Systems and methods for detection of bulk defects on a ophthalmic lenses

Abstract

Methods may include receiving image data captured by an image sensor and may include a plurality of image slices captured at a plurality of height measurements. Methods may include determining a contour of a subject lens in one or more of the plurality of image slices. Methods may include determining, based at least on the respective contour of the subject lens, a center of the subject lens in one or more of the plurality of image slices. Methods may include aligning, based at least on the respective center of the subject lens in the one or more of the plurality of image slices, the plurality of image slices resulting in an aligned plurality of image slices. Methods may include causing an aggregation of the aligned plurality of image slices to be displayed. The aggregation may indicate a through-height representation of the subject lens.

Description

JSV7231USPSP1SYSTEMS AND METHODS FOR DETECTION OF BULK DEFECTS ON A OPHTHALMIC LENSESBACKGROUND

[0001] The bulk material of an ophthalmic lens such as an intraocular lens (IOL) may contain and / or cumulatively develop in time spheroidal, opalescent microvacuoles generally named glistening. These microvacuoles are generally characterized by a different refractive index than the refractive index of a surrounding polymetric matrix. Depending on the density and size, glistenings impact vary from negative cosmetic perception to increased retinal stray light negatively impacting a quality of vision.

[0002] Relative to the materials properties as well as metrology methods, improvements are needed.SUMMARY

[0003] It is to be understood that both the following general description and the following detailed description are exemplary and explanatory only and are not restrictive. Methods and systems for detection of defects in lenses are described. Methods and systems for automatic detection of cosmetic defects in ophthalmic lenses are described.

[0004] A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions.

[0005] In one general aspect, systems may include a holder configured to support a subject lens during examination. Systems may include one or more light sources disposed to illuminate at least a portion of the subject lens during examination. Systems may include a translation stage in mechanical communication with the holder and configured to cause translation of the holderJSV7231USPSP1along at least a first axis. Systems may include an image sensor having a field of view directed along at least the first axis and configured to capture image data indicative of the subject lens during examination. Systems may include a magnification lens optically disposed in the field of view of the image sensor to control at least a magnification. Systems may include a pupil disposed adjacent the magnification lens to control light within at least a portion of the field of view of the image sensor. Systems may include a processor configured to: receive image data captured by the image sensor, where the image data may include a plurality of image slices captured at a plurality of height measurements along the first axis; determine a contour of the subject lens in one or more of the plurality of image slices; determine, based at least on the respective contour of the subject lens in the one or more of the plurality of image slices, a center of the subject lens in one or more of the plurality of image slices; align, based at least on the respective center of the subject lens in the one or more of the plurality of image slices, the plurality of image slices resulting in an aligned plurality of image slices; and cause an aggregation of the aligned plurality of image slices to be displayed, where the aggregation indicates a through-height representation of the subject lens. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

[0006] In one general aspect, systems may include a holder configured to support a subject lens during examination. Systems may include one or more light sources disposed to illuminate at least a portion of the subject lens during examination. Systems may include a translation stage in mechanical communication with the holder and configured to cause translation of the holder along at least a first axis. Systems may include an image sensor having a field of view directed along at least the first axis and configured to capture image data indicative of the subject lens during examination. Systems may include a processor configured to: receive image data captured by the image sensor, where the image data may include a plurality of image slices capture at a plurality of height measurements along the first axis; cause an aggregation of the plurality of image slices to be displayed, where the aggregation indicates a through-height representation of the subject lens. Other embodiments of this aspect include corresponding computer systems,JSV7231USPSP1apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

[0007] In one general aspect, methods may include receiving image data captured by an image sensor. The image data may include a plurality of image slices captured at a plurality of height measurements along a first axis. Methods may include determining a contour of a subject lens in each of the plurality of image slices. Methods may include determining, based at least on the respective contour of the subject lens in each of the plurality of image slices, a center of the subject lens in each of the plurality of image slices. Methods may include aligning, based at least on the respective center of the subject lens in each of the plurality of image slices, the plurality of image slices resulting in an aligned plurality of image slices. Methods may include causing an aggregation of the aligned plurality of image slices to be displayed. The aggregation may indicate a through-height representation of the subject lens. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

[0008] These and other features and advantages are described in greater detail below.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Some features are shown by way of example, and not by limitation, in the accompanying drawings. In the drawings, like numerals reference similar elements.

[0010] Fig. 1 shows an example system for examining lenses described herein.

[0011] Fig. 2 shows an example image slice of an examined lens described herein.

[0012] Fig. 3 shows example processing described herein of the image slice of Fig. 2.

[0013] Fig. 4 shows example processing described herein of the image slice of Fig. 2.

[0014] Fig. 5 shows example processing described herein of the image slice of Fig. 2.

[0015] Fig. 6 shows example processing described herein of the image slice of Fig. 2.

[0016] Figs. 7A-7C show example image slices of an examined lens described herein.

[0017] Fig. 7D shows an example aggregation of the example image slices shown in Figs. 7A-7C.JSV7231USPSP1

[0018] Figs. 8A-8C show an example progression of defects over time.

[0019] Fig. 9 shows a chart of an example progression of defects of time.

[0020] Fig. 10 shows a flowchart of an example method disclosed herein.

[0021] The accompanying drawings show examples of the disclosure. It is to be understood that the examples shown in the drawings and / or discussed herein are non-exclusive and that there are other examples of how the disclosure may be practiced.DETAILED DESCRIPTION

[0022] The accompanying drawings, which form a part hereof, show examples of the disclosure. It is to be understood that the examples shown in the drawings and / or discussed herein are nonexclusive and that there are other examples of how the disclosure may be practiced.

[0023] The present disclosure relates to systems and methods for automatic detection of cosmetic defects of ophthalmic lenses.

[0024] The systems and methods described herein address the issue of glistenings, which may be described as the unwanted presence of spheroidal, opalescent microvacuoles within a bulk material of intraocular lenses (IOLS). Glistenings comprise a different refractive index than a refractive index of a surrounding polymeric matrix. Glistenings may be visible under slit lamp examination. Glistenings may increase retinal stray light and may negatively impact the quality of vision.

[0025] A surgeon performing an IOL examination under a slit lamp may underestimate a functional impact of glistenings relying on subjective assessment. Previous studies proposed a pre-clinical method for evaluating a functional impact of glistenings by relating microvacuole density and size distribution to light scatter.

[0026] The systems and methods described herein relate to an automated glistening detection device. The systems and methods described herein may detect glistening size, density, etc. TheJSV7231USPSP1systems and methods described herein may comprise hardware and / or software components. The systems and methods described herein may enable a high degree of operator independence.

[0027] The systems and methods described herein may comprise a stand-alone bulk cosmetic defects detection device. The systems and methods described herein may comprise dedicated hardware and / or software components. The systems and methods described herein may facilitate operation with few operator interactions. Operator interactions may include placement of a lens sample in a holder of a device described herein, measurement initiation of a device described herein, etc. The systems and methods described herein may comprise automated data acquisition. The systems and methods described herein may comprise automated data post-processing. The systems and methods described herein may comprise segmentation, which may enable analysis of batches of samples characterized by different local levels of contrast. The systems and methods described herein may facilitate dynamic tracking and / or quantification of defects such as glistening, bulk haze, etc.

[0028] Fig. 1 shows an example system 100 for examining a lens described herein. The system 100 may comprise a custom dark field microscope. The lens may comprise an intraocular lens (IOL). The example system 100 may comprise an automatic z-scanning, retro-illuminated microscope.

[0029] The system 100 may comprise an image sensor 110. The image sensor 110 may comprise or be a component of a camera. The image sensor 110 may comprise or be a component of a complementary metal oxide semiconductor (CMOS) image sensor. The image sensor 110 may comprise or be a component of a charge-coupled device (CCD) camera. Other sensors / cameras may be used. The image sensor 110 may comprise and / or be a component of and / or be in communication with one or more processors. The one or more processors may perform one or more methods described herein. The image sensor 110 may be controlled by the one or more processors.

[0030] The system 100 may comprise a magnification lens 120. The magnification lens 120 may comprise an objective lens. The magnification lens 120 may comprise a fixed power. TheJSV7231USPSP1magnification lens 120 may be configured such that an area of interest of the magnification lens 120 is transmitted to the image sensor 110.

[0031] The system 100 may comprise a pupil 130. The pupil 130 may comprise a fixed size. The pupil 130 may comprise an adjustable size. Adjusting the size of the pupil 130 may adjust an F-number associated with the system 100. The image sensor 110 and / or the magnification lens 120 and / or the pupil may be mounted above a light source holder 140.

[0032] The light source holder 140 may comprise a frame 142. The light source holder 140 may comprise a base platform 144. The light course holder 140 may comprise one or more light sources 146. Illumination intensity and / or illumination type associated with the one or more light sources 146 may be controlled by a light control panel. The one or more light sources 146 may comprise and / or be a component of and / or be in communication with a processor. The one or more light sources 146 may be controlled by the one or more processors. The frame 142 may define a boundary of an observation area. A lens undergoing examination may be placed within the frame 142 on the base platform 144. The light source holder 140 may provide a dark field illumination stage for images captured by the image sensor 110. The light source holder 140 may be mounted on a translation stage 150.

[0033] The translation stage 150 may comprise a motorized stage. The translation stage 150 may comprise vertical motion control. The translation stage 150 may be configured for automated z-translation. The translation stage 150 may automatically cause the light source holder 140 to move a predetermined vertical distance. The translation stage 150 may automatically cause the light source holder 140 to move a predetermined vertical distance increment at a predetermined time increment. The translation stage 150 may comprise and / or be a component of and / or be in communication with a processor. The translation stage 150 may be controlled by the one or more processors.

[0034] A lens under examination may be placed in a Petri dish. The Petri dish may comprise a liquid. The liquid may be saline, purified water, etc. The Petri dish and the lens may be placed in the light source holder 140. As explained below, the lens may be examined for haze and / or glistening and / or bubbles to evaluate different lens materials for propensities to have defects. ForJSV7231USPSP1example, a darkfield microscopy image of an acrylic 1 -piece IOL using the systems and methods described herein revealed a glistening free appearance. As another example, a darkfield microscopy image of an IOL made with a different material using the systems and methods described herein enabled visualization and quantification of glistening.

[0035] An exposure associated with the image sensor 110 may be automatically adjusted to provide enough contrast to detect glistenings and / or haze for a broad range of conditions in a lens. The exposure associated with the image sensor 110 may be operated with fixed values to provide enough contrast to detect glistenings and / or haze for a broad range of conditions in a lens. The one or more processors may cause the translation stage 150 to adjust a height of the light source holder 140 in pre-defines steps. A step may be a discrete focal plane at which the one or more processors cause automatic triggering of image acquisition at the image sensor 110. A predefined z-scanning range may comprise the steps. An image taken at a step may be called an image slice. The image slices may be correlated with each other. The image slices may be aligned in a horizontal plane. The image slices may be aggregated into a final through-height image. The image slices may be summed together into a final through-height image. The image slices may be averaged into a final through-height image.

[0036] A lens to be examined may be placed in a Petri dish with saline and the Petri dish may be placed on the base platform 144 within the frame 142 of the light source holder 140 of the system 100. A processor may cause the translation stage 150 to adjust a height of the light source holder 140 to a first height. The processor may cause the one or more light sources 146 to illuminate the lens. The processor may determine if a center of the lens is in a center of a field of view for the image sensor 110 and if not, cause adjustments to be made such that the center of the lens is in the center of the field of view of the image sensor 110. The processor may cause the image sensor 110 to capture a first image (image slice, etc.) at the first height, wherein the first image captured is via the pupil 130 and the magnification lens 120 and comprises details of a first thickness layer of the lens. The processor may cause the translation stage 150 to adjust a height of the light source holder 140 to a second height. The processor may determine if the center of the lens is in the center of the field of view for the image sensor 110 and if not, causeJSV7231USPSP1adjustments to be made such that the center of the lens is in the center of the field of view of the image sensor 110. The processor may cause the image sensor 110 to capture a second image at the second height, wherein the second image captured is via the pupil 130 and the magnification lens 120 and comprises details of a second thickness layer of the lens. The processor may cause the system 100 to continue to capture images at thickness layers of the lens, and then aggregate the images into a single aggregated image.

[0037] Figs. 2-6 show processing associated with an example image slice of an examined lens described herein. The processing may be used to correct for potential misalignment between an optical axis of the image sensor 110 and a displacement axis of the translation stage 150. The processing may be used to correct for potential tilt misalignments. The processing may comprise cross-correlation correction performed between consecutive image slices.

[0038] Fig. 2 shows an example image slice 200 of an examined lens described herein. The lens comprises a contour 202. The contour 202 may be detected using an edge detection algorithm. The edge detection algorithm may detect contrast change associated with an edge of the lens, such as the contrast difference noticeable at the contour 202. As shown, the image slice 200 may show many bubbles formed in the lens, including bubble 204a and bubble 204b. The image slice 200 may show a haze 206 in which the bubbles, such as the bubble 204a and the bubble 204b, formed. The image slice 200 may be processed using the methods described below.

[0039] Fig. 3 shows example processing described herein of the image slice of Fig. 2. Fig. 3 comprises a visual representation 300 of the processing described herein. As shown, the visual representation 300 comprises a representation of the contour 202 after the contour 202 is inputted into a polar unwrapping algorithm resulting in a polar unwrapped contour 302. The edge detection algorithm may comprise the polar unwrapping algorithm.

[0040] Fig. 4 shows example processing described herein of the image slice of Fig. 2. Fig. 4 comprises a visual representation 400 of the processing described herein. In the visual representation 400, polar coordinates 402 associated with the contour 202 may be detected. The polar coordinates 402 may be detected by detecting an edge point associated with each meridianJSV7231USPSP1of the polar unwrapped contour 302. The edge detection algorithm may comprise a step of obtaining the polar coordinates 402 as shown in Fig. 4.

[0041] Fig. 5 shows example processing described herein of the image slice of Fig. 2. Fig. 5 comprises a visual representation 500 of the processing described herein. In the visual representation 500, cartesian coordinates 502 may be created using the polar coordinates 402. The edge detection algorithm may comprise a step of obtaining the cartesian coordinates 502 as shown in Fig. 5.

[0042] Fig. 6 shows example processing described herein of the image slice of Fig. 2. Fig. 6 comprises a visual representation 600 of the processing described herein. In the visual representation 600, a fitted circle 602 may be created using the cartesian coordinates 502. The edge detection algorithm may comprise a step of obtaining the fitted circle 602 as shown in Fig.6. With the fitted circle 602, a center of the fitted circle 602 may be determined. Image slices may be aligned such that a center of a fitted circle of a first image slice aligns with a center of a fitted circle of a second image slice. The processor may cause the system 100 to automatically make adjustments if a first center of a first fitted circle is not aligned with a second center of a second fitted circle such that the first center and the second center come in alignment. A set of image slices may be configured such that a lens in the set of image slices is centered in the set of image slices. Aligning the image slices and / or centering the lens in the image slices allows the processor to detect displacement between image slices and correct alignment before aggregating (e.g., summing, averaging, etc.) the image slices.

[0043] In an embodiment, the edge detection algorithm may bypass the steps described in reference to Figs. 3-6 and instead use template matching to identify a center of a circle, such as the center of the fitted circle 602 shown in Fig. 6. Template matching may comprise matching a first circle with a first diameter in an image with a template comprising a circle representative of a lens with the first diameter. In an embodiment, the alignment of the image slices may not depend on creating a fitted circle and aligning centers of fitted circles, but instead on using a cross correlation function to align consecutive image slices. Using a cross correlation function to align consecutive image slices does not require circle fitting and / or center alignment. Using aJSV7231USPSP1cross correlation function to align consecutive image slices may result in a final combined plurality of image slices comprising a fitted circle. A center of the final combined plurality of image slices may be determined. If the final combined plurality of image slices fails to fit a circle, then a last of the plurality of image slices may be used to estimate a center for analysis for detects, such as glistening.

[0044] Figs. 7A-7C show example image slices of an examined lens described herein. Fig. 7A shows a first image slice 700. The first image slice 700 may comprise a contour 702 of an examined lens. The first image slice 700 may comprise defects such as haze or bubbles (vacuoles, microvacuoles, etc.), such as bubble 704a and bubble 704b. The first image slice 700 may show defects associated with the examined lens at a layer of thickness. A center 706 of the examined lens may be centered in the first image slice 700. The center 706 of the examined lens may be determined using the processing described in reference to Figs. 2-6.

[0045] Fig. 7B shows a second image slice 710. The second image slice 710 may comprise a contour 712 of an examined lens. The second image slice 710 may comprise defects such as haze or bubbles, such as bubble 704c. The second image slice 710 may show defects associated with the examined lens at a layer of thickness. A center 716 of the examined lens may be centered in the second image slice 710. The center 716 of the examined lens may be determined using the processing described in reference to Figs. 2-6. The center 706 in the first image slice 700 may be configured to align with the center 716 in the second image slice 710. The second image slice 710 may comprise an image of a layer of the examined lens comprising a higher height than the image of the layer of the examined lens in the first image slice 700. The second image slice 710 may comprise an image of a layer of the examined lens comprising a lower height than the image of the layer of the examined lens in the first image slice 700.

[0046] Fig. 7C shows a third image slice 720. The third image slice 720 may comprise a contour 722 of an examined lens. The third image slice 720 may comprise defects such as haze or bubbles, such as bubble 704d. The third image slice 720 may show defects associated with the examined lens at a layer of thickness. A center 726 of the examined lens may be centered in the third image slice 720. The center 726 of the examined lens may be determined using theJSV7231USPSP1processing described in reference to Figs. 2-6. The center 706 in the first image slice 700 may be configured to align with the center 726 in the third image slice 720. The center 716 in the second image slice 710 may be configured to align with the center 726 in the third image slice 720. The third image slice 720 may comprise an image of a layer of the examined lens comprising a higher height than the image of the layer of the examined lens in the first image slice 700. The third image slice 720 may comprise an image of a layer of the examined lens comprising a lower height than the image of the layer of the examined lens in the first image slice 700. The third image slice 720 may comprise an image of a layer of the examined lens comprising a higher height than the image of the layer of the examined lens in the second image slice 710. The third image slice 720 may comprise an image of a layer of the examined lens comprising a lower height than the image of the layer of the examined lens in the second image slice 710.

[0047] Fig. 7D shows an example aggregation 730 of the example image slices shown in Figs.7A-7C. The aggregation 730 may comprise a final through-height image. The aggregation 730 may comprise a contour 732 of an examined lens. The aggregation 730 may comprise defects such as haze or bubbles, such as the bubble 704a, the bubble 704b, the bubble 704c, and the bubble 704d. The defects shown in the aggregation 730 may comprise every defect detected in the image slices, such as he first image slice 700, the second image slice 710, and the third image slice 720. The defects shown in the aggregation 730 may comprise an average of defects detected in the image slices. The defects shown in the aggregation 730 may comprise defects that satisfy a defect threshold. The defects shown in the aggregation 730 may comprise defects that appear on a predetermined amount of image slices. A center 736 of the examined lens may be centered in the aggregation 730. The center 736 of the aggregation 730 may be aligned with the centers of the image slices, such as the center 706, the center 716, and the center 726.

[0048] Although only three image slices are shown, the systems and methods described herein may be used with more or less image slices. In an embodiment, the systems and methods described herein take twenty-one image slices for each examined lens, and an image slice may comprise 75 micrometers between an adjacent image slice. Although haze and bubbles areJSV7231USPSP1shown in Figs. 7A-7D, other defects, such as glistening, inclusions through contamination, voids, etc. may be detected in the image slices described above.

[0049] The aggregation 730 may be analyzed to determine properties associated with material used for the examined lens. Properties may include glistening quantification. The systems and / or methods described herein may implement software segmentation. Implementing software segmentation may enable analysis of multiple samples, such as batch analysis, for example. Analysis of multiple samples may be performed to determine glistening properties.Implementing software segmentation may enable a high degree of operator independence. For example, an operator may embed a pixel to millimeter conversion function to compute distances between objects, such as defects, in an image.

[0050] The aggregation 730 may show static defects (e.g., defects present at a moment in time). The aggregation 730 may be used to dynamically track defects over time.

[0051] Implementing software segmentation may comprise automated thresholding. For example, a threshold may be automatically created based on data in the software segmentation to aid in glistening quantification, such as a defect threshold and / or a bubble (vacuole, microvacuole, glistening, etc.) threshold. A defect threshold and / or a bubble threshold may comprise a size threshold, an appearance on a number image slices threshold, an appearance on a percentage of image slices threshold, an illumination contrast threshold, etc. Implementing software segmentation may comprise performing the systems and methods described herein on lenses characterized by multiple local contrast conditions. For example, gamma adjustment may change a brightness and / or contrast associated with captured image slices. Gray level thresholding may be used to determine a lens contour and / or detect defects. Parameters associated with gray level thresholding may be material dependent. For example, a first material may be associated with a first set of gray level thresholding parameters and a second material may be associated with a second set of gray level threshold parameters.

[0052] Figs. 8A-8C show an example progression of defects over time. Fig. 8A may comprise a first image 800a of a lens at a first time after formation. The first time may be immediately after formation. The first time may be, for example, between zero and one hour after formation. TheJSV7231USPSP1first image 800a may comprise a contour 802 of the lens. The first image 800a may comprise a first area of haze 804a. The first image 800a may comprise a first plurality of bubbles (vacuoles, microvacuoles, glistenings, etc.), such as bubble 806a and bubble 806b.

[0053] Fig. 8B may comprise a second image 800b of the lens at a second time after formation. The second time may be after the first time. The second time may be, for example, between zero and five hours after formation. The second image 800b may comprise the contour 802 of the lens. The second image 800b may comprise a second area of haze 804b. The first area of haze 804a may be bigger than the second area of haze 804b. The second image 800b may comprise a second plurality of bubbles (vacuoles, microvacuoles, glistenings, etc.), such as bubble 806a and bubble 806b. There may be more bubbles in the second plurality of bubbles than in the first plurality of bubbles.

[0054] Fig. 8C may comprise a third image 800c of the lens at a third time after formation. The third time may be after the second time. The third time may be, for example, between zero and twenty-four hours after formation. The third image 800c may comprise the contour 802 of the lens. The third image 800c may comprise a third area of haze 804c. The second area of haze 804b and / or the first area of haze 804a may be bigger than the third area of haze 804c. The third image 800c may comprise a third plurality of bubbles (vacuoles, microvacuoles, glistenings, etc.), such as bubble 806a and bubble 806b. There may be less bubbles in the third plurality of bubbles than in the second plurality of bubbles and / or in the first plurality of bubbles.

[0055] Fig. 9 shows a chart 900 of an example progression of defects of time, such as the progression depicted in Figs. 8A-8C. The chart 900 may comprise a horizontal axis 902. The horizontal axis may depict time. Time may be depicted in hours. The chart 900 may comprise vertical lines along the horizontal axis 902 depicting a time increment. Although the time increment shown between vertical lines along the horizontal axis 902 is five hours, any appropriate time increment may be used.

[0056] The chart 900 may comprise a first vertical axis 910. The first vertical axis 910 is shown as a left vertical axis; however, the first vertical axis 910 may be a right vertical axis. The first vertical axis 910 may depict a percentage of the lens comprising haze. The chart 900 mayJSV7231USPSP1comprise horizontal lines along the first vertical axis 910 depicting a percentage increment. Although the percentage increment shown between horizontal lines along the first vertical axis 910 is twenty percent, any appropriate percentage may be used. The percentages depicted on the first vertical axis 910 may be values between zero and one hundred, or, as shown, values between zero and one. The chart 900 may comprise a first structure 915 relating values on the first vertical axis 910 to values on the horizontal axis 902 and representing a haze reading across time.

[0057] The chart 900 may comprise a second vertical axis 920. The second vertical axis 920 is shown as a right vertical axis; however, the second vertical axis 920 may be a left vertical axis. The second vertical axis 920 may depict a count of bubbles (vacuoles, microvacuoles, glistenings, etc.). The chart 900 may comprise horizontal lines along the second vertical axis 920 depicting a count increment. Although the count increment shown between horizontal lines along the second vertical axis 920 is one hundred, any appropriate count may be used. The chart 900 may comprise a second structure 925 relating values on the second vertical axis 920 to values on the horizontal axis 902 and representing a bubble count across time.

[0058] As shown in the chart 900, a material tested using the systems and methods described herein initially had a high haze reading, but by five hours had significantly reduced the haze reading. The material tested also had an initial count of glistening that rose for about the first hour or two and then steadily declined. Other materials tested using the systems and methods described herein may exhibit different haze and / or bubble characteristics over time.

[0059] Information gained from a chart such as the chart 900 may include long term (twenty-four hours, for example) image acquisition. Long term image acquisition may enable visualization of bubble (vacuole, microvacuole, glistening, etc.) progression and / or haze progression. Long term image acquisition may be used with dynamic segmentation for visualization and / or quantification of bulk cosmetic defects, such as bubbles and haze for a material examined.

[0060] The systems and methods described herein may allow for structural robustness in examining lenses. The systems and methods described herein may allow for operatorJSV7231USPSP1independence in examining lenses. The systems and methods described herein may allow for flexibility in examining lenses, allowing for evaluation of a single lens or batch evaluations of multiple lenses. The systems and methods described herein may automatically generate a traceable measurement certificate. The systems and methods described herein may be usable for ophthalmic lenses and polymer buttons manufactured from different optically transparent materials. The systems and methods described herein may allow for flexible segmentation. The systems and methods described herein may allow for figures of merit definition (sectorial and / or cumulative, count and / or density, single time point and / or long-term tracking, etc.). Determining figures of merit may comprise determining size, density, cumulative distribution, radial distribution, average intensity per acquisition for haze, etc. The systems and methods described herein may allow for glistening detection insensitive to haze presence.

[0061] Fig. 10 is a flowchart of an example process 1000. In some implementations, one or more process blocks of Fig. 10 may be performed by a computing device, such as a processor.

[0062] As shown in Fig. 10, process 1000 may include receiving image data. For example, a processor may receive image data (block 1002). The image data may be captured by an image sensor, such as the image sensor 110 in Fig. 1. The image data may comprise a plurality of image slices. The image slices may be captured at a plurality of height measurements along a first axis. The first axis may be a vertical axis. The first axis may be associated with height. The process may be configured to capture a predefined number of image slices. The processor may be configured to cause the height measurements between consecutive image slices to have a predefined height difference.

[0063] As shown in Fig. 10, process 1000 may include determining a contour of a subject lens (block 1004). For example, the processor may determine a contour of a subject lens. The contour of the subject lens may be determined in each of the plurality of image slices or one or more of the image slices. Determining the contour of the subject lens in each of the plurality of image slices may comprise using an edge detection algorithm. The edge detection algorithm may comprise receiving a first image slice. The edge detection algorithm may comprise unwrapping the first image slice to determine polar coordinates associated with the first image slice. OtheJSV7231USPSP1edge detection methods may be used. The edge detection algorithm may comprise detecting a contrast jump associated with the contour of the subject lens. The subject lens may be disposed in a holder, such as a Petri dish. One or more of purified water or saline may be disposed in the holder.

[0064] As shown in Fig. 10, process 1000 may include determining a center of the subject lens (block 1006). For example, the processor may determine a center of the subject lens. The center of the subject lens may be determined in each of the plurality of image slices, or one or more of the image slices. The center of the subject lens may be determined based at least on the respective contour of the subject lens in each of the plurality of image slices, or one or more of the image slices. The contour and center need not be determined in each of the image slices. Determining the center of the subject lens may comprise fitting points associated with the contrast jump into a circle. Determining the center of the subject lens may comprise determining the center of the circle.

[0065] As shown in Fig. 10, process 1000 may include aligning the plurality of image slices (block 1008). For example, the processor may align the plurality of image slices. The plurality of image slices may be aligned based at least on the respective center of the subject lens in each of the plurality of image slices, or one or more of the image slices. Aligning the plurality of image slices may result in an aligned plurality of image slices.

[0066] As shown in Fig. 10, process 1000 may include causing an aggregation of the aligned plurality of image slices to be displayed (block 1010). For example, the processor may cause an aggregation of the aligned plurality of image slices to be displayed. The aggregation may indicate a through-height representation of the subject lens. A location of the subject lens indicated by the aggregation of the aligned plurality of image slices may comprise a defect if any of the plurality of image slices indicate a defect in the location. A location of the subject lens indicated by the aggregation of the aligned plurality of image slices may comprise a defect if most of the plurality of image slices indicate a defect in the location. A location of the subject lens indicated by the aggregation of the aligned plurality of image slices may comprise a defect ifJSV7231USPSP1any of the plurality of image slices indicate a defect in the location, and the defect satisfies a defect threshold.

[0067] Although Fig. 10 shows example blocks of process 1000, in some implementations, process 1000 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in Fig. 10. Additionally, or alternatively, two or more of the blocks of process 1000 may be performed in parallel.EXAMPLE CLAUSES

[0068] Example Clause 1 : A system for examining a lens, the system may include: a holder configured to support a subject lens during examination; one or more light sources disposed to illuminate at least a portion of the subject lens during examination; a translation stage in mechanical communication with the holder and configured to cause translation of the holder along at least a first axis; an image sensor having a field of view directed along at least the first axis and configured to capture image data indicative of the subject lens during examination; a magnification lens optically disposed in the field of view of the image sensor to control at least a magnification; a pupil disposed adjacent the magnification lens to control light within at least a portion of the field of view of the image sensor; and a processor configured to: receive image data captured by the image sensor, where the image data may include a plurality of image slices captured at a plurality of height measurements along the first axis; determine a contour of the subject lens in each of the plurality of image slices; determine, based at least on the respective contour of the subject lens in each of the plurality of image slices, a center of the subject lens in each of the plurality of image slices; align, based at least on the respective center of the subject lens in each of the plurality of image slices, the plurality of image slices resulting in an aligned plurality of image slices; and cause an aggregation of the aligned plurality of image slices to be displayed, where the aggregation indicates a through-height representation of the subject lens.JSV7231USPSP1

[0069] Example Clause 2: The system of Example Clause 1, where a location of the subject lens indicated by the aggregation of the aligned plurality of image slices may include a defect if any of the plurality of image slices indicate a defect in the location.

[0070] Example Clause 3: The system of Example Clause 1 or Example Clause 2, where a location of the subject lens indicated by the aggregation of the aligned plurality of image slices may include a defect if most of the plurality of image slices indicate a defect in the location.

[0071] Example Clause 4: The system of any one of Example Clauses 1-3, where a location of the subject lens indicated by the aggregation of the aligned plurality of image slices may include a defect if any of the plurality of image slices indicate a defect in the location, and where the defect satisfies a defect threshold.

[0072] Example Clause 5: The system of any one of Example Clauses 1-4, where the determine the contour of the subject lens in each of the plurality of image slices may include using an edge detection algorithm.

[0073] Example Clause 6: The system of any one of Example Clauses 1-5, where the edge detection algorithm may include: receiving a first image slice; unwrapping the first image slice to determine polar coordinates associated with the first image slice; and detecting a contrast jump associated with the contour of the subject lens.

[0074] Example Clause 7: The system of any one of Example Clauses 1-6, where the determine the center of the subject lens in each of the plurality of image slice may include: fitting points associated with the contrast jump into a circle; and determining the center of the circle.

[0075] Example Clause 8: The system of any one of Example Clauses 1-7, where the holder may include one or more of purified water or saline.

[0076] Example Clause 9: The system of any one of Example Clauses 1-8, where the translation stage is automatically adjusted by a predefined height increment, and where the translation stage is automatically adjusted a predefined number of times.

[0077] Example Clause 10: A system for examining a lens, the system may include: a holder configured to support a subject lens during examination; one or more light sources disposed to illuminate at least a portion of the subject lens during examination; a translation stage inJSV7231USPSP1mechanical communication with the holder and configured to cause translation of the holder along at least a first axis; an image sensor having a field of view directed along at least the first axis and configured to capture image data indicative of the subject lens during examination; a processor configured to: receive image data captured by the image sensor, where the image data may include a plurality of image slices capture at a plurality of height measurements along the first axis; cause an aggregation of the plurality of image slices to be displayed, where the aggregation indicates a through-height representation of the subject lens.

[0078] Example Clause 11: The system of Example Clause 10, where a location of the subject lens indicated by the aggregation of the plurality of image slices may include a defect if any of the plurality of image slices indicate a defect in the location.

[0079] Example Clause 12: The system of Example Clause 10 or Example Clause 11, where a location of the subject lens indicated by the aggregation of the plurality of image slices may include a defect if most of the plurality of image slices indicate a defect in the location.

[0080] Example Clause 13: The system of any one of Example Clauses 10-12, where a location of the subject lens indicated by the aggregation of the plurality of image slices may include a defect if any of the plurality of image slices indicate a defect in the location, and where the defect satisfies a defect threshold.

[0081] Example Clause 14: The system of any one of Example Clauses 10-13, further may include determining a contour of the subject lens in each of the plurality of image slices using an edge detection algorithm.

[0082] Example Clause 15: The system of any one of Example Clauses 10-14, where the edge detection algorithm may include: receiving a first image slice; unwrapping the first image slice to determine polar coordinates associated with the first image slice; and detecting a contrast jump associated with the contour of the subject lens.

[0083] Example Clause 16: The system of any one of Example Clauses 10-15, further may include determining a center of the subject lens in each of the plurality of image slices.JSV7231USPSP1

[0084] Example Clause 17: The system of any one of Example Clauses 10-16, further may include: fitting points associated with the contrast jump into a circle; and determining the center of the circle.

[0085] Example Clause 18: The system of any one of Example Clauses 10-17, where the holder may include one or more of purified water or saline.

[0086] Example Clause 19: The system of any one of Example Clauses 10-18, where the translation stage is automatically adjusted by a predefined height increment, and where the translation stage is automatically adjusted a predefined number of times.

[0087] Example Clause 20: A method for examining a lens may include: receiving image data captured by an image sensor, where the image data may include a plurality of image slices captured at a plurality of height measurements along a first axis; determining a contour of a subject lens in each of the plurality of image slices; determining, based at least on the respective contour of the subject lens in each of the plurality of image slices, a center of the subject lens in each of the plurality of image slices; aligning, based at least on the respective center of the subject lens in each of the plurality of image slices, the plurality of image slices resulting in an aligned plurality of image slices; and causing an aggregation of the aligned plurality of image slices to be displayed, where the aggregation indicates a through-height representation of the subject lens.

[0088] Example Clause 21: The method of Example Clause 20, where a location of the subject lens indicated by the aggregation of the aligned plurality of image slices may include a defect if any of the plurality of image slices indicate a defect in the location.

[0089] Example Clause 22: The method of Example Clause 20 or Example Clause 21, where a location of the subject lens indicated by the aggregation of the aligned plurality of image slices may include a defect if most of the plurality of image slices indicate a defect in the location.

[0090] Example Clause 23: The method of any one of Example Clauses 20-22, where a location of the subject lens indicated by the aggregation of the aligned plurality of image slices may include a defect if any of the plurality of image slices indicate a defect in the location, and where the defect satisfies a defect threshold.JSV7231USPSP1

[0091] Example Clause 24: The method of any one of Example Clauses 20-23, where the determining the contour of the subject lens in each of the plurality of image slices may include using an edge detection algorithm.

[0092] Example Clause 25: The method of any one of Example Clauses 20-24, where the edge detection algorithm may include: receiving a first image slice; unwrapping the first image slice to determine polar coordinates associated with the first image slice; and detecting a contrast jump associated with the contour of the subject lens.

[0093] Example Clause 26: The method of any one of Example Clauses 20-25, where the determining the center of the subject lens in each of the plurality of image slices, further may include: fitting points associated with the contrast jump into a circle; and determining the center of the circle.

[0094] The foregoing disclosure provides illustration and description but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications may be made in light of the above disclosure or may be acquired from practice of the implementations. As used herein, the term “component” is intended to be broadly construed as hardware, firmware, or a combination of hardware and software. It will be apparent that systems and / or methods described herein may be implemented in different forms of hardware, firmware, and / or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not limiting of the implementations. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code - it being understood that software and hardware can be used to implement the systems and / or methods based on the description herein. As used herein, satisfying a threshold may, depending on the context, refer to a value being greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, and / or the like, depending on the context. Although particular combinations of features are recited in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of various implementations. In fact, manyJSV7231USPSP1of these features may be combined in ways not specifically recited in the claims and / or disclosed in the specification

[0095] Although each dependent claim listed below may directly depend on only one claim, the disclosure of various implementations includes each dependent claim in combination with every other claim in the claim set. No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items and may be used interchangeably with “one or more.” Further, as used herein, the article “the” is intended to include one or more items referenced in connection with the article “the” and may be used interchangeably with “the one or more.” Furthermore, as used herein, the term “set” is intended to include one or more items (e.g., related items, unrelated items, a combination of related and unrelated items, and / or the like), and may be used interchangeably with “one or more.” Where only one item is intended, the phrase “only one” or similar language is used. Also, as used herein, the terms “has,” “have,” “having,” or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. Also, as used herein, the term “or” is intended to be inclusive when used in a series and may be used interchangeably with “and / or,” unless explicitly stated otherwise (e.g., if used in combination with “either” or “only one of’).

Claims

JSV7231USPSP1CLAIMSWhat is claimed is:

1. A system for examining a lens, the system comprising:a holder configured to support a subject lens during examination;one or more light sources disposed to illuminate at least a portion of the subject lens during examination;a translation stage in mechanical communication with the holder and configured to cause translation of the holder along at least a first axis;an image sensor having a field of view directed along at least the first axis and configured to capture image data indicative of the subject lens during examination;a magnification lens optically disposed in the field of view of the image sensor to control at least a magnification;a pupil disposed adjacent the magnification lens to control light within at least a portion of the field of view of the image sensor; anda processor configured to:receive image data captured by the image sensor, wherein the image data comprises a plurality of image slices captured at a plurality of height measurements along the first axis;align the plurality of image slices resulting in an aligned plurality of image slices;andcause an aggregation of the aligned plurality of image slices to be displayed, wherein the aggregation indicates a through-height representation of the subject lens.

2. The system of claim 1, wherein a location of the subject lens indicated by the aggregation of the aligned plurality of image slices comprises a defect if any of the plurality of image slices indicate a defect in the location.JSV7231USPSP13. The system of claim 1, wherein a location of the subject lens indicated by the aggregation of the aligned plurality of image slices comprises a defect if most of the plurality of image slices indicate a defect in the location.

4. The system of claim 1, wherein a location of the subject lens indicated by the aggregation of the aligned plurality of image slices comprises a defect if any of the plurality of image slices indicate a defect in the location, and wherein the defect satisfies a defect threshold.

5. The system of claim 1, wherein the processor is further configured to:determine a contour of the subject lens in one or more of the plurality of image slices; determine, based at least on the respective contour of the subject lens in the one or more of the plurality of image slices, a center of the subject lens in one or more of the plurality of image slices; andwherein the aligning the plurality of image slices resulting in an aligned plurality of image slices is based at least on the respective center of the subject lens in the one or more of the plurality of image slices.

6. The system of claim 5, wherein the determination of the contour of the subject lens in the one or more of the plurality of image slices comprises using an edge detection algorithm.

7. The system of claim 6, wherein the edge detection algorithm comprises:receiving a first image slice;unwrapping the first image slice to determine polar coordinates associated with the first image slice; anddetecting a contrast jump associated with the contour of the subject lens.

8. The system of claim 7, wherein the determination of the center of the subject lens in the one or more of the plurality of image slice comprises:fitting points associated with the contrast jump into a circle; anddetermining the center of the circle.

9. The system of claim 1, wherein the holder comprises one or more of purified water or saline.JSV7231USPSP110. The system of claim 1, wherein the translation stage is automatically adjusted by a predefined height increment, and wherein the translation stage is automatically adjusted a predefined number of times.

11. The system of claim 1, wherein the aligning the plurality of image slices resulting in an aligned plurality of image slices comprises using a cross correlation function to align consecutive image slices.

12. The system of claim 11, wherein the processor is further configured to:determine a center of the aggregation of the aligned plurality of image slices.

13. The system of claim 1, wherein the aggregation of the aligned plurality of image slices shows one or more defects.

14. The system of claim 13, wherein the one or more defects are one or more of glistening and haze.

15. The system of claim 13, wherein the aggregation of the aligned plurality of image slices shows one or more defects statically.

16. The system of claim 13, wherein the aggregation of the aligned plurality of image slices allow dynamic tracking of one or more defects over time.

17. The system of claim 13, wherein the aggregation of the aligned plurality of image slices comprise determining a figure of merit.

18. The system of claim 17, wherein the figure of merit comprises one or more of size, density, cumulative distribution, radial distribution, and average intensity per acquisition for one or more defects.

19. The system of claim 1, wherein the aligning the plurality of image slices resulting in an aligned plurality of image slices comprises matching a template, wherein the template comprises a circle comprising a first diameter, and wherein the subject lens comprises the first diameter.

20. A system for examining a lens, the system comprising:a holder configured to support a subject lens during examination;JSV7231USPSP1one or more light sources disposed to illuminate at least a portion of the subject lens during examination;a translation stage in mechanical communication with the holder and configured to cause translation of the holder along at least a first axis;an image sensor having a field of view directed along at least the first axis and configured to capture image data indicative of the subject lens during examination;a processor configured to:receive image data captured by the image sensor, wherein the image data comprises a plurality of image slices capture at a plurality of height measurements along the first axis;cause an aggregation of the plurality of image slices to be displayed, wherein the aggregation indicates a through-height representation of the subject lens.

21. The system of claim 20, wherein a location of the subject lens indicated by the aggregation of the plurality of image slices comprises a defect if any of the plurality of image slices indicate a defect in the location.

22. The system of claim 20, wherein a location of the subject lens indicated by the aggregation of the plurality of image slices comprises a defect if most of the plurality of image slices indicate a defect in the location.

23. The system of claim 20, wherein a location of the subject lens indicated by the aggregation of the plurality of image slices comprises a defect if any of the plurality of image slices indicate a defect in the location, and wherein the defect satisfies a defect threshold.

24. The system of claim 20, further comprising determining a contour of the subject lens in each of the plurality of image slices using an edge detection algorithm.

25. The system of claim 24, wherein the edge detection algorithm comprises:receiving a first image slice;JSV7231USPSP1unwrapping the first image slice to determine polar coordinates associated with the first image slice; anddetecting a contrast jump associated with the contour of the subject lens.

26. The system of claim 25, further comprising determining a center of the subject lens in each of the plurality of image slices.

27. The system of claim 26, further comprising:fitting points associated with the contrast jump into a circle; anddetermining the center of the circle.

28. The system of claim 20, wherein the holder comprises one or more of purified water or saline.

29. The system of claim 20, wherein the translation stage is automatically adjusted by a predefined height increment, and wherein the translation stage is automatically adjusted a predefined number of times.

30. A method for examining a lens comprising:receiving image data captured by an image sensor, wherein the image data comprises a plurality of image slices captured at a plurality of height measurements along a first axis;determining a contour of a subject lens in one or more of the plurality of image slices; determining, based at least on the respective contour of the subject lens in the one or more of the plurality of image slices, a center of the subject lens in one or more of the plurality of image slices;aligning, based at least on the respective center of the subject lens in the one or more of the plurality of image slices, the plurality of image slices resulting in an aligned plurality of image slices; andcausing an aggregation of the aligned plurality of image slices to be displayed, wherein the aggregation indicates a through-height representation of the subject lens.JSV7231USPSP131. The method of claim 30, wherein a location of the subject lens indicated by the aggregation of the aligned plurality of image slices comprises a defect if any of the plurality of image slices indicate a defect in the location.

32. The method of claim 30, wherein a location of the subject lens indicated by the aggregation of the aligned plurality of image slices comprises a defect if most of the plurality of image slices indicate a defect in the location.

33. The method of claim 30, wherein a location of the subject lens indicated by the aggregation of the aligned plurality of image slices comprises a defect if any of the plurality of image slices indicate a defect in the location, and wherein the defect satisfies a defect threshold.

34. The method of claim 30, wherein the determining the contour of the subject lens in the one or more of the plurality of image slices comprises using an edge detection algorithm.

35. The method of claim 34, wherein the edge detection algorithm comprises:receiving a first image slice;unwrapping the first image slice to determine polar coordinates associated with the first image slice; anddetecting a contrast jump associated with the contour of the subject lens.

36. The method of claim 35, wherein the determining the center of the subject lens in the one or more of the plurality of image slices, further comprising:fitting points associated with the contrast jump into a circle; anddetermining the center of the circle.

Images