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A novel adaptive deformable model for automated optic disc and cup segmentation to aid glaucoma diagnosis

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journal contribution
posted on 23.11.2017, 11:02 by Muhammad Salman Haleem, Liangxiu Han, Jano van Hemert, Baihua LiBaihua Li, Alan Fleming, Louis R. Pasquale, Brian J. Song
This paper proposes a novel Adaptive Region- based Edge Smoothing Model (ARESM) for automatic boundary detection of optic disc and cup to aid automatic glaucoma diagnosis. The novelty of our approach consists of two aspects: 1) automatic detection of initial optimum object boundary based on a Region Classification Model (RCM) in a pixel-level multidimensional feature space; 2) an Adaptive Edge Smoothing Update model (AESU) of contour points (e.g. misclassified or irregular points) based on iterative force field calculations with contours obtained from the RCM model by minimising energy function (an approach that does not require predefined geometric templates to guide auto-segmentation). Such an approach provides robustness in capturing a range of variations and shapes. We have conducted a comprehensive comparison between our approach and the state-of-the-art existing deformable models and validated it with publicly available datasets. The experimental evaluation shows that the proposed approach significantly outperforms existing methods. The generality of the proposed approach will enable segmentation and detection of other object boundaries and provide added value in the field of medical image processing and analysis.

Funding

This project is fully sponsored by EPSRC-DHPA and Optos plc., entitled "Automatic Detection of Features in Retinal Imaging to Improve Diagnosis of Eye Diseases" (Grant Ref: EP/J50063X/1). Dr. Pasquale is supported by the Harvard Glaucoma Center of Excellence. Brian J. Song has been supported by the Harvard Vision Clinical Scientist Development Program 2K12 EY016335-11.

History

School

  • Science

Department

  • Computer Science

Published in

Journal of Medical Systems

Citation

HALEEM, M.S. ...et al., 2017. A novel adaptive deformable model for automated optic disc and cup segmentation to aid glaucoma diagnosis. Journal of Medical Systems, 42, Article 20.

Publisher

Springer © The Author(s)

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

01/11/2017

Publication date

2017

Notes

This is an Open Access Article. It is published by Springer under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

ISSN

0148-5598

eISSN

1573-689X

Language

en