Li Y, Wang X, Gong Q, Deng M, Chen S, Chen H. Ridge operator-assisted delineation of capsulorhexis border for cataract surgery.
Quant Imaging Med Surg 2023;
13:5119-5129. [PMID:
37581076 PMCID:
PMC10423338 DOI:
10.21037/qims-22-1319]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 05/05/2023] [Indexed: 08/16/2023]
Abstract
Background
With the continuous development of machine vision and imaging technology and its application in computer-aided diagnosis, it is clinically important to use computer technology to assist physicians in accurate cataract surgery. The capsulorhexis directly affects the outcome of cataract surgery, therefore, we design a method to automatically determine the virtual boundary of capsulorhexis for cataract surgery planning and tracking in-vivo to help surgeons achieve a more ideal capsulotomy geometry.
Methods
In this study, an effective method was proposed to detect and display the location of capsulorhexis in cataract videos in-vivo. The initial step was locating the entire eye area by analyzing the connected components of the mirror reflective points in the image in the cataract surgery video. Then, an operator was designed for ridge edge variation and used to extract pupil edge features. Lastly, circular Hough transform was used to detect the pupillary margin and calculate the boundary between the scleral limbus and the virtual capsulorhexis border in accordance with the pupillary margin and finally displayed it in-vivo during cataract surgery.
Results
The method was tested on eight videos of cataract surgery and the results showed that 98.52% accuracy was achieved in the localization of the specular reflection point. We compared the proposed operator with the Sobel, Scharr, Laplace and Canny operators and the results showed that our operator achieved the smallest mean square error with the greatest structural similarity.
Conclusions
The analysis demonstrated that the proposed operator outperformed other operators in detection and achieved satisfactory results in the videos of actual cataract surgeries.
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