Gaussian fitting on mean curvature maps of parameterization of corneal ectatic diseases

1. A method of using a device that maps corneal thickness and anterior and posterior corneal topography to analyze cornea cone characteristics, said method comprises:

measuring the corneal topography of a subject;

computing and displaying a map of the cornea;

fitting said map to a mathematical function having a cone-like shape; and determining and displaying the cone's location based on the fitting;

wherein said measuring device uses software encoded on a computer readable media.

2. The method of claim 1 , wherein said corneal map is a mean curvature map of the anterior surface of the cornea.

3. The method of claim 1 , wherein said corneal map is a mean curvature map of the posterior surface of the cornea.

4. The method of claim 1 , wherein said corneal map is an inverse normalized pachymetry map.

5. The method of claim 1 , wherein said mathematical function is one selected from 4th-order zero-th period Zernike polynomials, a Alpha function, a Rayleigh function, a Cauchy function, or a Gaussian function.

6. The method of claim 5 , wherein the Gaussian function is a two-dimensional Gaussian function comprising a single diameter for both the horizontal and vertical dimension.

7. The method of claim 5 , wherein the two-dimensional Gaussian function comprises different vertical and horizontal diameters.

8. The method of claim 1 further comprises smoothing the map with a moving average window.

9. The method of claim 8 , wherein the moving average window is a size from about 0.02 mm by 0.02 mm to about 2 mm by 2 mm.

10. The method of claim 8 , wherein determining the cone's location comprises identifying the maximum mean curvature value from the smoothed map.

11. A computer implemented system for diagnosing corneal ectatic diseases, comprising:

a device for measuring the surface map of a cornea; and

a processing unit comprising a program for performing the method of claim 10 .

12. A method of using a device that maps corneal thickness and anterior and posterior corneal topography to detect ectatic diseases of the cornea, said method comprises:

measuring the corneal topography of a subject:

providing a mean curvature map of the cornea;

fitting said map to a mathematical function having a cone-like shape;

determining and displaying the location of the cornea's cone based on the fitting; and

comparing and displaying the location of the cone to a reference location of a healthy cornea,

wherein if the location of the cone deviates from the reference location by a predetermined amount, a diseased state is detected, and wherein said measuring device uses software encoded on a computer readable media.

13. The method of claim 12 , wherein said ecstatic disease is one selected from keratoconus and pellucid marginal degeneration.

14. The method of claim 12 , wherein said mathematical function is one selected from 4th order Zernike polynomials, a Alpha function, a Rayleigh function, a Cauchy function, or a Gaussian function.

15. The method of claim 14 , wherein said Gaussian function is a two-dimensional Gaussian function and has different horizontal and vertical diameters.

16. The method of claim 12 , further comprising the step of smoothing the mean curvature maps with a moving average window.

17. The method of claim 16 , wherein the moving average window has a size of from about 0.02 mm by 0.02 mm to about 2 mm by 2 mm.

18. The method of claim 12 , further comprising determining the cone width by a search algorithm that maximized the cross-correlation coefficient between the mean curvature map and the Gaussian function.

19. The method of claim 12 , wherein the width of the cone is equal to full-width-half maximum diameter of the Gaussian function.

20. The method of claim 12 , further comprising the step of converting the curvature measurement of the mean curvature map from the natural inverse meter units into clioptric units.