Novel Statistical Glaucoma Prediction Algorithm Based on Spectral Analysis
Ghosh A, Bose S, Sen A (2024)
Publication Type: Conference contribution
Publication year: 2024
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 946
Pages Range: 105-120
Conference Proceedings Title: Lecture Notes in Networks and Systems
Event location: Pune, IND
ISBN: 9789819713226
DOI: 10.1007/978-981-97-1323-3_9
Abstract
Glaucoma is a condition that causes damage to the eye’s optic nerve and may result in the loss of vision. About 12 million people in India suffer from glaucoma. The ML models predicting Glaucoma are computationally complex, presence of infrastructure like GPU is of high importance, and sometimes they are also not eco-friendly due to carbon footprints. As a result, the authors of this paper proposed an algorithm which based on spectral analysis with fusion of advanced statistical approach of KL divergence for predicting the presence of Glaucoma. The algorithm has been evaluated on a total of 98 images: 70 images are used for training (glaucoma—49, normal—21) and 28 images (glaucoma—18, normal—10) are used for prediction. The accuracy obtained by the proposed novel algorithm is 76.4% with sensitivity of 86.7%, F1 Score of 82.5%, and precision 78.9%. In terms of computational efficiency, the training process takes approximately 51.116 s to complete, while the testing phase requires about 11.616 s to finish.
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India (IN)How to cite
APA:
Ghosh, A., Bose, S., & Sen, A. (2024). Novel Statistical Glaucoma Prediction Algorithm Based on Spectral Analysis. In Tomonobu Senjyu, Chakchai So–In, Amit Joshi (Eds.), Lecture Notes in Networks and Systems (pp. 105-120). Pune, IND: Springer Science and Business Media Deutschland GmbH.
MLA:
Ghosh, Arkoprovo, Soumalya Bose, and Anindya Sen. "Novel Statistical Glaucoma Prediction Algorithm Based on Spectral Analysis." Proceedings of the 8th International Conference on Smart Trends in Computing and Communications, SmartCom 2024, Pune, IND Ed. Tomonobu Senjyu, Chakchai So–In, Amit Joshi, Springer Science and Business Media Deutschland GmbH, 2024. 105-120.
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