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Computer-aided Diagnosis of Proliferative Diabetic Retinopathy via Modeling of the Major Temporal Arcade in Retinal Fundus Images

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Abstract

Monitoring the openness of the major temporal arcade (MTA) and how it changes over time could facilitate diagnosis and treatment of proliferative diabetic retinopathy (PDR). We present methods for user-guided semiautomated modeling and measurement of the openness of the MTA based on Gabor filters for the detection of retinal vessels, morphological image processing, and a form of the generalized Hough transform for the detection of parabolas. The methods, implemented via a graphical user interface, were tested with retinal fundus images of 11 normal individuals and 11 patients with PDR in the present pilot study on potential clinical application. A method of arcade angle measurement was used for comparative analysis. The results using the openness parameters of single- and dual-parabolic models as well as the arcade angle measurements indicate areas under the receiver operating characteristics of A z = 0.87, 0.82, and 0.80, respectively. The proposed methods are expected to facilitate quantitative analysis of the architecture of the MTA, as well as assist in detection and diagnosis of PDR.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada, T2N 1N4

    Faraz Oloumi & Rangaraj M. Rangayyan

  2. Division of Ophthalmology, Department of Surgery, Alberta Children’s Hospital, Calgary, AB, Canada, T3B 6A8

    Anna L. Ells

Authors
  1. Faraz Oloumi
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  2. Rangaraj M. Rangayyan
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  3. Anna L. Ells
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Corresponding author

Correspondence to Rangaraj M. Rangayyan.

Additional information

This work was supported by the Natural Sciences and Engineering Research Council of Canada. We thank Dr. A. Hoover for help with the STARE images.

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Oloumi, F., Rangayyan, R.M. & Ells, A.L. Computer-aided Diagnosis of Proliferative Diabetic Retinopathy via Modeling of the Major Temporal Arcade in Retinal Fundus Images. J Digit Imaging 26, 1124–1130 (2013). https://doi.org/10.1007/s10278-013-9592-9

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