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Four discriminant models for detecting keratoconus pattern using Zernike coefficients of corneal aberrations

  • Clinical Investigation
  • Published:
Japanese Journal of Ophthalmology Aims and scope Submit manuscript

Abstract

Purpose

We compared the ability of four discriminant models to detect keratoconus (KC) using Zernike coefficients of corneal aberrations.

Methods

We studied 51 eyes with KC, 46 with KC suspect, 50 after laser in situ keratomileusis, and 65 normal eyes. Four statistical discriminant analyses—linear discriminant analysis, k-nearest neighbor algorithm, Mahalanobis distance method, and neural network method—were performed using Zernike coefficients of corneal aberrations obtained by a Placido-based topographer. The detection scheme was constructed using a training set of data from one half of the randomly selected study participants, and performance was evaluated by a validation set in the other half.

Results

Performance of the four models was different when <12 explanatory variables were included. Performance using the 2nd- to 4th-order Zernike terms did not differ significantly among models; average accuracy was 79 %.

Conclusions

Determining explanatory variables of Zernike expansion coefficients of the corneal topography in discriminant models may contribute to improving accuracy of KC detection over the discriminant model, as appropriate selection of explanatory variables gave similar results despite different discriminant models.

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Acknowledgments

Supported in part by the Japan Ministry of Education, Science, Sports, and Culture, Tokyo, Japan (No. 24592669).

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Authors and Affiliations

  1. Research Institute, Optics Laboratory, Topcon Corporation, Tokyo, Japan

    Makoto Saika & Yoko Hirohara

  2. Department of Ophthalmology, Osaka University Graduate School of Medicine, Room E7, 2-2 Yamadaoka, Suita, 565-0871, Japan

    Naoyuki Maeda & Kohji Nishida

  3. Department of Applied Visual Science, Osaka University Graduate School of Medicine, Suita, Japan

    Makoto Saika, Yoko Hirohara & Takashi Fujikado

  4. Innovative Research Initiatives, Tokyo Institute of Technology, Kanagawa, Japan

    Toshifumi Mihashi

Authors
  1. Makoto Saika
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  2. Naoyuki Maeda
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  3. Yoko Hirohara
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  4. Toshifumi Mihashi
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  5. Takashi Fujikado
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  6. Kohji Nishida
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Correspondence to Naoyuki Maeda.

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Saika, M., Maeda, N., Hirohara, Y. et al. Four discriminant models for detecting keratoconus pattern using Zernike coefficients of corneal aberrations. Jpn J Ophthalmol 57, 503–509 (2013). https://doi.org/10.1007/s10384-013-0269-1

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  • DOI: https://doi.org/10.1007/s10384-013-0269-1

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