WO2003092485A1 - Procede de mesure de l'acuite visuelle pour la qualite de vision - Google Patents
Procede de mesure de l'acuite visuelle pour la qualite de vision Download PDFInfo
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- WO2003092485A1 WO2003092485A1 PCT/US2003/013716 US0313716W WO03092485A1 WO 2003092485 A1 WO2003092485 A1 WO 2003092485A1 US 0313716 W US0313716 W US 0313716W WO 03092485 A1 WO03092485 A1 WO 03092485A1
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- quality function
- sharpness
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- subjective
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/0016—Operational features thereof
- A61B3/0025—Operational features thereof characterised by electronic signal processing, e.g. eye models
Definitions
- the wave aberration can be broken down into individual aberrations, or Zernike modes, with a process called Zernike decomposition.
- Zernike decomposition can provide valuable insight into the relative importance of different aberrations for vision. It is useful in diagnosing the cause of a wave aberration and visual complaints. For example, a refractive surgery patient who post-op presents with an increase of vertical coma and complains of a vertical flare on car headlights at night very likely suffered some vertical decentration during laser ablation.
- Wavefront sensors provide a physical measure of the severity of each patient's wave aberration in the form of the rms wavefront error.
- the RMS wavefront error is the square root of the sum of the squares of the deviation of the actual wavefront from the ideal wavefront.
- rms wavefront error is not an especially useful metric for describing the subjective impact of the eye's wave aberration.
- Fig. 1 shows that the eye with the best image quality can sometimes have the highest RMS.
- the present invention is directed to a sharpness metric.
- the sharpness metric is the maximum of the convolution of the point spread function (PSF) measured in the retinal plane and a neural point spread function (PSF).
- the neural PSF can be modeled as a Gaussian function.
- the metric is constructed according to the following principles.
- the number of metrics that one might explore to predict subjective image quality is infinite.
- To make this problem tractable one must apply logical constraints that restrict the search to those domains that are most likely to yield the best solutions.
- the metrics proposed so far have involved summary statistics of the wave aberration itself, as defined in the pupil plane of the eye.
- the retinal image is then processed by a nervous system, the imaging properties of which are also reasonably well understood. Hence, the best metrics will mimic those steps that the patient's eye and brain actually take in order to see.
- the strength of building the metric around a model of vision is that additional factors can be added to the model as their significance is assessed. For example, the model might initially incorporate only the blurring effects of aberrations and diffraction on the retinal image, but experiments undertaken to see if light scatter and apodization by the Stiles-Crawford effect are important might increase predictive power.
- the metric according to the present claimed invention illustrates the value of including neural as well as optical factors in predicting subjective image quality.
- spectacles can correct only five aberrations (defocus, two astigmatism aberrations, and two prismatic aberrations), whereas wavefront sensors can reliably measure dozens of aberrations in normal human eyes.
- the higher order aberrations can influence the values of defocus and astigmatism that provide the best subjective image quality.
- the development of metrics for subjective image quality that include the effects of higher order aberrations will allow us to optimize vision correction.
- Metric formats will now be discussed. One would probably choose to convert metric values into scores that reflect population norms. For example, if the metric were transformed to a percentile, the clinician would know what fraction of the patient population has worse optics than the patient in question.
- the metrics described in the preferred embodiment are univariate: only one number is used to characterize the blur produced by the eye's wave aberration.
- blur is not a unity perceptual experience.
- a multivariate scheme would more accurately describe the subjective effect of a given wave aberration.
- our experience with different wave aberrations suggests that some of them reduce the overall contrast of the image, while keeping edges crisp. Others keep contrast high but sharp edges become fuzzy.
- Still other aberrations, especially odd-order aberrations like coma produce asymmetry in images such as flaring away from the object in one direction. This suggests a tripartite metric with separate numbers for contrast, sharpness, and symmetry in the retinal image.
- psychophysical experiments could determine the importance of each of these subjective qualities in overall image quality. Therefore, while the preferred embodiment features a univariate sharpness metric, the present invention can be expanded to include multivariate metrics.
- the 5 optimum metric is highly dependent on the visual task. For example, a task that requires detecting relatively large features in a low contrast environment would demand a quite different metric that detecting tiny features at very high contrast.
- the optimum metric will no doubt depend on a very large number of factors such as the visual task, pupil size, luminance, object distance, individual differences in neural systems. The optimum metric will also be used.
- Metrics for subjective image quality might also need to incorporate the fact that neural processing is plastic, changing its performance depending on the wave aberration it currently sees the world through. There is a long history of research revealing this plasticity.
- a metric based on the average patient is the first goal. But this metric could be customized depending on the specific characteristics of each patient. For example, older patients are likely , to have more light scatter, their pupil sizes are smaller on average, their accommodation range is reduced, and they will probably tolerate large changes in vision correction less readily. A metric that included patient age as a parameter would help to ensure the optimum vision correction. The optimum metric for someone with a poor neural contrast sensitivity will be different than the metric for someone withaji neural sensitivity. It may ultimately be possible to build known features of an individual patient's nervous system into the metric. For example, with laser interferometry or adaptive optics, it is possible to measure the neural performance of the eye independent of its optical quality.
- the metric according to the present claimed invention allows fully automated refraction.
- Autorefractors have not replaced subjective refraction as the ultimate method to prescribe vision correction.
- the advent of the wave front sensing reopens the possibility of fully-automated refraction.
- Wave front sensors provide much more information than autorefractors, since they indicate the fate of light as it passes through every point in the pupil.
- a fast algorithm has been described to compute the optimum vision correction for any metric from wave aberration data. Coupled with a biologically-plausible metric designed to mimic the eye and brain of each patient, wave front sensors may ultimately surpass the clinical refraction as the preferred method for choosing the best correction, whether for refractive surgery, spectacles, contact lenses, or intraocular lenses.
- the sharpness metric will have utility in describing the quality of vision to patients, which goes beyond a descriptor such as "20/20" vision.
- the metric can expected be extended to indicate where a patient's vision fits within the general population. Such information would be useful in guiding choices about refractive surgery, contact lens or spectacles.
- a sharpness metric for research and clinical use, for communicating the quality of vision in a simple single parameter
- An automated process for computing the sharpness metric for clinical use in communicating with patients, built, as a feature, into any wavefront measuring device, including standalone diagnostic devices and those devices used as part of an integrated refractive surgery system;
- Two experiments have been designed to compare the effectiveness of different metrics in determining the subjective impact of the wave aberration.
- subjects viewed a visual stimulus through a deformable mirror in an adaptive optics system that compensates for the subject's wave aberration.
- the subject's wave aberration was replaced by the wave aberration corresponding to an individual Zernike mode.
- the subject then adjusted the coefficient of the Zernike mode to match the blur of a standard stimulus.
- the subject viewed the stimulus with the wave aberration of one of 59 Lasik patients post-op and matched the blur by adjusting defocus.
- Fig. 1 shows the effects of combinations of various Zernike modes
- 5 Fig. 2 shows an experimental setup used to test the sharpness metric of the preferred embodiment
- Figs. 3A-3E show mode blur matching
- Figs. 4A-4D show wave aberrations from a Lasik post-operative patient;
- Figs. 4E-4H show wave aberrations caused by corrective optics;
- Figs. 5A-5D show blur matching of patient wave aberrations;
- Fig. 6 shows the differences among aberrations in their ability to blur
- Fig. 7 shows the varying effectiveness of Zernike modes
- Fig. 8 shows the various Zernike modes
- Figs. 9A-9C show the effects of wave aberration RMS
- L5 shows the derivation of the Strehl ratio
- Fig. 11 shows the deficiencies of RMS and the Strehl ratio in predicting subjective sharpness
- Fig. 12 shows the predictive value of the sharpness metric
- Figs. 13A-13C show the various predictive abilities of the RMS, the Strehl ratio, and 2.0 the sharpness metric, respectively;
- Fig. 14 shows a flow chart of a process for correcting vision by use of the sharpness metric
- Fig. 15 shows a schematic diagram of an apparatus for correcting vision by use of the sharpness metric. 25 Detailed Description of the Preferred Embodiment
- the sharpness metric S is calculated from the point 5 spread function (PSF) and a neural point spread function based on psychophysical experiments.
- the sharpness metric S has the form
- the optical PSF is convolved with the neural PSF, where the latter is expressed as a Gaussian.
- the maximum value of this convolution is the metric value. .0
- the neural PSF is represented by a Gaussian function. The value of
- Fig. 2 shows the setup of the adaptive optics system 200 for the matching experiment.
- This adaptive optics system 200 uses a Hartmann-Shack wavefront sensor 202, conjugate with the pupil plane of the subject's eye E, to make measurements of the eye's wave aberrations at 30 Hz.
- This Hartmann-Shack wave-front sensor 202 has 177 lenslets (not individually shown) in a square array 204, which can measure the aberrations for a 6mm pupil up to tenth radial order, corresponding to 63 20 Zernike modes.
- the wave aberration measurements were made at 810nm wavelength.
- the deformable mirror also acted as an aberration generator to blur the subject's vision either with individual Zernike modes or with the wave aberrations of Lasik patients.
- Measurements were on the right eyes of 6 subjects respectively. During the measurement, the subject's head was stabilized with a bite bar, and the subject's pupil was dilated with cyclopentolate hydrochlori.de (2.5%).
- Subjects viewed a binary noise stimulus through adaptive optics system.
- the stimulus used in the matching experiment shown in Fig. 3A, contains sharp edges at all orientations.
- the stimulus pattern was generated randomly by computer.
- the subject viewed the stimulus for 500ms immediately after the deformable mirror generated the standard aberrations or the tested aberration. At other times, the subject viewed a uniform field.
- the artificial pupil diameter was 6 mm, and the test field subtended 1 degree visual angle.
- a Gaussian function smoothed the edge of the field.
- the stimulus was viewed in 550nm monochromatic light.
- the adaptive optics system blurred the subject's vision with a standard aberration or a single Zernike mode alternating in time.
- the standard aberration was created by combining
- the test aberration was only one single Zernike mode whose coefficient could be adjusted by the subject to produce the same subjective blur in the stimulus as the standard aberration.
- Figs. 3B and 3C show, respectively, the standard aberration and one of the test aberrations generated with adaptive optics in one subject's eye.
- the corresponding Zernike modes are shown in Figs. 3D and 3E.
- Each mode has two matching values, one positive and one negative.
- the matching measurement for each mode was performed 8 times, 4 times to match the positive value and 4 times to match the negative value.
- the matching value of one mode to the standard aberration is the average from the absolute values of these 8 matches.
- a similar matching procedure was used to measure the subjective blur produced by patient wave aberrations.
- Figs. 4A-4D show a sample of patient aberrations, while corresponding Figs. 4E-4H show the same aberration generated in the eye of one of the subjects with adaptive optics. Figs.
- FIGS. 5A-5D show the matching procedure in which the subject changed the value of defocus to match the blur caused by the patient aberration.
- the stimulus is the same as that shown in Fig. 3A.
- Figs. 5A-5D show, respectively, the patient wave aberration, defocus, the Zernike modes corresponding to the patient wave aberration, and the Zernike modes corresponding to defocus.
- the reason we chose defocus as the test aberration to quantify the blur caused by the patient wave aberration is that defocus, expressed in diopters is familiar.
- the matching value of defocus to each patient's aberration was measured 4 times at the positive value and 4 times at negative value. The matching value was the average from the absolute of values of these 8 measurements.
- Fig. 6 shows the matching results for individual Zernike modes. The lower the matching value, the stronger the aberration. Aberrations in the center of each order are stronger than those at the edge. This agrees with the simulation in Fig. 7 showing that equal amplitudes of RMS produce large differences in subjective blur. Note that the letters at the center of the pyramid are more blurred than those along the flanks. One can see in Fig. 8 that the wave aberrations along the flanks have relatively large regions where the wavefront is flat, unlike those in the center of the pyramid. Figs. 9A-9C and 10 define two commonly used metrics, RMS wavefront error and
- RMS ⁇ J ( ⁇ (x, y) - mean) 2 .
- Strehl ratio is the ratio of the point spread function of the aberrated eye to the point spread function of a perfect eye, that is, the diffraction-limited point spread function.
- Figs. 9A and 9B show cases for a large RMS and a small RMS, respectively, while Fig. 9C shows a plot of amplitude as a function of aperture.
- Fig. 11 shows that neither of these metrics does a good job of predicting the matching data. This leads us to create a new sharpness metric.
- Fig. 12 is the result using sharpness metric to predict the matching data. Compared with fitting results from RMS wavefront error and Strehl ratio metrics, the neural sharpness metric is much more effective at describing the subjective sharpness of images viewed with the wave aberrations of real eyes.
- Figs. 13A-13C show the correlation between matching value and prediction data from the metrics.
- the sharpness metric did the best at predicting the image quality of the patient's aberrations.
- a wavefront sensor 1502 is in communication with, or has integrated into it, a computer 1504.
- the wavefront sensor 1502 and the computer 1504 perform the following steps shown in Fig. 14: taking the wavefront data, step 1402; determining the wavefront aberration metric, step 1404; providing the neural PSF, step 1406; forming a the maximum of the convolution of the two to form the sharpness metric, step 1408; and determining an optimization of that metric, step 1410.
- the result of the optimization can then be used to control surgery on the eye or the fabrication of a lens (e.g., spectacle, contact, or intraocular) or to generate a prescription for surgery or corrective lenses (Fig. 14, step 1412; Fig. 15, component 1506).
- the steps can be automated.
- Yet another example of the utility of the metric is in retinal imaging.
- the optimization of the metric can be used to control a deformable mirror or other adaptive optical element, as taught in the above-cited U.S. Patent No. 5,777,719, to improve the image of the retina. This would be valuable if, for example, the correction element were incapable of correcting all the aberrations that could be measured with the wavefront sensor.
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Abstract
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
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AU2003225276A AU2003225276A1 (en) | 2002-05-03 | 2003-05-02 | Sharpness metric for vision quality |
EP03721996A EP1501404A4 (fr) | 2002-05-03 | 2003-05-02 | Procede de mesure de l'acuite visuelle pour la qualite de vision |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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US37721902P | 2002-05-03 | 2002-05-03 | |
US60/377,219 | 2002-05-03 |
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WO2003092485A1 true WO2003092485A1 (fr) | 2003-11-13 |
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PCT/US2003/013716 WO2003092485A1 (fr) | 2002-05-03 | 2003-05-02 | Procede de mesure de l'acuite visuelle pour la qualite de vision |
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EP (1) | EP1501404A4 (fr) |
AU (1) | AU2003225276A1 (fr) |
WO (1) | WO2003092485A1 (fr) |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2007073848A2 (fr) | 2005-12-15 | 2007-07-05 | Franz Fankhauser | Dispositif de mesure oculaire par diffusion de lumière dynamique |
US7654674B2 (en) | 2005-11-16 | 2010-02-02 | Bausch & Lomb Incorporated | Method and apparatus for determining the visual acuity of an eye |
JP2014506513A (ja) * | 2011-02-22 | 2014-03-17 | イマジン・アイズ | 高解像度網膜結像方法および装置 |
EP2947505A1 (fr) | 2014-05-22 | 2015-11-25 | Carl Zeiss Vision International GmbH | Procédé permettant de réduire l'épaisseur d'une forme de lentille |
US9784992B2 (en) | 2013-02-11 | 2017-10-10 | Carl Zeiss Vision International Gmbh | Method and system for determining an eyeglass prescription |
US9864212B2 (en) | 2014-05-22 | 2018-01-09 | Carl Zeiss Vision International Gmbh | Method for reducing the thickness of a lens shape and uncut lens blank |
WO2018022765A1 (fr) | 2016-07-27 | 2018-02-01 | Carl Zeiss Vision International Gmbh | Procédé de détermination d'une conception améliorée d'un verre progressif tenant compte des aberrations de degré élevé de l'œil |
CN108307619A (zh) * | 2015-06-23 | 2018-07-20 | 依视路国际公司 | 验光测量表 |
WO2018147834A1 (fr) | 2017-02-07 | 2018-08-16 | Carl Zeiss Vision International Gmbh | Détermination d'ordonnance |
US10775642B2 (en) | 2015-11-23 | 2020-09-15 | Carl Zeiss Vision International Gmbh | Method for designing a lens shape and spectacle lens |
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US5777719A (en) | 1996-12-23 | 1998-07-07 | University Of Rochester | Method and apparatus for improving vision and the resolution of retinal images |
US6338559B1 (en) * | 2000-04-28 | 2002-01-15 | University Of Rochester | Apparatus and method for improving vision and retinal imaging |
US6511180B2 (en) * | 2000-10-10 | 2003-01-28 | University Of Rochester | Determination of ocular refraction from wavefront aberration data and design of optimum customized correction |
-
2003
- 2003-05-02 WO PCT/US2003/013716 patent/WO2003092485A1/fr not_active Application Discontinuation
- 2003-05-02 AU AU2003225276A patent/AU2003225276A1/en not_active Abandoned
- 2003-05-02 EP EP03721996A patent/EP1501404A4/fr not_active Withdrawn
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
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US5777719A (en) | 1996-12-23 | 1998-07-07 | University Of Rochester | Method and apparatus for improving vision and the resolution of retinal images |
US6338559B1 (en) * | 2000-04-28 | 2002-01-15 | University Of Rochester | Apparatus and method for improving vision and retinal imaging |
US6511180B2 (en) * | 2000-10-10 | 2003-01-28 | University Of Rochester | Determination of ocular refraction from wavefront aberration data and design of optimum customized correction |
Non-Patent Citations (1)
Title |
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See also references of EP1501404A4 * |
Cited By (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7654674B2 (en) | 2005-11-16 | 2010-02-02 | Bausch & Lomb Incorporated | Method and apparatus for determining the visual acuity of an eye |
WO2007073848A2 (fr) | 2005-12-15 | 2007-07-05 | Franz Fankhauser | Dispositif de mesure oculaire par diffusion de lumière dynamique |
JP2014506513A (ja) * | 2011-02-22 | 2014-03-17 | イマジン・アイズ | 高解像度網膜結像方法および装置 |
US9784992B2 (en) | 2013-02-11 | 2017-10-10 | Carl Zeiss Vision International Gmbh | Method and system for determining an eyeglass prescription |
EP2947505A1 (fr) | 2014-05-22 | 2015-11-25 | Carl Zeiss Vision International GmbH | Procédé permettant de réduire l'épaisseur d'une forme de lentille |
WO2015178916A1 (fr) | 2014-05-22 | 2015-11-26 | Carl Zeiss Vision International Gmbh | Procédé de réduction de l'épaisseur d'une forme de lentille et ébauche de lentille non taillée |
US9864212B2 (en) | 2014-05-22 | 2018-01-09 | Carl Zeiss Vision International Gmbh | Method for reducing the thickness of a lens shape and uncut lens blank |
CN108307619B (zh) * | 2015-06-23 | 2021-04-23 | 依视路国际公司 | 验光测量表 |
CN108307619A (zh) * | 2015-06-23 | 2018-07-20 | 依视路国际公司 | 验光测量表 |
US10782541B2 (en) | 2015-11-23 | 2020-09-22 | Carl Zeiss Vision International Gmbh | Method for designing a lens shape and spectacle lens |
US10775642B2 (en) | 2015-11-23 | 2020-09-15 | Carl Zeiss Vision International Gmbh | Method for designing a lens shape and spectacle lens |
US10775641B2 (en) | 2015-11-23 | 2020-09-15 | Carl Zeiss Vision International Gmbh | Method for designing a lens shape and spectacle lens |
US10976573B2 (en) | 2015-11-23 | 2021-04-13 | Carl Zeiss Vision International Gmbh | Method for designing a lens shape and spectacle lens |
US10969607B2 (en) | 2016-07-27 | 2021-04-06 | Carl Zeiss Vision International Gmbh | Method for determining an improved design for a progressive lens |
WO2018022765A1 (fr) | 2016-07-27 | 2018-02-01 | Carl Zeiss Vision International Gmbh | Procédé de détermination d'une conception améliorée d'un verre progressif tenant compte des aberrations de degré élevé de l'œil |
WO2018148210A1 (fr) | 2017-02-07 | 2018-08-16 | Carl Zeiss Vision International Gmbh | Détermination de prescription |
EP3610781A1 (fr) | 2017-02-07 | 2020-02-19 | Carl Zeiss Vision International GmbH | Détermination de prescriptions |
US10765313B2 (en) | 2017-02-07 | 2020-09-08 | Carl Zeiss Vision International Gmbh | Prescription determination |
WO2018147834A1 (fr) | 2017-02-07 | 2018-08-16 | Carl Zeiss Vision International Gmbh | Détermination d'ordonnance |
US10863901B2 (en) | 2017-02-07 | 2020-12-15 | Carl Zeiss Vision International Gmbh | Prescription determination |
EP3834707A1 (fr) | 2017-02-07 | 2021-06-16 | Carl Zeiss Vision International GmbH | Détermination de prescription |
Also Published As
Publication number | Publication date |
---|---|
AU2003225276A1 (en) | 2003-11-17 |
EP1501404A1 (fr) | 2005-02-02 |
EP1501404A4 (fr) | 2009-03-04 |
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