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A survey of neural network based automated systems for human chromosome classification

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Abstract

Chromosome classification and karyotype establishment are important procedures for genetic diseases diagnosis. Various computer-aided systems have been developed to automate this tedious and time consuming task, which is performed manually in most cytogenetic laboratories. This paper provides a comprehensive review of past and recent research in the area of automatic chromosome classification systems. We start by reviewing methods for feature extraction, followed by a neural network based chromosome classifiers survey. We sum-up various techniques and methods in this area of research and discuss important issues and outcomes within each study for both chromosome feature extraction and classification. Although the ANN based chromosome classifiers are the main topic of this survey, a number of classifiers based on other algorithms are exposed to give an overall idea about additional techniques employed in chromosome classification.

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Authors and Affiliations

  1. Département d’électronique, Ecole Nationale Polytechnique, 10 Avenue Hacen Badi, BP 182, El Harrach, Alger, Algeria

    Faroudja Abid & Latifa Hamami

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  1. Faroudja Abid
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  2. Latifa Hamami
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Correspondence to Faroudja Abid.

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Abid, F., Hamami, L. A survey of neural network based automated systems for human chromosome classification. Artif Intell Rev 49, 41–56 (2018). https://doi.org/10.1007/s10462-016-9515-5

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