Contact lens & anterior eye : the journal of the British Contact Lens Association · 2018
Semi-automatic measurement of rigid gas-permeable contact lens movement in keratoconus patients using blinking images.
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Rezazadeh Hassan, Arabalibeik Hossein, Alipour Fateme, Pasyar Pezhman, Sadeghi Vahid
Аннотация
PURPOSE: To introduce a method for estimation of the rigid gas-permeable contact lens (RGP) movement.
MATERIALS AND METHODS: Videos captured from normal blinking of keratoconus patients while wearing RGP lenses were used for this study. The videos are recorded using the CCD camera of a smart phone attached to the eyepiece of the slit lamp. The algorithm starts with extracting two frames of the video related to the highest and lowest positions of the lens during blinking, followed by an appropriate edge detection method. In the next step circular Hough transform is used to find the center of lens and to segment it in each image. Finally the lens movement is estimated by measuring vertical displacement of the lens center between these two frames.
RESULTS: Mean and standard deviation of the difference between real movement and results of the algorithm for 20 cases are -8.66% and 10.71% respectively. The results are highly correlated with Pearson coefficient 0.986 P < 0.001. Bland-Altman plot with 95% levels of agreement (LoA) shows an agreement between exact manual measurement method and the proposed algorithm.
CONCLUSION: The proposed algorithm shows a relatively high accuracy as the first attempt and compared to the routine qualitative visual estimation. Considering the importance of the lens movement, although this system was not tested on a series of RGP fitting patients yet, semi-automatic measurement may potentially help practitioners decide the appropriate RGP lens fit and reduce the fitting time.
MATERIALS AND METHODS: Videos captured from normal blinking of keratoconus patients while wearing RGP lenses were used for this study. The videos are recorded using the CCD camera of a smart phone attached to the eyepiece of the slit lamp. The algorithm starts with extracting two frames of the video related to the highest and lowest positions of the lens during blinking, followed by an appropriate edge detection method. In the next step circular Hough transform is used to find the center of lens and to segment it in each image. Finally the lens movement is estimated by measuring vertical displacement of the lens center between these two frames.
RESULTS: Mean and standard deviation of the difference between real movement and results of the algorithm for 20 cases are -8.66% and 10.71% respectively. The results are highly correlated with Pearson coefficient 0.986 P < 0.001. Bland-Altman plot with 95% levels of agreement (LoA) shows an agreement between exact manual measurement method and the proposed algorithm.
CONCLUSION: The proposed algorithm shows a relatively high accuracy as the first attempt and compared to the routine qualitative visual estimation. Considering the importance of the lens movement, although this system was not tested on a series of RGP fitting patients yet, semi-automatic measurement may potentially help practitioners decide the appropriate RGP lens fit and reduce the fitting time.