Deep Sequential Feature Learning in Clinical Image Classification of Infectious Keratitis
نویسندگان
چکیده
Infectious keratitis is the most common condition of corneal diseases in which a pathogen grows cornea leading to inflammation and destruction tissues. medical emergency for rapid accurate diagnosis needed ensure prompt precise treatment halt disease progression limit extent damage; otherwise, it may develop sight-threatening even eye-globe-threatening condition. In this paper, we propose sequential-level deep model effectively discriminate infectious via classification clinical images. approach, devise an appropriate mechanism preserve spatial structures images disentangle informative features image keratitis. comparison, performance proposed achieved 80% diagnostic accuracy, far better than 49.27% ± 11.5% accuracy by 421 ophthalmologists over 120 test
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ژورنال
عنوان ژورنال: Engineering
سال: 2021
ISSN: ['2096-0026', '2095-8099']
DOI: https://doi.org/10.1016/j.eng.2020.04.012