M. Mirto, Laura Conte, G. Aloisio, C. Distante, Pietro Vecchio, Alessandra De Giovanni
{"title":"Measuring cells in phytoplankton images","authors":"M. Mirto, Laura Conte, G. Aloisio, C. Distante, Pietro Vecchio, Alessandra De Giovanni","doi":"10.1109/HPCSim.2015.7237085","DOIUrl":null,"url":null,"abstract":"Phytoplankton is a quality element for determining the ecological status of transitional water ecosystems. In routine analysis, bio-volume and surface area of phytoplankton are the most studied morphometric descriptors. Bio-volume can be estimated by comparing the algae with similar three-dimensional geometric forms and determining their volume, by measuring the linear dimensions required for its calculation with images acquired by an inverse microscope. Software such as LUCIA-G (Laboratory Imaging) determines, in an automatic way, only the linear dimensions of simple forms such as circle or ellipse, approximated at a given algae, whereas complex forms require the intervention of an operator by selecting the start and end points of linear dimensions with obvious introduction of human error. In this paper, we propose a novel methodology for detecting phytoplankton algae and by measuring linear dimensions of 42 geometrical forms to automatically compute their area and bio-volume, that has been implemented in a novel software, named LUISA, for image analysis.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSim.2015.7237085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Phytoplankton is a quality element for determining the ecological status of transitional water ecosystems. In routine analysis, bio-volume and surface area of phytoplankton are the most studied morphometric descriptors. Bio-volume can be estimated by comparing the algae with similar three-dimensional geometric forms and determining their volume, by measuring the linear dimensions required for its calculation with images acquired by an inverse microscope. Software such as LUCIA-G (Laboratory Imaging) determines, in an automatic way, only the linear dimensions of simple forms such as circle or ellipse, approximated at a given algae, whereas complex forms require the intervention of an operator by selecting the start and end points of linear dimensions with obvious introduction of human error. In this paper, we propose a novel methodology for detecting phytoplankton algae and by measuring linear dimensions of 42 geometrical forms to automatically compute their area and bio-volume, that has been implemented in a novel software, named LUISA, for image analysis.