A semi-automated analysis method of small sensory nerve fibers in human skin-biopsies
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 th...
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creator | Tamura, Kazuyuki Mager, Violet A. Burnett, Lindsey A. Olson, John H. Brower, Jeremy B. Casano, Ashley R. Baluch, Debra P. Targovnik, Jerome H. Windhorst, Rogier A. Herman, Richard M. |
description | 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. |
doi_str_mv | 10.1016/j.jneumeth.2009.10.011 |
format | Article |
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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.</description><identifier>ISSN: 0165-0270</identifier><identifier>EISSN: 1872-678X</identifier><identifier>DOI: 10.1016/j.jneumeth.2009.10.011</identifier><identifier>PMID: 19852982</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Basement membrane ; Basement Membrane - cytology ; Biopsy - methods ; Cohort Studies ; Computerized detection method ; Confocal images ; Humans ; Image Interpretation, Computer-Assisted - methods ; Microscopy, Confocal - methods ; Nerve Fibers ; Signal Processing, Computer-Assisted ; Skin - cytology ; Skin - innervation ; Small sensory nerve fibers ; Software ; Visual classification</subject><ispartof>Journal of neuroscience methods, 2010-01, Vol.185 (2), p.325-337</ispartof><rights>2009 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c366t-1049e520cbb613a27e579d82454b8c7bf15f6f5ac25b6245143190a1abe9d0303</citedby><cites>FETCH-LOGICAL-c366t-1049e520cbb613a27e579d82454b8c7bf15f6f5ac25b6245143190a1abe9d0303</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0165027009005676$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27903,27904,65309</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19852982$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tamura, Kazuyuki</creatorcontrib><creatorcontrib>Mager, Violet A.</creatorcontrib><creatorcontrib>Burnett, Lindsey A.</creatorcontrib><creatorcontrib>Olson, John H.</creatorcontrib><creatorcontrib>Brower, Jeremy B.</creatorcontrib><creatorcontrib>Casano, Ashley R.</creatorcontrib><creatorcontrib>Baluch, Debra P.</creatorcontrib><creatorcontrib>Targovnik, Jerome H.</creatorcontrib><creatorcontrib>Windhorst, Rogier A.</creatorcontrib><creatorcontrib>Herman, Richard M.</creatorcontrib><title>A semi-automated analysis method of small sensory nerve fibers in human skin-biopsies</title><title>Journal of neuroscience methods</title><addtitle>J Neurosci Methods</addtitle><description>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.</description><subject>Basement membrane</subject><subject>Basement Membrane - cytology</subject><subject>Biopsy - methods</subject><subject>Cohort Studies</subject><subject>Computerized detection method</subject><subject>Confocal images</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Microscopy, Confocal - methods</subject><subject>Nerve Fibers</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Skin - cytology</subject><subject>Skin - innervation</subject><subject>Small sensory nerve fibers</subject><subject>Software</subject><subject>Visual classification</subject><issn>0165-0270</issn><issn>1872-678X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE9r2zAYh8VYWdNsXyHo1JtTSY5k-7YS1m5Q6KWB3YQkvybKbCnTawfy7SuTlB13euHH8_57CFlxtuaMq4fD-hBgGmDcrwVjTQ7XjPNPZMHrShSqqn9_JosMyoKJit2SO8QDY2zTMPWF3PKmlqKpxYLsHinC4AszjXEwI7TUBNOf0SOdh8eWxo7iYPo-cwFjOtMA6QS08xYSUh_ofhpMoPjHh8L6eEQP-JXcdKZH-HatS7J7-vG2_Vm8vD7_2j6-FK5Uaix4vgekYM5axUsjKpBV09ZiIze2dpXtuOxUJ40T0qqc8k3JG2a4sdC0rGTlktxf5h5T_DsBjnrw6KDvTYA4oRZciKqSM6guoEsRMUGnj8kPJp01Z3oWqg_6Q6iehc55FpobV9cNkx2g_dd2NZiB7xcA8p8nD0mj8xActD6BG3Ub_f92vAMO84rp</recordid><startdate>20100115</startdate><enddate>20100115</enddate><creator>Tamura, Kazuyuki</creator><creator>Mager, Violet A.</creator><creator>Burnett, Lindsey A.</creator><creator>Olson, John H.</creator><creator>Brower, Jeremy B.</creator><creator>Casano, Ashley R.</creator><creator>Baluch, Debra P.</creator><creator>Targovnik, Jerome H.</creator><creator>Windhorst, Rogier A.</creator><creator>Herman, Richard M.</creator><general>Elsevier B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope></search><sort><creationdate>20100115</creationdate><title>A semi-automated analysis method of small sensory nerve fibers in human skin-biopsies</title><author>Tamura, Kazuyuki ; Mager, Violet A. ; Burnett, Lindsey A. ; Olson, John H. ; Brower, Jeremy B. ; Casano, Ashley R. ; Baluch, Debra P. ; Targovnik, Jerome H. ; Windhorst, Rogier A. ; Herman, Richard M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c366t-1049e520cbb613a27e579d82454b8c7bf15f6f5ac25b6245143190a1abe9d0303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Basement membrane</topic><topic>Basement Membrane - cytology</topic><topic>Biopsy - methods</topic><topic>Cohort Studies</topic><topic>Computerized detection method</topic><topic>Confocal images</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Microscopy, Confocal - methods</topic><topic>Nerve Fibers</topic><topic>Signal Processing, Computer-Assisted</topic><topic>Skin - cytology</topic><topic>Skin - innervation</topic><topic>Small sensory nerve fibers</topic><topic>Software</topic><topic>Visual classification</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tamura, Kazuyuki</creatorcontrib><creatorcontrib>Mager, Violet A.</creatorcontrib><creatorcontrib>Burnett, Lindsey A.</creatorcontrib><creatorcontrib>Olson, John H.</creatorcontrib><creatorcontrib>Brower, Jeremy B.</creatorcontrib><creatorcontrib>Casano, Ashley R.</creatorcontrib><creatorcontrib>Baluch, Debra P.</creatorcontrib><creatorcontrib>Targovnik, Jerome H.</creatorcontrib><creatorcontrib>Windhorst, Rogier A.</creatorcontrib><creatorcontrib>Herman, Richard M.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><jtitle>Journal of neuroscience methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tamura, Kazuyuki</au><au>Mager, Violet A.</au><au>Burnett, Lindsey A.</au><au>Olson, John H.</au><au>Brower, Jeremy B.</au><au>Casano, Ashley R.</au><au>Baluch, Debra P.</au><au>Targovnik, Jerome H.</au><au>Windhorst, Rogier A.</au><au>Herman, Richard M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A semi-automated analysis method of small sensory nerve fibers in human skin-biopsies</atitle><jtitle>Journal of neuroscience methods</jtitle><addtitle>J Neurosci Methods</addtitle><date>2010-01-15</date><risdate>2010</risdate><volume>185</volume><issue>2</issue><spage>325</spage><epage>337</epage><pages>325-337</pages><issn>0165-0270</issn><eissn>1872-678X</eissn><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.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>19852982</pmid><doi>10.1016/j.jneumeth.2009.10.011</doi><tpages>13</tpages></addata></record> |
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subjects | Basement membrane Basement Membrane - cytology Biopsy - methods Cohort Studies Computerized detection method Confocal images Humans Image Interpretation, Computer-Assisted - methods Microscopy, Confocal - methods Nerve Fibers Signal Processing, Computer-Assisted Skin - cytology Skin - innervation Small sensory nerve fibers Software Visual classification |
title | A semi-automated analysis method of small sensory nerve fibers in human skin-biopsies |
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