Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis
Virtual histology, the process of assessing digital images of histological slides, is gaining momentum in modern histopathology and digital image acquisition systems are becoming commonplace. Associated image processing and analysis methods can potentially complement traditional histological assessm...
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ftunivstirling:oai:dspace.stir.ac.uk:1893/28750 2023-05-15T15:32:15+02:00 Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis Silva, Polyana F McGurk, Charles Thompson, Kim Jayasuriya, Nilantha Bron, James Skretting Aquaculture Research Centre Institute of Aquaculture orcid:0000-0003-3544-0519 2015-05-01 application/pdf http://hdl.handle.net/1893/28750 https://doi.org/10.1016/j.aquaculture.2015.02.034 http://dspace.stir.ac.uk/bitstream/1893/28750/1/A6_Development%20of%20a%20quantitative.pdf en eng Elsevier Silva PF, McGurk C, Thompson K, Jayasuriya N & Bron J (2015) Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis. Aquaculture, 442, pp. 100-111. https://doi.org/10.1016/j.aquaculture.2015.02.034 http://hdl.handle.net/1893/28750 doi:10.1016/j.aquaculture.2015.02.034 WOS:000351837100016 2-s2.0-84924690209 1077791 http://dspace.stir.ac.uk/bitstream/1893/28750/1/A6_Development%20of%20a%20quantitative.pdf The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. http://www.rioxx.net/licenses/under-embargo-all-rights-reserved 2999-12-31 [A6_Development of a quantitative.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work. Image analysis Quantitative histology Histomorphometric features Digital histopathology Intestinal histology Salmo salar Journal Article VoR - Version of Record 2015 ftunivstirling https://doi.org/10.1016/j.aquaculture.2015.02.034 2022-06-13T18:41:42Z Virtual histology, the process of assessing digital images of histological slides, is gaining momentum in modern histopathology and digital image acquisition systems are becoming commonplace. Associated image processing and analysis methods can potentially complement traditional histological assessment methodologies.Image analysis of digitised histological sections, can provide a practical means for quantifying and helping interpretation of functional alterations in an objective and reproducible fashion. This study focused on the development of a practical and time-efficient image capture, processing and analysis pipeline, employing advanced image analysis that was able to identify features of salmon intestine histological sections in a quantitative manner. Through standardisation of the sampling and preparation methodologies, staining protocols and digital capture thresholds and techniques, this assessment system has proven to be an efficient, accurate and objective method, having consistent data outputs when the analysis is performed by different observers with varying levels of expertise in histopathological assessment Article in Journal/Newspaper Atlantic salmon Salmo salar University of Stirling: Stirling Digital Research Repository Aquaculture 442 100 111 |
institution |
Open Polar |
collection |
University of Stirling: Stirling Digital Research Repository |
op_collection_id |
ftunivstirling |
language |
English |
topic |
Image analysis Quantitative histology Histomorphometric features Digital histopathology Intestinal histology Salmo salar |
spellingShingle |
Image analysis Quantitative histology Histomorphometric features Digital histopathology Intestinal histology Salmo salar Silva, Polyana F McGurk, Charles Thompson, Kim Jayasuriya, Nilantha Bron, James Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis |
topic_facet |
Image analysis Quantitative histology Histomorphometric features Digital histopathology Intestinal histology Salmo salar |
description |
Virtual histology, the process of assessing digital images of histological slides, is gaining momentum in modern histopathology and digital image acquisition systems are becoming commonplace. Associated image processing and analysis methods can potentially complement traditional histological assessment methodologies.Image analysis of digitised histological sections, can provide a practical means for quantifying and helping interpretation of functional alterations in an objective and reproducible fashion. This study focused on the development of a practical and time-efficient image capture, processing and analysis pipeline, employing advanced image analysis that was able to identify features of salmon intestine histological sections in a quantitative manner. Through standardisation of the sampling and preparation methodologies, staining protocols and digital capture thresholds and techniques, this assessment system has proven to be an efficient, accurate and objective method, having consistent data outputs when the analysis is performed by different observers with varying levels of expertise in histopathological assessment |
author2 |
Skretting Aquaculture Research Centre Institute of Aquaculture orcid:0000-0003-3544-0519 |
format |
Article in Journal/Newspaper |
author |
Silva, Polyana F McGurk, Charles Thompson, Kim Jayasuriya, Nilantha Bron, James |
author_facet |
Silva, Polyana F McGurk, Charles Thompson, Kim Jayasuriya, Nilantha Bron, James |
author_sort |
Silva, Polyana F |
title |
Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis |
title_short |
Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis |
title_full |
Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis |
title_fullStr |
Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis |
title_full_unstemmed |
Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis |
title_sort |
development of a quantitative semi-automated system for intestinal morphology assessment in atlantic salmon, using image analysis |
publisher |
Elsevier |
publishDate |
2015 |
url |
http://hdl.handle.net/1893/28750 https://doi.org/10.1016/j.aquaculture.2015.02.034 http://dspace.stir.ac.uk/bitstream/1893/28750/1/A6_Development%20of%20a%20quantitative.pdf |
genre |
Atlantic salmon Salmo salar |
genre_facet |
Atlantic salmon Salmo salar |
op_relation |
Silva PF, McGurk C, Thompson K, Jayasuriya N & Bron J (2015) Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis. Aquaculture, 442, pp. 100-111. https://doi.org/10.1016/j.aquaculture.2015.02.034 http://hdl.handle.net/1893/28750 doi:10.1016/j.aquaculture.2015.02.034 WOS:000351837100016 2-s2.0-84924690209 1077791 http://dspace.stir.ac.uk/bitstream/1893/28750/1/A6_Development%20of%20a%20quantitative.pdf |
op_rights |
The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. http://www.rioxx.net/licenses/under-embargo-all-rights-reserved 2999-12-31 [A6_Development of a quantitative.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work. |
op_doi |
https://doi.org/10.1016/j.aquaculture.2015.02.034 |
container_title |
Aquaculture |
container_volume |
442 |
container_start_page |
100 |
op_container_end_page |
111 |
_version_ |
1766362764960333824 |