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Multi-scale Segmentation and Surface Fitting for Measuring 3D Macular Holes

Lookup NU author(s): Professor David SteelORCiD, Professor Boguslaw ObaraORCiD



This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2018.

For re-use rights please refer to the publisher's terms and conditions.


IEEE Macular holes are blinding conditions where a hole develops in the central part of retina, resulting in reduced central vision. The prognosis and treatment options are related to a number of variables including the macular hole size and shape. High-resolution spectral domain optical coherence tomography (SD-OCT) allows precise imaging of the macular hole geometry in three dimensions, but the measurement of these by human observers is time consuming and prone to high inter- and intra-observer variability, being characteristically measured in 2D rather than 3D. We introduce several novel techniques to automatically retrieve accurate 3D measurements of the macular hole, including: surface area, base area, base diameter, top area, top diameter, height, and minimum diameter. Specifically, we introduce a multi-scale 3D level set segmentation approach based on a state-of-the-art level set method, and we introduce novel curvature-based cutting and 3D measurement procedures. The algorithm is fully automatic, and we validate our extracted measurements both qualitatively and quantitatively, where our results show the method to be robust across a variety of scenarios. Our automated processes are considered a significant contribution for clinical applications.

Publication metadata

Author(s): Nasrulloh AV, Willcocks CG, Jackson PTG, Geenen C, Habib MS, Steel DHW, Obara B

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Medical Imaging

Year: 2018

Volume: 37

Issue: 2

Pages: 580-589

Print publication date: 01/02/2018

Online publication date: 30/10/2017

Acceptance date: 21/10/2017

Date deposited: 05/03/2018

ISSN (print): 0278-0062

ISSN (electronic): 1558-254X

Publisher: IEEE


DOI: 10.1109/TMI.2017.2767908


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