory nerve fibers in human skin-biopsies

Kazuyuki Tamura, Violet A. Mager, Lindsey A. Burnett, John H. Olson, Jeremy B. Brower, Ashley R. Casano, Debra P. Baluch, Jerome H. Targovnik, Rogier A. Windhorst, Richard M. Herman

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)325-337
Number of pages13
JournalJournal of Neuroscience Methods
Issue number2
StatePublished - Jan 15 2010

All Science Journal Classification (ASJC) codes

  • General Neuroscience


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