Objective quality metric for ocular wavefront measurements

• US 9,603,516 B2
• Filed: 11/03/2014
• Issued: 03/28/2017
• Est. Priority Date: 07/06/2009
• Status: Active Grant

• Current Assignee: Alcon Incorporated
• Original Assignee: WaveTec Vision Systems, Inc. (Alcon Incorporated)
• Inventors: Sarver, Edwin Jay, Padrick, Thomas D., Hall, Max
• Primary Examiner(s): SAHLE, MAHIDERE S
• Application Number:
  US14/531,926
• Publication Number:
  US 20150157200A1
• Time in Patent Office: 876 Days
• Field of Search: 351/203, 351/205, 351/206, 351/210, 351/221
• US Class Current: 1/1
• CPC Class Codes: A61B 3/0025 characterised by electronic signal processing, e.g. eye models
• CPC Class Codes: A61B 3/1015 for wavefront analysis

Abstract

A system and method for determining an objective quality metric for image data collected by a wavefront aberrometer. The method may include quantifying a plurality of characteristics of the image data and calculating the objective quality metric based on the quantified characteristics of the image data. The objective quality metric can be a weighted sum of the quantified characteristics of the image data. The weightings for the weighted sum can be determined based on subjective quality metrics assigned to a set of training image data by a human expert.

Claims

1. An ophthalmic device, comprising:

a wavefront aberrometer; and

a processing module enabled to execute computer-executable instructions for,

receiving an indication of a plurality of wavefront aberrometer images indicative of ocular aberrations of an eye of a patient;

determining a plurality of quantitative quality metrics respectively for each of the wavefront aberrometer images, wherein each of the quantitative quality metrics is based on a characteristic of a respective wavefront aberrometer image;

selecting at least a subset of the wavefront aberrometer images based on values of the quantitative quality metrics; and

determining ocular aberration measurements using at least the subset of the wavefront aberrometer images.

2. The ophthalmic device of claim 1, wherein the subset of wavefront aberrometer images consists of a first wavefront aberrometer image.

3. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

calculating a first quantitative quality metric using a parameter determined from a plurality of training images representative of ocular aberrations.

4. The ophthalmic device of claim 3, further comprising computer-executable instructions for:

determining the parameter based on qualitative quality metrics assigned to the plurality of training images by a human expert.

5. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

determining the characteristic of a second wavefront aberrometer image by analyzing a spatial-domain representation of the second wavefront aberrometer image.

6. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

determining the characteristic of a third wavefront aberrometer image by analyzing a frequency-domain representation of the third wavefront aberrometer image.

7. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

quantifying the characteristic of a fourth wavefront aberrometer image as an output of a mathematical function that receives the fourth wavefront aberrometer image as an input.

8. The ophthalmic device of claim 7, further comprising computer-executable instructions for:

determining a quantitative quality metric for the fourth wavefront image based on a combination of outputs of a plurality of mathematical functions.

9. The ophthalmic device of claim 8, further comprising computer-executable instructions for:

calculating the combination of the outputs of the mathematical functions based on a weighted sum of the outputs calculated using respective weightings of the mathematical functions.

10. The ophthalmic device of claim 9, further comprising computer-executable instructions for:

selecting the weightings based on qualitative quality metrics assessed to a plurality of test images by a human expert.

11. The ophthalmic device of claim 10, further comprising computer-executable instructions for:

selecting the weightings based on a difference between the quantitative quality metrics calculated for the test images and the qualitative quality metrics for the test images.

12. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

determining the characteristic of a fifth wavefront aberrometer image based on a degree of centration of the fifth wavefront aberrometer image.

13. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

determining the characteristics of the subset of wavefront aberrometer images based on a first variance of the ocular aberration measurements.

14. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

determining the characteristic of a sixth wavefront aberrometer image based on a width of a spectral peak identified in a spatial frequency-domain representation of the sixth wavefront aberrometer image.

15. The ophthalmic device of claim 14, further comprising computer-executable instructions for:

determining the characteristic of the sixth wavefront aberrometer image based on a second variance of the width of the spectral peak based on a direction across the spectral peak.

16. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

determining the characteristic of a seventh wavefront aberrometer image based on an image contrast value for the seventh wavefront aberrometer image.

17. The ophthalmic device of claim 16, further comprising computer-executable instructions for:

determining the image contrast value from a region of interest within the seventh wavefront aberrometer image.

18. The ophthalmic device of claim 1, wherein an eighth wavefront aberrometer image comprises a Moiré

fringe pattern.

19. The ophthalmic device of claim 1, wherein a ninth wavefront aberrometer image comprises a Shack-Hartmann spot pattern.

20. The ophthalmic device of claim 1, wherein the ocular aberration measurements include measurements selected from:

a spherical power of the eye, a cylindrical power of the eye, and a cylindrical axis of the eye.

21. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

based on the ocular aberration measurements, selecting an intraocular lens for implantation in the eye.

22. The ophthalmic device of claim 1, further comprising computer-executable instructions for:

outputting the ocular aberration measurements for positioning an intraocular lens during cataract surgery.

25. The ophthalmic device of claim 1, wherein the quantitative quality metrics comprise scalar values.

23. A computer-implemented method for execution in a wavefront aberrometer system, the method comprising:

receiving an indication of a plurality of wavefront aberrometer images indicative of ocular aberrations of an eye of a patient;

determining a plurality of quantitative quality metrics respectively for each of the wavefront aberrometer images, wherein each of the quantitative quality metrics is based on a characteristic of a respective wavefront aberrometer image;

selecting at least a subset of the wavefront aberrometer images based on values of the quantitative quality metrics; and

determining ocular aberration measurements using at least the subset of the wavefront aberrometer images.

24. A computer-readable medium storing instructions executable by a computer for:

receiving an indication of a plurality of wavefront aberrometer images indicative of ocular aberrations of an eye of a patient;

determining a plurality of quantitative quality metrics respectively for each of the wavefront aberrometer images, wherein each of the quantitative quality metrics is based on a characteristic of a respective wavefront aberrometer image;

selecting at least a subset of the wavefront aberrometer images based on values of the quantitative quality metrics; and

determining ocular aberration measurements using at least the subset of the wavefront aberrometer images.