# Spatial normalization of eye fundus images

Xiwei Zhang, Etienne Decencière, Guillaume Thibault, Guy Cazuguel, Gwénolé Quellec, Ronan Danno, Bruno Laÿ, Ali Erginay, Pascale Massin, Zeynep Guvenli-Victor, et al.

► To cite this version:

Xiwei Zhang, Etienne Decencière, Guillaume Thibault, Guy Cazuguel, Gwénolé Quellec, et al. Spatial normalization of eye fundus images. ISBI 2012: 9th IEEE International Symposium on Biomedical Imaging, May 2012, Barcelone, Spain. IEEE, 2012. [hal-00945417](https://hal.science/hal-00945417)

HAL Id: hal-00945417

https://hal.science/hal-00945417

Submitted on 11 Oct 2022

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## Introduction

* The heterogeneity of clinical retinal image databases, regarding image scale, contrast and quality, makes the design of generic image processing algorithms difficult. Different possibilities of spatial normalization of eye fundus images are analyzed, and a simple and efficient method is proposed.

* **OPHDIAT** is a telemedicine network for diabetic retinopathy screening. Thousands of color eye fundus images have been collected, 70% of which have been classified as healthy by ophthalmologists. The **e-ophtha** database has been built from this data. The **TeleOphta** project aims at performing a preliminary analysis of these images, in order to automatically filter out healthy images, and thus reduce the burden on specialists.

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Eye fundus images from the e-ophta database.
Pixel size is often either absent, or not reliable

## Partners:

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## Authors:

X. Zhang, E. Decencière, G. Thibault, G. Cazuguel, G. Quellec, R. Danno, B. LaÿA. Erginay, P. Massin, Z. Guvenli-Victor, A. Chabouis

## Financial support:

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## Possible Approaches

* Using **image size** directly: This is the most common and the easiest method. Before any processing, all images are sampled to the same size. However, the field-of-view appears different shapes according to manufacture and date[1]. The size of the image cannot precisely represent the pixel size.

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Normalization by anatomical structure size. Left: optic disc; Middle: vessel; Right: microaneurysm

Normalization by image size, leading to different sizes of field-of-view

* Spatial normalization based on **anatomic structures and lesions size**, such as the diameter of the optic disc (OD) and the width of blood vessels: Difficult, given, firstly, that the anatomical size of structures varies from one person to the other (for example, the theoretical size of the OD is between 1-2 mm), and, secondly, that obtaining a precise segmentation and measurement of retinal structures, such as blood vessels, remains a problem.

* Using the **distance between optic disc and fovea**: the OD and fovea need to be detected, which is not easy, and moreover they may be absent from the image.

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Normalization based on the distance between the optic disc and the fovea

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Absence of OD

## Validation

* The proposed method has been tested on the **e-ophtha** database and compared to a manual measurement, based on the distance between the center of the Optic Disc and the fovea as the scale coefficient (see the table on the right). There are 8 different image sizes, and the first group (in red) is taken as the reference. For each group, 5 images are used to get a mean value.

## Proposed Method

* The field-of-view (FOV) is easy to segment. Since all the images in the e-ophta database have been acquired with the same capture angle, the width of the FOV and the pixels size are linearly correlated.

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Capture angle of a fundus camera

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Normalization by the width of the FOV. Left: fundus image; Right: segmented FOV

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* The width of the FOV is considered as a constant, which can then be used to compute the scale of the image.

<table><tr><td>Field-of-view</td><td>D<sub>ref</sub> = 900 px</td></tr><tr><td>Optic disc</td><td>OD<sub>ref</sub> = 160 px</td></tr><tr><td>Vessel</td><td>V<sub>ref</sub> = 12 px</td></tr><tr><td>Microaneurysm</td><td>MA<sub>ref</sub> = 10 px</td></tr></table>

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* The result shows an excellent agreement between the manually measured and automatically calculated scale coefficients (blue columns). Moreover, the standard deviation of the estimated size is smaller when using the automatic method. The proposed method shows a high accuracy and stability for estimating the scale coefficients.

* The generalization to other capture angles is straightforward

<table><thead><tr><th>Image size</th><th>Distance between OD and Fovea</th><th>Scale coefficient (manually measured)</th><th>Width of FOV</th><th>Scale coefficient (proposed method)</th></tr></thead><tbody><tr><td>1440×960</td><td>349</td><td>1</td><td>910</td><td>1</td></tr><tr><td>1504×1000</td><td>352</td><td>0.99</td><td>923</td><td>0.99</td></tr><tr><td>1728×1152</td><td>512</td><td>0.68</td><td>1305</td><td>0.70</td></tr><tr><td>1936×1288</td><td>555</td><td>0.63</td><td>1484</td><td>0.61</td></tr><tr><td>2048×1360</td><td>595</td><td>0.59</td><td>1533</td><td>0.59</td></tr><tr><td>2544×1696</td><td>778</td><td>0.45</td><td>1924</td><td>0.47</td></tr><tr><td>2816×1880</td><td>817</td><td>0.43</td><td>2159</td><td>0.42</td></tr><tr><td>3504×2336</td><td>1044</td><td>0.33</td><td>2650</td><td>0.34</td></tr></tbody></table>

Remember us

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Web site: www.teleophta.fr

Contact: etienne.decenciere@mines-paristech.fr

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<footnote>[1] P.J. Saine, 'Focusing The Fundus Camera: A Clinical Approach', Jornal of Ophthalmic Photography, Vol. 14, No.1, 1992.</footnote>