Zebrafish Larvae Classification based on Decision Tree Model: A Comparative Analysis

AlSaaidah, Bayan, Al-Nuaimy, Waleed ORCID: 0000-0001-8927-2368, Al-Hadidi, Mohammed Rasoul and Young, Iain ORCID: 0000-0002-9502-6216 (2018) Zebrafish Larvae Classification based on Decision Tree Model: A Comparative Analysis. Advances in Science, Technology and Engineering Systems Journal, 3 (4). pp. 347-353.

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Official URL: http://dx.doi.org/10.25046/aj030435

Abstract

Screening the abnormal development of the zebrafish embryos before and after being hatched for a large number of samples is always carried out manually. The manual process is presented as a tedious work and low-throughput. The single female fish produce hundreds of eggs in every single mating process, the samples of the zebrafish embryos should be studied and analyzed within a short time according to the fast response of their bodies and the ethical regulations. The limited number of the automatic screening systems for aquaculture experiments encourage researchers to find out a high-throughput screening systems with a fast prediction results according to the large number of experimental samples. This work aims to design an automatic segmentation, classification system for zebrafish eggs using two ways for feature extraction and also a classifier. Using the whole image generally with several feature vectors useful for detection process, this way does not depend on the type of the image. The second way focus on specific characteristics of the image which are the colour and the texture features relating to the system purposes. Two different ways for feature extraction integrated by the Classification And Regression Tree (CART) classifier are proposed, analysed, and qualified by comparing the two methods performance and accuracies. The experimental results for zebrafish eggs classification into three distinct classes: live egg, live embryo, dead egg show higher accuracy using the texture and colour feature extraction with an accuracy 97% without any manual intervention. The proposed system results very promising for another type of classification such as the zebrafish larva deformations.

Item Type:	Article
Depositing User:	Symplectic Admin
Date Deposited:	10 May 2019 11:15
Last Modified:	19 Jan 2023 00:46
DOI:	10.25046/aj030435
Open Access URL:	https://astesj.com/v03/i04/p35/
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3040613