Replication Data for: CCI.net: A Fully Automated Recognition and Quantification System for Fungal Keratitis based on Corneal Confocal Images
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Replication Data for: CCI.net: A Fully Automated Recognition and Quantification System for Fungal Keratitis based on Corneal Confocal Images
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Identifier |
https://doi.org/10.7910/DVN/MLRZBC
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Creator |
Wang, Yang
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Publisher |
Harvard Dataverse
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Description |
Patients diagnosed with FK were enrolled from three cities in China between April 2015 and June 2022. The diagnosis was confirmed either by corneal cultures or corneal biopsy. Patients who were over 65 years old, had systemic diseases such as diabetes, autoimmune diseases, thyroid-related diseases, or were pregnant, were excluded. Patients with bacterial, amebic, or other infections confirmed by culture were also excluded. A total of 355 patients were included, comprising 212 from Zhongshan Ophthalmic Center in Guangdong Province, 83 from Xi'an First Hospital in Shanxi Province, and 60 from Guangxi Zhuang Autonomous Region People's Hospital in Guangxi Zhuang Autonomous Region. There were 5 licensed ophthalmologists using standard processing12 to grade the image quality. A total of 8697 images were graded as good quality and were further divided into three datasets: a classification dataset (N=7086, including 4255 in the training set, 1413 in the validation set, and 1418 in the test set), a segmentation dataset (N=56, including 46 in the training set and 10 in the test set), and an external validation set (N=1555, including 1455 to validate the classification model and 100 to validate the segmentation model). |
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Subject |
Computer and Information Science
Medicine, Health and Life Sciences |
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Date |
2024-01-22
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Contributor |
Wang, Yang
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