Towards an Automated Zebrafish-based Toxicity Test Model Using Machine Learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096565" target="_blank" >RIV/61989100:27240/15:86096565 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.procs.2015.09.008" target="_blank" >http://dx.doi.org/10.1016/j.procs.2015.09.008</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.procs.2015.09.008" target="_blank" >10.1016/j.procs.2015.09.008</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Towards an Automated Zebrafish-based Toxicity Test Model Using Machine Learning

Popis výsledku v původním jazyce

Zebrafish animal is considered as one of the most suitable animals to test toxicity of compounds due many features such as transparency and a large number of embryos produced in each mating. The main problem of the zebrafish-based toxicity test is the manual inspection of thousands of animals images in different phases and this is not feasible enough for the analysis, i.e. it is slow and may be inaccurate process. To help addressing this problem, in this paper, an automated classification of alive (healthy) and coagulant (died because of toxic compounds) zebrafish embryos are proposed. The embryos' images are used to extract some features using the Segmentation-based Fractal Texture Analysis (SFTA) technique. The Rotation Forest classifier is then usedto match between testing and training features (i.e. to classify alive and coagulant embryos). The experiments have proved that choosing threshold value of SFTA technique and the size of the rotation forest classifier have a great impact

Název v anglickém jazyce

Towards an Automated Zebrafish-based Toxicity Test Model Using Machine Learning

Popis výsledku anglicky

Zebrafish animal is considered as one of the most suitable animals to test toxicity of compounds due many features such as transparency and a large number of embryos produced in each mating. The main problem of the zebrafish-based toxicity test is the manual inspection of thousands of animals images in different phases and this is not feasible enough for the analysis, i.e. it is slow and may be inaccurate process. To help addressing this problem, in this paper, an automated classification of alive (healthy) and coagulant (died because of toxic compounds) zebrafish embryos are proposed. The embryos' images are used to extract some features using the Segmentation-based Fractal Texture Analysis (SFTA) technique. The Rotation Forest classifier is then usedto match between testing and training features (i.e. to classify alive and coagulant embryos). The experiments have proved that choosing threshold value of SFTA technique and the size of the rotation forest classifier have a great impact

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Procedia Computer Science. Volume 65

ISBN

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ISSN

1877-0509

e-ISSN

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Počet stran výsledku

9

Strana od-do

643-651

Název nakladatele

Elsevier

Místo vydání

Amsterdam

Místo konání akce

Praha

Datum konání akce

20. 4. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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