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Medical Imaging in Clinical Applications pp 131–152Cite as

Ensemble Classifiers Construction Using Diversity Measures and Random Subspace Algorithm Combination: Application to Glaucoma Diagnosis

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 651))

Abstract

Glaucoma is a group of eye diseases caused due to excessively high intraocular pressure within the eye. Ensemble classifier construction has attracted increasing interest in the field of pattern recognition and machine learning. Diversity among the classifiers is important factor for each ensemble to be successful. The most widely generation techniques are focused on incorporating the concept of diversity by using different features or training subsets. a classifier selection process becomes an important issue of multiple classifier system by choosing the optimal subset of members that maximizes the performance. The main goal of this study is to develop novel automated glaucoma diagnosis system which analyze and classify retinal images using a novel classification approach based on feature selection and static classifier selection schemes. Experimental results based on RIM-ONE dataset are very encouraging.

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Notes

  1. 1.

    http://www.glaucoma.org/glaucoma/diagnostic-tests.php.

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Author information

Authors and Affiliations

  1. Labged Laboratory, Badji Mokhtar Annaba University, Annaba, Algeria

    Soraya Cheriguene & Nabiha Azizi

  2. Computer Science Department, Badji Mokhtar University, PO BOX 12, 23000, Annaba, Algeria

    Soraya Cheriguene & Nabiha Azizi

  3. Department of Computer Science, Bengal College of Engineering & Technology, Durgapur, India

    Nilanjan Dey

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  1. Soraya Cheriguene
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  2. Nabiha Azizi
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  3. Nilanjan Dey
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Correspondence to Soraya Cheriguene or Nabiha Azizi .

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Editors and Affiliations

  1. Techno India College of Technology, Durgapur, West Bengal, India

    Nilanjan Dey

  2. Professional Colleges (SRMGPC), Shri Ramswaroop Memorial Group of, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Faculty of Computers & Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Cheriguene, S., Azizi, N., Dey, N. (2016). Ensemble Classifiers Construction Using Diversity Measures and Random Subspace Algorithm Combination: Application to Glaucoma Diagnosis. In: Dey, N., Bhateja, V., Hassanien, A. (eds) Medical Imaging in Clinical Applications. Studies in Computational Intelligence, vol 651. Springer, Cham. https://doi.org/10.1007/978-3-319-33793-7_6

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  • DOI: https://doi.org/10.1007/978-3-319-33793-7_6

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