The Foveal Avascular Zone Image Database (FAZID)

Arpit Agarwal; Jothi Balaji J.; Rajiv Raman; Vasudevan Lakshminarayanan

doi:10.1117/12.2567580

21 August 2020 The Foveal Avascular Zone Image Database (FAZID)

Arpit Agarwal, Jothi Balaji J., Rajiv Raman, Vasudevan Lakshminarayanan

Proceedings Volume 11510, Applications of Digital Image Processing XLIII; 1151027 (2020) https://doi.org/10.1117/12.2567580
Event: SPIE Optical Engineering + Applications, 2020, Online Only

Conference Poster

Abstract

The Foveal Avascular Zone (FAZ) is of clinical importance since the vascular arrangement around the fovea changes with disease and refractive state of the eye. Therefore, it is important to segment and quantify the FAZ accurately. Studies done to date have achieved reasonable segmentation but there is a need for considerable improvement. In order to test and validate newly developed automated segmentation algorithms, we have created a public dataset of these retinal fundus images. The 304 images in the dataset are classified into: diabetic (107), myopic (109) and normal (88) eyes. The images were classified by a clinical expert and include clinical grading of diabetic retinopathy and myopia. The images are of dimensions 420 x 420 pixels (6mm x 6mm of retina). Both clear and manually segmented by a clinical expert (ground truth) images are available (608 total images). In these images, the FAZ is the green region marked in manually segmented image. The images can be used to test newly developed techniques and the manual segmentation images can be used as a ground truth for making performance comparisons and validation. It should also be noted there are only a few studies using supervised learning to segment the FAZ and this dataset will potentially be useful for machine learning training and validation. The image database, The Foveal Avascular Zone Image Database (FAZID) dataset can be accessed from the ICPSR website at the University of Michigan (https://doi.org/10.3886/E117543V2).

Conference Presentation

Citation Download Citation

Arpit Agarwal, Jothi Balaji J., Rajiv Raman, and Vasudevan Lakshminarayanan "The Foveal Avascular Zone Image Database (FAZID)", Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 1151027 (21 August 2020); https://doi.org/10.1117/12.2567580

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