Development of a quantitative semi-automated system for intestinal morphology assessment in Atlantic salmon, using image analysis

• Published in: Aquaculture
• Main Authors: Silva, Polyana F, McGurk, Charles, Thompson, Kim, Jayasuriya, Nilantha, Bron, James
• Other Authors: Skretting Aquaculture Research Centre, Institute of Aquaculture, orcid:0000-0003-3544-0519
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2015
• Subjects: Image analysis; Quantitative histology; Histomorphometric features; Digital histopathology; Intestinal histology; Salmo salar; Atlantic salmon
• Online Access: 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

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