Determining degree of optic nerve edema from color fundus photography

Jason Agne; Jui-Kai Wang; Randy H. Kardon M.D.; Mona K. Garvin

doi:10.1117/12.2081423

20 March 2015 Determining degree of optic nerve edema from color fundus photography

Jason Agne, Jui-Kai Wang, Randy H. Kardon M.D., Mona K. Garvin

Proceedings Volume 9414, Medical Imaging 2015: Computer-Aided Diagnosis; 94140F (2015) https://doi.org/10.1117/12.2081423
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Swelling of the optic nerve head (ONH) is subjectively assessed by clinicians using the Frisén scale. It is believed that a direct measurement of the ONH volume would serve as a better representation of the swelling. However, a direct measurement requires optic nerve imaging with spectral domain optical coherence tomography (SD-OCT) and 3D segmentation of the resulting images, which is not always available during clinical evaluation. Furthermore, telemedical imaging of the eye at remote locations is more feasible with non-mydriatic fundus cameras which are less costly than OCT imagers. Therefore, there is a critical need to develop a more quantitative analysis of optic nerve swelling on a continuous scale, similar to SD-OCT. Here, we select features from more commonly available 2D fundus images and use them to predict ONH volume. Twenty-six features were extracted from each of 48 color fundus images. The features include attributes of the blood vessels, optic nerve head, and peripapillary retina areas. These features were used in a regression analysis to predict ONH volume, as computed by a segmentation of the SD-OCT image. The results of the regression analysis yielded a mean square error of 2.43 mm³ and a correlation coefficient between computed and predicted volumes of R = 0:771, which suggests that ONH volume may be predicted from fundus features alone.

Citation Download Citation

Jason Agne, Jui-Kai Wang, Randy H. Kardon M.D., and Mona K. Garvin "Determining degree of optic nerve edema from color fundus photography", Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94140F (20 March 2015); https://doi.org/10.1117/12.2081423

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