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Development of an efficient algorithm for the detection of macular edema from optical coherence tomography images

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Abstract

Purpose

Detection of eye diseases and their treatment is a key to reduce blindness, which impacts human daily needs like driving, reading, writing, etc. Several methods based on image processing have been used to monitor the presence of macular diseases. Optical coherence tomography (OCT) imaging is the most efficient technique used to observe eye diseases. This paper proposes an efficient algorithm to automatically classify normal as well as disease-affected (macular edema) retinal OCT images by using segmentation of Inner Limiting Membrane and the Choroid Layer.

Methods

In the proposed method, preprocessing of the input image is done to improve the quality and reduce the speckle noise. The layer segmentation is done on the gradient image, and graph theory and dynamic programming algorithm is performed. The feature vectors from segmented image are in terms of thickness profile and cyst fluid parameter, and these features are applied to various classifiers.

Results

The proposed method was tested with the standard dataset collected from the Department of Ophthalmology, Duke University, and achieved a high accuracy rate of 99.4975%, sensitivity of 100%, and specificity of 99% for the SVM classifier.

Conclusions

An efficient algorithm is proposed for macular edema detection from OCT images using segmentation based on graph theory and dynamic programming algorithm. The comparison with alternative methods yielded results that demonstrate the superiority of the proposed algorithm for macular edema detection.

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Funding

This study was funded by APJ Abdul Kalam Technological University (APJAKTU)–Centre for Engineering Research and Development (CERD), India (Grant No. KTU/RESEARCH 2/56/2017 dated 06-01-2017).

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Government Engineering College, Wayanad, 670644, Kerala, India

    K. M. Jemshi & Varun P. Gopi

  2. School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore, 639798, Singapore

    Swamidoss Issac Niwas

Authors
  1. K. M. Jemshi
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  2. Varun P. Gopi
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  3. Swamidoss Issac Niwas
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Corresponding author

Correspondence to Varun P. Gopi.

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The authors declare that they have no conflict of interest.

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For this type of study, formal consent is not required.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Jemshi, K.M., Gopi, V.P. & Issac Niwas, S. Development of an efficient algorithm for the detection of macular edema from optical coherence tomography images. Int J CARS 13, 1369–1377 (2018). https://doi.org/10.1007/s11548-018-1795-6

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  • DOI: https://doi.org/10.1007/s11548-018-1795-6

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