Intensity and K-Means Clustering based Treatment Classification of Posterior Capsular Opacification
| Autor: | Teesid Leelasawassuk, Nattapon Wongcumchang, Toshiaki Kondo, Raisha Shrestha, Waree Kongprawechnon |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Treatment classification business.industry k-means clustering 02 engineering and technology eye diseases Intensity (physics) 03 medical and health sciences 0302 clinical medicine 030221 ophthalmology & optometry 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing Radiology Posterior capsular opacification business F1 score Complication Cluster analysis Grading (tumors) |
| Zdroj: | 2020 6th International Conference on Control, Automation and Robotics (ICCAR). |
| DOI: | 10.1109/iccar49639.2020.9107985 |
| Popis: | Posterior Capsular Opacification (PCO) is an after cataract complication which has been under continuous research over past couple of decades. Studies so far have been limited to it's grading, calculating severity and rate of occurrence. The grading can be more useful in practical world, if its severity level determined cases with requirement of treatment. PCO patients are treated only when they have pain in their eyes, resulting in need of regular check-ups. This paper presents an approach of PCO treatment classification, with two methods: intensity-based (method 1) and $k$ -means clustering based (method 2), to classify the requirement of treatment. When cross-checked to classifications made by expert ophthalmologists, methods 1 and 2 showed accuracy of 94.57% and 96.74%, with F1 score of 96.69% and 98.11% respectively. Also, the classifications made by method 1 and 2 were 83% and 87% correlated to the classification made by expert ophthalmologists. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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