Semi-automated atlas-based analysis of brain histological sections
▶ Semi-automated atlas registration to histological sections. ▶ Quantitative analysis of lesion extent across brain regions. ▶ Automated cell counting algorithm. ▶ Arc mRNA upregulated in frontal cortical regions following exploration. Quantifying the location and/or number of features in a histolog...
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| Veröffentlicht in: | Journal of neuroscience methods 2011-03, Vol.196 (1), p.12-19 |
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| container_title | Journal of neuroscience methods |
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| creator | Kopec, Charles D. Bowers, Amanda C. Pai, Shraddha Brody, Carlos D. |
| description | ▶ Semi-automated atlas registration to histological sections. ▶ Quantitative analysis of lesion extent across brain regions. ▶ Automated cell counting algorithm. ▶
Arc mRNA upregulated in frontal cortical regions following exploration.
Quantifying the location and/or number of features in a histological section of the brain currently requires one to first, manually register a corresponding section from a tissue atlas onto the experimental section and second, count the features. No automated method exists for the first process (registering), and most automated methods for the second process (feature counting) operate reliably only in a high signal-to-noise regime. To reduce experimenter bias and inconsistencies and increase the speed of these analyses, we developed Atlas Fitter, a semi-automated, open-source MatLab-based software package that assists in rapidly registering atlas panels onto histological sections. We also developed CellCounter, a novel fully automated cell counting algorithm that is designed to operate on images with non-uniform background intensities and low signal-to-noise ratios. |
| doi_str_mv | 10.1016/j.jneumeth.2010.12.007 |
| format | Article |
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Arc mRNA upregulated in frontal cortical regions following exploration.
Quantifying the location and/or number of features in a histological section of the brain currently requires one to first, manually register a corresponding section from a tissue atlas onto the experimental section and second, count the features. No automated method exists for the first process (registering), and most automated methods for the second process (feature counting) operate reliably only in a high signal-to-noise regime. To reduce experimenter bias and inconsistencies and increase the speed of these analyses, we developed Atlas Fitter, a semi-automated, open-source MatLab-based software package that assists in rapidly registering atlas panels onto histological sections. We also developed CellCounter, a novel fully automated cell counting algorithm that is designed to operate on images with non-uniform background intensities and low signal-to-noise ratios.</description><identifier>ISSN: 0165-0270</identifier><identifier>EISSN: 1872-678X</identifier><identifier>DOI: 10.1016/j.jneumeth.2010.12.007</identifier><identifier>PMID: 21194546</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Algorithms ; Analysis ; Animals ; Arc ; Automation, Laboratory - methods ; Brain - anatomy & histology ; Brain - metabolism ; Brain Mapping ; Cell Count - methods ; Cell counting ; Cytoskeletal Proteins - metabolism ; Histology ; IEG ; Image Interpretation, Computer-Assisted ; Male ; Mapping ; Nerve Tissue Proteins - metabolism ; Neurons - cytology ; Neurons - metabolism ; Rats ; Rats, Long-Evans ; Software</subject><ispartof>Journal of neuroscience methods, 2011-03, Vol.196 (1), p.12-19</ispartof><rights>2010 Elsevier B.V.</rights><rights>Copyright © 2010 Elsevier B.V. All rights reserved.</rights><rights>2010 Elsevier B.V. All rights reserved. 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c502t-e0d21f678f209b37c715a030cb19db1c400ecaf8c39536ab4597c4a9d293b1263</citedby><cites>FETCH-LOGICAL-c502t-e0d21f678f209b37c715a030cb19db1c400ecaf8c39536ab4597c4a9d293b1263</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0165027010006709$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65534</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21194546$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kopec, Charles D.</creatorcontrib><creatorcontrib>Bowers, Amanda C.</creatorcontrib><creatorcontrib>Pai, Shraddha</creatorcontrib><creatorcontrib>Brody, Carlos D.</creatorcontrib><title>Semi-automated atlas-based analysis of brain histological sections</title><title>Journal of neuroscience methods</title><addtitle>J Neurosci Methods</addtitle><description>▶ Semi-automated atlas registration to histological sections. ▶ Quantitative analysis of lesion extent across brain regions. ▶ Automated cell counting algorithm. ▶
Arc mRNA upregulated in frontal cortical regions following exploration.
Quantifying the location and/or number of features in a histological section of the brain currently requires one to first, manually register a corresponding section from a tissue atlas onto the experimental section and second, count the features. No automated method exists for the first process (registering), and most automated methods for the second process (feature counting) operate reliably only in a high signal-to-noise regime. To reduce experimenter bias and inconsistencies and increase the speed of these analyses, we developed Atlas Fitter, a semi-automated, open-source MatLab-based software package that assists in rapidly registering atlas panels onto histological sections. We also developed CellCounter, a novel fully automated cell counting algorithm that is designed to operate on images with non-uniform background intensities and low signal-to-noise ratios.</description><subject>Algorithms</subject><subject>Analysis</subject><subject>Animals</subject><subject>Arc</subject><subject>Automation, Laboratory - methods</subject><subject>Brain - anatomy & histology</subject><subject>Brain - metabolism</subject><subject>Brain Mapping</subject><subject>Cell Count - methods</subject><subject>Cell counting</subject><subject>Cytoskeletal Proteins - metabolism</subject><subject>Histology</subject><subject>IEG</subject><subject>Image Interpretation, Computer-Assisted</subject><subject>Male</subject><subject>Mapping</subject><subject>Nerve Tissue Proteins - metabolism</subject><subject>Neurons - cytology</subject><subject>Neurons - metabolism</subject><subject>Rats</subject><subject>Rats, Long-Evans</subject><subject>Software</subject><issn>0165-0270</issn><issn>1872-678X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkUFP3DAQhS1EBQvtX0C59ZTt2Inj-IIoCEolpB7aSr1ZE2fCepXE1HaQ-Pd4tYDaEydb9jfPz-8xdsZhzYE3X7br7UzLRGmzFrA7FGsAdcBWvFWibFT755CtMihLEAqO2UmMWwCoNTRH7FhwrmtZNyt2-ZMmV-KS_ISJ-gLTiLHsMO72M45P0cXCD0UX0M3FxsXkR3_vLI5FJJucn-NH9mHAMdKnl_WU_b65_nV1W979-Pb96utdaSWIVBL0gg_Z2SBAd5WyikuECmzHdd9xWwOQxaG1lZZVg10ttbI16l7oquOiqU7Z-V73Yekm6i3NKeBoHoKbMDwZj878fzO7jbn3j6YCJTmXWeDzi0DwfxeKyUwuWhpHnMkv0WjIlpSA6l2ylULnCFuRyWZP2uBjDDS8-eFgdk2ZrXltyuyaMlyY3FQePPv3N29jr9Vk4GIPUM700VEw0TqaLfUu5ORN7917bzwD25ipZQ</recordid><startdate>20110315</startdate><enddate>20110315</enddate><creator>Kopec, Charles D.</creator><creator>Bowers, Amanda C.</creator><creator>Pai, Shraddha</creator><creator>Brody, Carlos D.</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>7X8</scope><scope>7TK</scope><scope>5PM</scope></search><sort><creationdate>20110315</creationdate><title>Semi-automated atlas-based analysis of brain histological sections</title><author>Kopec, Charles D. ; Bowers, Amanda C. ; Pai, Shraddha ; Brody, Carlos D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c502t-e0d21f678f209b37c715a030cb19db1c400ecaf8c39536ab4597c4a9d293b1263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Analysis</topic><topic>Animals</topic><topic>Arc</topic><topic>Automation, Laboratory - methods</topic><topic>Brain - anatomy & histology</topic><topic>Brain - metabolism</topic><topic>Brain Mapping</topic><topic>Cell Count - methods</topic><topic>Cell counting</topic><topic>Cytoskeletal Proteins - metabolism</topic><topic>Histology</topic><topic>IEG</topic><topic>Image Interpretation, Computer-Assisted</topic><topic>Male</topic><topic>Mapping</topic><topic>Nerve Tissue Proteins - metabolism</topic><topic>Neurons - cytology</topic><topic>Neurons - metabolism</topic><topic>Rats</topic><topic>Rats, Long-Evans</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kopec, Charles D.</creatorcontrib><creatorcontrib>Bowers, Amanda C.</creatorcontrib><creatorcontrib>Pai, Shraddha</creatorcontrib><creatorcontrib>Brody, Carlos D.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Neurosciences Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of neuroscience methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kopec, Charles D.</au><au>Bowers, Amanda C.</au><au>Pai, Shraddha</au><au>Brody, Carlos D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Semi-automated atlas-based analysis of brain histological sections</atitle><jtitle>Journal of neuroscience methods</jtitle><addtitle>J Neurosci Methods</addtitle><date>2011-03-15</date><risdate>2011</risdate><volume>196</volume><issue>1</issue><spage>12</spage><epage>19</epage><pages>12-19</pages><issn>0165-0270</issn><eissn>1872-678X</eissn><abstract>▶ Semi-automated atlas registration to histological sections. ▶ Quantitative analysis of lesion extent across brain regions. ▶ Automated cell counting algorithm. ▶
Arc mRNA upregulated in frontal cortical regions following exploration.
Quantifying the location and/or number of features in a histological section of the brain currently requires one to first, manually register a corresponding section from a tissue atlas onto the experimental section and second, count the features. No automated method exists for the first process (registering), and most automated methods for the second process (feature counting) operate reliably only in a high signal-to-noise regime. To reduce experimenter bias and inconsistencies and increase the speed of these analyses, we developed Atlas Fitter, a semi-automated, open-source MatLab-based software package that assists in rapidly registering atlas panels onto histological sections. We also developed CellCounter, a novel fully automated cell counting algorithm that is designed to operate on images with non-uniform background intensities and low signal-to-noise ratios.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>21194546</pmid><doi>10.1016/j.jneumeth.2010.12.007</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of neuroscience methods, 2011-03, Vol.196 (1), p.12-19 |
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| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals Complete |
| subjects | Algorithms Analysis Animals Arc Automation, Laboratory - methods Brain - anatomy & histology Brain - metabolism Brain Mapping Cell Count - methods Cell counting Cytoskeletal Proteins - metabolism Histology IEG Image Interpretation, Computer-Assisted Male Mapping Nerve Tissue Proteins - metabolism Neurons - cytology Neurons - metabolism Rats Rats, Long-Evans Software |
| title | Semi-automated atlas-based analysis of brain histological sections |
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