Loughborough University
10.1007%2Fs10916-017-0859-4.pdf (7.02 MB)

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

Download (7.02 MB)
journal contribution
posted on 2017-11-23, 11:02 authored 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.


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.



  • Science


  • Computer Science

Published in

Journal of Medical Systems


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.


Springer © The Author(s)


  • 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


Publication date



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/






  • en