An Automated Assay for the Evaluation of Mortality in Fish Embryo

International audience Waterways are often first and severely affected by pollution. In this context, fish embryos – which constitute a good model for sensitivity to chemicals – are widely used in environmental toxicology studies. Such studies are devoted to the analysis of a wide spectrum of physio...

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Bibliographic Details
Main Authors: Puybareau, Élodie, Léonard, Marc, Talbot, Hugues
Other Authors: Laboratoire d'Informatique Gaspard-Monge (LIGM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), L'Oréal Research, L'OREAL
Format: Conference Object
Language:English
Published: HAL CCSD 2015
Subjects:
Toxicology
medaka
image stabilisation
change detection
connected filtering
[INFO]Computer Science [cs]
Iceland
Online Access:https://hal-upec-upem.archives-ouvertes.fr/hal-01154543
https://hal-upec-upem.archives-ouvertes.fr/hal-01154543/document
https://hal-upec-upem.archives-ouvertes.fr/hal-01154543/file/paper40.pdf
https://doi.org/10.1007/978-3-319-18720-4_10
Description
Summary:International audience Waterways are often first and severely affected by pollution. In this context, fish embryos – which constitute a good model for sensitivity to chemicals – are widely used in environmental toxicology studies. Such studies are devoted to the analysis of a wide spectrum of physiological parameters, for instance mortality ratio. In this article, we develop an assay to determine the mortality rate of Medaka embryo. Based on video sequences, our purpose is to obtain reliable, repeatable results in a fully automated fashion. To reach that challenging goal, we develop an efficient morphological pipeline that analyses image sequences in a multiscale paradigm, from the global scene to the embryo, and then to its heart, finally analysing its putative motion, characterized by intensity variations. Our pipeline, based on robust morphological operators, has a low computational cost, and was experimentally assessed on a dataset consisting of 660 images, providing a success ratio higher than 99%.

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