Functional Regressive Modeling for Detection of Retinal Nerve Fiber Layer (RNFL) Thinning in Glaucoma Progression
A linear statistical method of detecting local thinning of the RNFL based on the 200x200 pixels RNFL thickness map measured by a spectral-domain OCT is introduced with practical implementation guide. This linear regression based trend detection method is found to be more robust and efficient in detecting local thinning of the RNFL than the commercially available algorithm – Guided Progression Analysis.
Advantages and improvements over existing technology: By adopting the invention diagnosis method, the power of detecting local thinning of RNFL thickness can be improved. In addition, poor image quality for a few scans will not strongly affect the analytical results.
生物醫學
醫療裝置
11/MED/417
Inventor(s): Professor LEUNG Kai Shun Christopher, Department of Ophthalmology and Visual Sciences Licensing Status: Available
香港
