Edge detection and mathematic fitting for corneal surface with Matlab software

AIM:To select the optimal edge detection methods to identify the corneal surface,and compare three fitting curve equations with Matlab software. METHODS:Fifteen subjects were recruited. The corneal images from optical coherence tomography(OCT)were imported into Matlab software. Five edge detection m...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of ophthalmology Vol. 10; no. 3; pp. 336 - 342
Main Authors Di, Yue, Li, Mei-Yan, Qiao, Tong, Lu, Na
Format Journal Article
LanguageEnglish
Published China International Journal of Ophthalmology Press 18.03.2017
Press of International Journal of Ophthalmology (IJO PRESS)
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:AIM:To select the optimal edge detection methods to identify the corneal surface,and compare three fitting curve equations with Matlab software. METHODS:Fifteen subjects were recruited. The corneal images from optical coherence tomography(OCT)were imported into Matlab software. Five edge detection methods(Canny,Log,Prewitt,Roberts,Sobel)were used to identify the corneal surface. Then two manual identifying methods(ginput and getpts)were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve(y=Ax2+Bx+C),Polynomial curve [p(x)=p1xn+p2x(n-1)+...+pnx+pn+1] and Conic section(Ax2+Bxy+Cy2+Dx+Ey+F=0)were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally,the eccentricity(e)obtained by corneal topography and conic section were compared with paired t-test. RESULTS:Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis,eccentricity,circle center,etc. There were no significant differences between 'e' values by corneal topography and conic section(t=0.9143,P=0.3760 〉0.05).CONCLUSION:It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.
Bibliography:Matlab software edge detection curve fitting mathematic simulation optical coherence tomography corneal topography
AIM:To select the optimal edge detection methods to identify the corneal surface,and compare three fitting curve equations with Matlab software. METHODS:Fifteen subjects were recruited. The corneal images from optical coherence tomography(OCT)were imported into Matlab software. Five edge detection methods(Canny,Log,Prewitt,Roberts,Sobel)were used to identify the corneal surface. Then two manual identifying methods(ginput and getpts)were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve(y=Ax2+Bx+C),Polynomial curve [p(x)=p1xn+p2x(n-1)+....+pnx+pn+1] and Conic section(Ax2+Bxy+Cy2+Dx+Ey+F=0)were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally,the eccentricity(e)obtained by corneal topography and conic section were compared with paired t-test. RESULTS:Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis,eccentricity,circle center,etc. There were no significant differences between 'e' values by corneal topography and conic section(t=0.9143,P=0.3760 〉0.05).CONCLUSION:It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Co-first authors: Yue Di and Mei-Yan Li
ISSN:2222-3959
2227-4898
DOI:10.18240/ijo.2017.03.02