A new method for detecting the outer corneal contour in images from an ultra-fast Scheimpflug camera

Table 3 A comparison of the tested methods of outer corneal edge detection in images from the Corvis^® ST tonometer, i.e. Sobel, Roberts, Canny methods and the authors’ (proposed) method of outer corneal edge detection, with the methods proposed by other authors

Outer edge detection method	Verification parameter			Number of analysed patients
Outer edge detection method	\(\delta_{k}\)	r	\(\Delta A\;{\text{time}}\)	Number of analysed patients
Proposed	\(0.16\%\)	−	−	110 healthy subjects (110 eyes)
Sobel	\(3.43\%\)	−	−
Roberts	\(5.76\%\)	−	−
Canny	\(1.26\%\)	−	−
Ji et al. [13]	−	0.9943	−	40 eyes (normal group)
Ji et al. [13]	−	0.9972	−	30 eyes (keratoconus group)
Kasprzak et al. [43]	−	−	\(\pm \;23\) ms	10 healthy subjects (only one eye was examined for each patient, 9 measurements were made for each eye)

\(\delta_{k} \left[ \% \right]\)—Measurement error (Eq. 1), calculated based on the difference between the position of the corneal edge obtained by a given method and the position of the outer corneal contour determined by the expert
r—Pearson’s correlation coefficient. The parameter values (r) are calculated for the correlation analysis of the method proposed by Ji et al. [13] with the manual method (expert). The correlation was determined for the Peak Distance parameter describing the distance between two corneal peaks at the moment of the largest corneal concavity
\(\Delta A\;{\text{time}}\) (ms)—The difference between corneal applanation times determined using the built-in method (available in the Corvis^® ST tonometer software) and the method proposed by Kasprzak et al. [43]

ISSN: 1475-925X