Combination advanced corneal to topography/wave front...

Optics: eye examining – vision testing and correcting – Eye examining or testing instrument – Objective type

Reexamination Certificate

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Reexamination Certificate

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06428168

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates generally to apparatus for use in determining the front and back contours of the cornea of a human eye and thus facilitating the diagnosis and evaluation of corneal anomalies, design and fitting of contact lens, and the performance of surgical procedures. The present invention also relates to the field of measurement of the refractive characteristics of an optical system, and more particularly, to automatic measurement of the refractive characteristics of the human or other animal eye and to corrections to the vision thereof.
2. Background of Related Art
Corneal Front Surface Measurements
The cornea, being the front surface of the eye, provides the majority of the refracting power (about ⅔) of the eye and is important to quality of vision. Recently, a number of corneal surgical techniques have been developed for correcting visual deficiencies, such as near-sightedness, far-sightedness and astigmatism. In order to assist with such surgical techniques, a number of devices have been proposed or developed to evaluate the topography, i.e., the shape or curvature, of the cornea. In addition, such corneal topography techniques are useful for fitting contact lenses and for the diagnosis and management of corneal pathologic conditions, such as keratoconus and other ectasias. For example, prior to performing a corneal surgical technique to correct a refractive error, the patient is preferably screened using a corneal topography device to rule out the possibility of subclinical keratoconus.
Corneal topography is typically measured using a series of concentric lighted rings, known as a keratoscope pattern, shown in FIG.
12
. In a typical embodiment, the keratoscope pattern (reflected image of rings on CCD) is created by a keratoscope target, consisting of illuminated concentric rings which emit light rays which are projected onto the cornea of the patient's eye. Light rays are reflected off the patient's cornea, and a portion of the light is captured by a camera lens and focused onto a CCD. A computer is utilized to analyze the captured image to identify any distortions in the captured image and thus calculate any deformations in the patient's cornea.
While conventional corneal topography devices have achieved significant success, such devices suffer from a number of limitations, which, if overcome, could significantly enhance their accuracy and utility. For example, commercially available topography devices, such as the design illustrated in
FIG. 12
, typically measure the topography of only a portion of the cornea. In the design shown in
FIG. 12
, the light beam is emitted from a large, backlit keratoscope target and is then reflected off the cornea. Thereafter, a portion of the light reflects off the cornea and is focused by the camera lens at the center of the keratoscope target onto the CCD. Using this same technique to attempt to image the peripheral portion of the cornea would require a very large extended keratoscope target as shown in the “imaginary extension” of FIG.
12
. This imaginary extension could not be realized in a real system due to size and interference with the subject's head. Therefore, such prior art devices are unable to measure the peripheral cornea.
To overcome this problem, other corneal topography devices have attempted to capture the light rays reflected from the peripheral portions of the cornea by designing a very small keratoscope target in the shape of a cylinder or cone, as shown in
FIG. 13
, encompassing the peripheral cornea. In this manner, light rays emitted by the cylindrical or conical keratoscope target will form a pattern of illuminated rings which will be reflected off the cornea. The reflected light rays, including light rays reflected off the peripheral portions of the cornea, will be captured by the lens and imaged onto the CCD. For this strategy, however, the cylindrical or conical keratoscope target must be positioned very close to the eye, and thereby tends to impinge on the patient's brow and nose. In addition to being potentially uncomfortable and potentially contributing to the spread of disease, the close approach of the keratoscope target makes the design very error-prone, as a slight error in alignment or focusing causes a large percentage change in the position of the keratoscope rings relative to the eye and, hence, a large error in the measurement of the cornea.
In addition, current systems tend to provide poor pupil detection and do not accurately measure non-rotationally symmetric corneas, such as those with astigmatism. The location of the pupil is particularly important in planning surgical procedures for correcting visual deficiencies. In current systems, pupils are typically detected by deciphering the border of the pupil from the image of the keratoscope rings. This is particularly difficult with conventional designs, however, as the intensity transition from the black pupil to a dark iris is minimal compared to the intensity transition from a bright keratoscope ring image to a dark interring spacing. As a result, the pupil detection algorithms in current systems often fail or provide poor results.
In a recent corneal topography advancement, Malone (U.S. Pat. No. 5,873,832) describes a technique which utilizes a virtual image of a keratoscope pattern. The topography system reflects a structured light pattern off the cornea where light rays travel perpendicular to the cornea. In this manner, more of the peripheral cornea is imaged. The geometry of these reflected rays is similar to that of the innermost rays of the traditional corneal topography system. It is well known that the innermost data of traditional corneal topography systems have relatively low accuracy, so it is likely that this new technique will have lower accuracy than that currently provided by the commercially available corneal topography systems.
In the present invention, we overcome these problems of cornea measurement coverage and accuracy using a novel skew-view corneal analysis technique as explained below. We make use of three cameras as was detailed by Sarver (U.S. Pat. No. 5,847,804). While Sarver specifically used a front-view camera and two orthogonal side view cameras (only one of which was used during an exam), the present invention uses a front-view camera and a left- and right-camera oriented at 45 degrees to the optical axis of the front-view camera and all three cameras are used for each exam.
Cornea Back Surface Measurements and Cornea Thickness
Corneal thickness is commonly measured using an ultrasound technique. The hand held A-scan ultrasound probe produces a single-point measurement of the thickness of the cornea. This single point is, in reality, the average thickness of an area of several square millimeters in extent. Because the location of the measurement is dependent upon the operator's positioning, the location of the measurement is not exactly repeatable, hence the data is variable as well.
Another method is the scanning slit technique reported in Snook (U.S. Pat. No. 5,512,966), Knopp (U.S. Pat. No. 5,870,167), and Lempert (U.S. Pat. No. 5,404,884). In these techniques a slit of light is passed through the cornea and the interface of the slit with the front and back surfaces is evaluated from a digitized image. Using this information and an estimate of the index of refraction of the cornea, the thickness of the cornea can be estimated. By scanning the slit over several portions of the cornea, the thickness of a significant portion of the cornea can be obtained. Since the diffuse interaction of the light slit and the cornea can be ill-defined, the image processing will not be exact and so the measurements will contain some amount of error. These techniques also suffer from the characteristic that a large number of images must be obtained and processed to estimate a large portion of the cornea. The result is a large amount of data to process and store as well as the complexity of registration of the images due to mo

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