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Access to the keratoconus image bank
Automatic Detection of Keratoconus from Galilei Corneal Images Using Convolutional Neural Networks
The Dataset encompasses data from 3538 eyes, including 1872 with a diagnosis of keratoconus and 1666 healthy eyes. All images were collected from the recorded data in the Iranian National Registry for Keratoconus (KCNReg®). Four colored corneal maps—Posterior Elevation Best-fit Toric Aspheric (BFTA), Anterior Elevation BFTA, Anterior Instantaneous Curvature, and Pachymetry—as well as 14 indices from Galileo Corneal Tomography comprise the data for each eye. The dataset enables researchers to develop deep learning networks based on Galilei images for a more holistic investigation of the Keratoconus disease. To access the Keratoconus Dataset associated with the study titled "Automatic Detection of Keratoconus from Galilei Corneal Images Using Convolutional Neural Networks", please complete the following form. You commit to using the dataset solely for non-commercial purposes after approval.
Given name:
Family name:
Affiliation: [Your Institution/Organization]:
Institutional Email:
Intended use of the Dataset: [Briefly describe the purpose of using the dataset]
I confirm that this dataset and its subsets can only be used for academic research.
No
Yes
I confirm that I am not allowed to use this dataset and its subsets for any commercial purposes.
No
Yes
I confirm that I am not allowed to forward, publish, or distribute this dataset or its subsets to any organization or individual in any way or by any means.
No
Yes
I confirm that any request for access to the mentioned dataset should only be made by completing this form.
No
Yes
I confirm that if I use part or all of the image dataset in any research, I will cite the article "" and the access address "".
No
Yes
Contact if you need more information: Sabbaghi.opt@gmail.com
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