PROCEDURE OF EVALUATION OF THE STABILITY OF A TEAR FILM

Abstract

A method for measuring the stability of a patient's tear film using a device comprising a backlit translucent plate equipped with a target positioned in front of at least one eye (101) of a patient (100), at least one digital camera connected to a computing system equipped with image processing and analysis means, a camera lens pointing towards the patient's eye to photograph a reflection of the target pattern on the patient's eye, the method comprising, from a time origin (t0) constituted by a blink of the eye, a succession of image acquisitions (200), a succession of detections of micro-movement zones in the images (510), and calculation and storage of position, area, and number of micro-movement zones (520) of the tear film in each image using the image processing and analysis means, and the calculation (530) and storage (540),Based on a series of calculations of the surface area and number of micro-movement zones of the tear film, and a measurement of the amplitude of the micro-movement zones as a function of time. Figure 14,

Description

Title of the invention: METHOD FOR EVALUATING THE STABILITY OF A TEAR FILM technical field

[0001] The invention relates to the field of detection of dry eye syndrome. Previous technique

[0002] Tests for evaluating dry eye syndrome have traditionally relied on a fluorescence test. The practitioner instills a drop of fluorescein into the patient's eye, and the fluorescence phenomenon is observed using a slit lamp. The practitioner determines the time between blinking and the appearance of the first non-fluorescent area. This time is the measurement of the ocular film breakup time, or BUT. This method allows for the measurement of an initial breakup, whether due to a local defect such as dust or a genuine dry eye problem. The measured times are on the order of 6 to 10 seconds.

[0003] Another evaluation method, called "Non-Invasive Breakup Time" or NIBUT, is a non-invasive method for measuring breakup time. Tests using this method notably employ the reflection on the cornea of ​​a target equipped with a pattern consisting of concentric circles and radial lines.

[0004] When a break in the film appears, the reflected pattern shows distortions of lines and / or circles or missing areas.

[0005] Images of the reflected pattern are acquired in sequence by a camera and processed by a computerized processing system which analyzes the evolution of the pattern over time to detect deformations of the pattern and deduce the time of appearance of the film break zones. Technical problem

[0006] Currently available devices using circular patterns and radial lines cause problems of several kinds:

[0007] Given the shape of the targets, and the coverage of the cornea by disc sectors, the spatial resolution is intrinsically less good on the edges of the field than at the center.

[0008] Moreover, in the center of the field, where the radial lines converge, it is difficult to determine the deformation of a pattern.

[0009] Increasing the spatial resolution would require tightening the target pattern. However, the circle distortion detection algorithms, which require finding the most probable circles in the image and evaluating whether a point in the image belongs to a probable circle and to calculate the distance from a given point to the circle to which it is supposed to belong are complex and the processing and computation time to detect break zones from the image is significant.

[0010] It is therefore clear that: on the one hand, devices presenting the classic pattern of concentric circles and radial lines suffer from a lack of homogeneity of spatial resolution, on the other hand, increasing the resolution at the edge of the field is penalizing on computation times.

[0011] Due to the low resolution of this method, the measurement may give inaccurate and overestimated values ​​for the occurrence of breaks.

[0012] It should be noted in particular that the measurements obtained by the fluorescence method and the non-invasive method are generally not well correlated: a factor of 2 between the BUT and NIBUT measurements is commonly observed, with the fluorescence measurement showing a shorter time. This suggests a lack of sensitivity or resolution in the NIBUT devices.

[0013] Similarly, the times displayed in NIBUT on different available devices are also not well correlated.

[0014] In the diagnosis of dry eye syndrome, measurements obtained by measuring break up time with fluorescein or measurements obtained by a NIBUT method are not correlated with the suffering expressed by the patient.

[0015] The previous methods are not revealing of the overall state of the tear film. Description of the invention

[0016] The invention improves the situation and proposes a method for measuring the stability of the tear film on the cornea of ​​a patient, based on the detection of changes in this film and using a device comprising a pattern made up of horizontal or vertical light and dark lines, and observing the reflection of this pattern on the cornea.

[0017] To do this, within the framework of the present application we will search for micromovements at the level of the tear film by analyzing the images of the lines of the target.

[0018] A micro-movement is defined as a local variation in the overall thickness of the tear film. This variation induces slopes on the surface of the tear film, which will be manifested by a localized modification of the image of the target lines and in particular by modifications in the width of the image of these lines or local deformations.

[0019] More specifically, the present application proposes a method for measuring the stability of a patient's tear film using a device comprising a backlit translucent plate equipped with a target positioned in front of at least one eye of a patient, and at least one digital camera connected to a computing system equipped with image processing and analysis means, a camera lens pointing towards the patient's eye in order to photograph a reflection of the target pattern on the patient's eye, characterized in that, the target being provided with a pattern consisting of a succession of alternating light and dark lines reflecting on the patient's eye, the image processing and analysis means are configured to detect deformations of said light or dark lines of the target pattern reflected on the patient's eye and to identify, by a comparison of the position of image points of the edge of the lines with respect to an estimated edge of the lines, the micro-movements of the tear film revealed by these deformations, said method comprising, from a time origin t0 constituted by a blink of the eye, a succession of image captures,a succession of detections of micro-movement zones in the images and a succession of calculations and storage of position and number of micro-movement zones of the tear film in each image using image processing and analysis means, and the calculation, from the succession of calculations of positions and number of micro-movement zones of the tear film, of a measure of the average amplitude of the micro-movement zones as a function of time.

[0020] The measurement carried out has the advantage of giving an image of the variations in thickness of the ocular film, film too thin or broken locally along a measurement sequence.

[0021] The features described in the following paragraphs may optionally be implemented. They may be implemented independently of each other or in combination with each other:

[0022] The method may include taking an image (200) every 0.1 to 0.5 seconds and preferably every 0.3 seconds.

[0023] Said sequence of image captures ends advantageously with the first arrival of one of the events: end of a time delay or detection of a subsequent blink of the eyelid.

[0024] The method may include tracking the patient's eye or eyes by means of an iris tracking method so as to reposition the areas of micro-movements of the tear film detected and memorized relative to the eye analyzed.

[0025] The estimated line edges can be calculated by polynomial regression.

[0026] The method may include determining a population of points representative of the micro-movement zones observed on the image of the lines by calculating, along the lines, the absolute value of the distance to the polynomial along the axis perpendicular to the general direction of the lines of the pixels PI to Pn of the edges of the lines of the image which are deviated from the polynomial by a distance dP in pixels greater than a threshold and storing for the representative points PI to Pn the distances dPl to dPn.

[0027] The method may include, for each image, on said population of points represented sentants, a calculation for each pixel PI to Pn of the equivalent surface Sp = dP x pixel width x pixel height and a calculation of the sum S p of the equivalent surfaces SP1 to SPn of the image points to their polynomial over the whole image and a calculation of a normalized sum NE Sp of said distances by means of the division of the sum V 5 p by the total length of the lines found on the image.

[0028] The method may include calculating an overall score consisting of the sum A of the normalized sums NV Sp on a series of images from the origin of time tO up to a given instant t.

[0029] The duration of the measurements can be chosen according to a patient population, a duration of around 6 seconds appearing sufficient to detect problems of dry eye while avoiding reaching a risk of blinking.

[0030] The method may include memorizing the positions of the micromovement zones and generating a map of the micromovement locations image by image.

[0031] The method may include calculating and storing the time of appearance of micro-movement points of the tear film and / or the kinetics of appearance of micro-movement points of the tear film.

[0032] The method may include storing in a database all or part of the calculated data in order to carry out patient follow-up and comparison of said data over several examinations.

[0033] According to another aspect, a computer program is proposed comprising instructions for the implementation of all or part of a process as defined herein when this program is executed by a processor.

[0034] According to another aspect of the invention, a non-transient, computer-readable recording medium is proposed on which such a program is recorded.

[0035] The invention and variants thereof can generally provide a method for measuring the evolution of irregularities in a tear film over a defined examination period, offering increased precision compared to existing methods for detecting ruptures in such a tear film.

[0036] Such a solution, which is based on a measurement of the film deformations and their evolution over time, makes it possible to solve the problems posed by known solutions by offering high repeatability of measurements. Brief description of the drawings

[0037] Other features, details and advantages of the invention will become apparent from reading the detailed description below, and from analyzing the accompanying drawings, in which:

[0038] [fig. 1] is a front flat view of a target provided with a motif of the invention;

[0039] [fig. 2] is a schematic view of a device of the present application;

[0040] [fig.3] shows a first example of a measurement support usable within the framework of the present request;

[0041] [fig.4] represents an image of a patient's eye following a first step of treatment ;

[0042] [Fig. 5A], [Fig. 5B], [Fig. 5C], [Fig. 5D], [Fig. 5E] represent various stages of processing the image of the eye in figure 4;

[0043] [fig.6A], [Fig. 6B] represent details of figure 5E;

[0044] [fig.7] represents an image of the eye in figure 4 after image analysis;

[0045] [fig.8] represents an image of a patient's eye looking towards a camera;

[0046] [Fig. 9A], [Fig. 9B], [Fig. 9C] represent steps in determining the position of the iris of the eye in figure 8 according to one aspect of the application;

[0047] [fig.10] represents an image of a patient's eye whose gaze deviates from a camera;

[0048] [fig.HA], [Fig. 11B], [Fig. 11C] represent steps in determining the position of the iris of the eye in Figure 10 according to one aspect of the application;

[0049] [fig.12] schematically illustrates a method for detecting points offset according to an aspect of the request;

[0050] [fig.13] schematically illustrates a method for repositioning line deformations image of a test pattern;

[0051] [fig.14] Schematic representation of the first steps in the application process;

[0052] [fig.15] schematizes subsequent steps in the application process;

[0053] [fig.16] represents a first graph with smoothed value curves for several patients;

[0054] [fig.17] represents a second graph with cumulative value curves for several patients. Description of the implementation methods

[0055] The drawings and description below describe one or more examples of implementation which may therefore not only serve to better understand the objects of this application, but also contribute to its definition, if necessary.

[0056] The method according to the present application uses a measuring device comprising a target 10 shown in Figure 1 and made from a transparent polymer film having a pattern 11 formed by alternating straight and parallel lines 12, 13. The pattern includes opaque lines 12, for example black lines separated by transparent lines 13 allowing light from a light source to pass through a translucent support behind the pattern to produce clear lines such that the clear lines of the pattern are reflected onto the eye or eyes of a patient.

[0057] According to the example, the pattern 11 of the target 10 comprises twelve opaque lines 12, not counting the upper and lower edges of the target. These opaque lines are separated by transparent lines 13 and centered around a central translucent line. The target can be mounted on a plastic frame to make it easier to handle.

[0058] By convention, a horizontal axis will be called an axis parallel to an axis passing through the patient's eyes and a vertical axis will be called the axis perpendicular to this axis and in the illustrated example, the lines of the pattern are horizontal.

[0059] As shown in Figure 2, the target 10 on its plastic support 10b is positioned on a translucent support 10a, itself pierced with holes for the camera lenses, and the device uses a diffuse light source 23 behind the support of the pattern to illuminate the pattern. The reflection of the pattern is observed by one or two digital cameras, and, to observe both eyes, two digital cameras 21, 22 are provided.

[0060] The diffuse light source 23 can be achieved by means of an integrating box or sphere or in a manner similar to an LCD screen backlight for example.

[0061] The target is provided with two recessed areas 14 centered within opaque frames 15 on a horizontal midline. The recessed areas are separated by a distance corresponding to the average interpupillary distance as shown in Figure 1. Referring back to Figure 2, the cameras are positioned behind the recessed areas and are located in front of the eyes 101 of the patient 100. The camera lenses film or photograph the patient's eyes through the recessed areas. The recessed areas can be replaced by transparent substrate areas of the target if the optical properties of the target substrate and its level of cleanliness are compatible with image formation (transparent and non-diffusing).

[0062] The cameras are, for example, 1 / 4" sensor CMOS type cameras. According to the non-limiting example shown, the transparent areas are circular holes with a diameter adapted to the camera lenses. For cameras with focal length lenses of approximately 4 mm, holes of approximately 14 mm are made, and the opaque frames are opaque squares of approximately 16 mm x 16 mm. These frames are intended to precisely finish the lines upstream of the holes receiving the camera lenses.

[0063] In the embodiment example, the camera(s) provide images with a definition of 1920x1080 which is sufficient for an analysis of the eye film without increasing the computational load of the system.

[0064] The video signals from the cameras are sent to a computerized processing device 30 or computing system, internal or external to the measuring device and, to avoid duplicating this processing device, the video signals from both cameras pass through a multiplexer, on an electronic card 24 of the device, the multiplexer allowing to send one or the other of the video channels at choice to the processing device 30.

[0065] The cameras film or photograph the image of the pattern lines reflected in the patient's cornea. Since the cornea can be considered, at first glance, as a spherical diopter, it exhibits significant field curvature, and the image displays considerable distortion. In order to at least partially compensate for this distortion and to preserve lines in the captured images whose width varies little from the median axis of the pattern to the edge of the image, the pattern of the target includes lines with a period increasing from the central axis of the pattern to the edges of the support parallel to the lines. The width of the lines is on the order of 2 to 4 mm, depending on the desired resolution.For example, a central white line might be approximately 2.8 mm high, the adjacent black lines 2.2 mm high, the last white lines 3.8 mm high, and the black lines preceding these white lines 2.8 mm high, the progression being optimized to compensate for the curvature of a standard eye. In the described method, light lines are used to search for variations in width or line distortions, but dark lines can also be used. The number and width of the light lines may differ from the examples given but are chosen to obtain sufficient definition for meaningful detection of film distortion areas, depending on the resolution of the camera(s).

[0066] In the principle of the present application, the white lines are reflected by the comet diopter and stand out when they are backscattered in the bulbar conjunctiva of the eye and the iris where the alternation of dark lines and light lines creates a continuous background that is more or less luminous depending on the ratio between the transparent surfaces of the target and its total surface.

[0067] In figure 2, the target seen from above is curved around a vertical axis to form a portion of a cylinder and follow the curvature of the patient's head 100 so that the image of the target covers a large part of the cornea.

[0068] The reasons are: a. Optical conjugation: The camera sees the reflection of the target on the cornea, which is initially considered a spherical mirror with a radius of approximately 8 mm, corresponding to a focal length of 4 mm. Given this short focal length, the target (the object in the optical conjugate) must be large enough for the image formed by the cornea to be sufficiently large, comparable in size to the outer diameter of the iris. This determines the size of the mask. b. Photometry: For the target to be visible, light rays from the edges must pass through it. The extremes of the target enter the pupil of the objective. Since the cornea is a highly curved mirror, the light rays arriving at the edge of the field of view must be grazing.

[0069] This is what justifies the curvature of the target.

[0070] According to Figure 3, the measuring device is mounted on an ophthalmic frame with A chin and forehead support comprising uprights 44, 46, and a housing 43 that integrates the cameras and receives the target 10 on a curved front face in front of which the patient will position themselves, chin resting on a support 45. On such a frame, the patient's eyes are at a distance of approximately 50 mm from the target for a camera focal length of 4 mm. The measuring device can also be integrated into a helmet worn by the patient.

[0071] The focal length and distance are chosen to allow the entire eye to be seen, taking into account variations in the eye's position relative to the camera (interocular distance differs from one individual to another). Next, a window of interest centered on the patient's pupil is selected by the operator pointing the center of the pupil at the image.

[0072] So that the lines of the target are sharp on the image, the focus is adjusted with a wheel 42.

[0073] The measurement method of this application is intended to detect and measure the extent and areas of instability in the tear film that result in distortions of the reflected lines. It comprises repeated exposures of one or both eyes of the patient at a repetition frequency of approximately 0.1 to 0.5 seconds, and in practice, 0.3 seconds after a blink of the eye.

[0074] The method is described primarily in the context of a horizontal line target, i.e., along an axis passing through the patient's two pupils, but is adaptable, notably by rotating the pixel array processing means and the anisotropic bandpass filter described below by 90°. Furthermore, the method described for detecting light lines can be applied to detecting dark lines.

[0075] Using horizontal or vertical lines rather than inclined lines is advantageous because image processing along lines or columns of pixels is the simplest to perform.

[0076] The measurement steps in the computing system 30 include image processing steps which, starting from a capture of the original image of the patient's eye, include; - a conversion of the image to grayscale according to step 205 of Figure 12, an example of which is shown in Figure 4, where the image 51 of the pattern on the iris 50 is distinguished from the image of the frame 52 surrounding the camera lens. On this image and the original color image, the shape of the reflected light lines includes local defects (in particular irregular line edges which already reveal deformations of the tear film); - an application of an anisotropic bandpass filter, step 210 of Figure 12, in a direction perpendicular to the direction of the reflected lines. This direction is vertical along the pixel columns of the image in the case of a horizontal line test pattern or a vertical line test pattern with the image rotated 90° to obtain clear lines oriented in a horizontal direction. The filter is configured to maintain sharp transitions between gray levels and to suppress or attenuate low spatial frequency and higher spatial frequency modulations in the perpendicular direction. The image output from the filter is shown in Figure 5A. This filter is particularly useful for eliminating vignetting and lighting uniformity defects. This transformation accentuates the eyelid lines 53, the clear lines 54 of the test pattern, and preserves the image of the frame 55.

[0077] Next, still in the case of light lines oriented in a horizontal direction, the process involves analyzing image 220 by pixel columns according to Figure 12, which searches for vertical light segments. The resulting image then contains lines 56, 57, 58, 59 as shown in Figure 5B. Once this analysis is complete, the light segments are qualified by their size, steps 230, 235. This makes it possible to eliminate segments that are too large or too short and that clearly do not correspond to line segments of the pattern, for example, segments forming part of the eyelid contour. At the end of this step, Figure 5C shows the image where the column segments constituting the isolated line 61, the lines of the pattern image 62, the background 64, and the frame 63 remain. It should be noted that the eyelashes cause significant fragmentation of the lines 65 at the top of the image.In the case of a vertical line test pattern, the analysis and qualification of the segments is done by pixel lines.

[0078] Once the segmentation is complete, the processing method includes a marking / cataloging algorithm 240, 250, 260 of the light segments to obtain objects representative of light branches of lines in the pattern and to reject light objects that do not have the desired shape, which are then considered artifacts. This algorithm first involves connecting contiguous column segments to reconstruct horizontal branches. The result of this marking / cataloging is shown in Figure 5D, in which each line found is assigned a color, here represented in grayscale. This cataloging makes it possible to create complete lines 70 or isolated branches 71, 72.

[0079] A next step is a connection 280 of the branches of light lines of the same level (for example of similar width and altitude) in the image and then a re Polynomial regression 285 uses a polynomial of order higher than two to calculate an RMS curve in the shape of the line edges. This step is shown in Figure 5E. In this figure, we can see, in particular, the connections between the lower RMS curves 74 and the upper RMS curves 74' of branches 73a, 73b of the fragmented lines at the level of the image of the frame surrounding the camera lens and branches 73c, 73d of the lower line. Enlarging Figure 6A allows us to better distinguish the RMS curves 74, 74' between branches 73c, 73d at the bottom of the image. Next, a detection of offset points 500 is performed at locations where the line edges contain measurement points that deviate from the shape given by the polynomial.

[0080] Unlike a simple method of searching for proven film breaks, in the context of the present invention we search for fluctuations in film thickness which result in micro-movements in the film.

[0081] The criterion taken into account for detection is here only a threshold criterion (for example a threshold of one pixel) to filter noise in the image, the totality of deviations between points and the polynomial greater than this threshold being taken into account.

[0082] This is for example shown in figure 6B in the area 76 where the edge of line 77b of line 77a does not reach the curve 74'.

[0083] As seen above, the method can be based on processing dark lines. Grouping the transition pairs (rising and falling in the case of light lines) allows for a consistency check on the width of the resulting segment and for rejecting segments that are too wide or too narrow to be part of the test pattern image. Once the branches have been determined, polynomial regression is performed on each side of the branch: one polynomial for rising transitions, one polynomial for falling transitions. The method of the invention therefore makes it equally possible to search for dark segments and dark lines and arrive at the same polynomial regressions and the same final result.

[0084] The result of the measurements is a map of micro-movements in the tear film represented in Figure 7, view of a patient's eye 6 seconds after blinking with magnification, for which the map of areas of reduced or zero film thickness 780 appears positioned on lines 51 in the initial color image of the eye reproduced here in greyscale.

[0085] Micro-movements correspond to evolving local deformations or sagging of the film, for example, in the form of depressions that can lead to film rupture, resulting in line deformations due to local changes in the diopter's curvature. The evolution of these deformations when the eye is observed under magnification appears as micro-movements or undulations.

[0086] As seen above, the images are captured approximately every 0.3 seconds. One The origin of time is defined as a blink of the eye, and repeating the measurement for each image over a period of time allows the construction of a map of the defects of the ocular film as a function of time.

[0087] One problem to consider is that the patient's gaze may change direction during the image acquisition period.

[0088] Since the camera observes the reflections of the pattern on the cornea, which behaves, to a first approximation, like a spherical diopter, the position of the pattern image remains virtually invariant in the image delivered by the camera, whereas the position of the iris changes if the patient turns their eyes. Therefore, a given point in the pattern image is not linked to a fixed point on the cornea, but rather to a point dependent on the direction of gaze. This implies that the measurement must be referenced to the position of the observed eye and not to the pattern image.

[0089] To do this, it is necessary to follow the position of the eye in each image. It was preferred to follow the outer contour of the iris of the eye because there is a significant contrast with the bulbar conjunctiva, which is light in color and on which there is no reflection of the target, whereas the pupil is more difficult to follow because of the reflection of the target which complicates the analysis of the image.

[0090] The following method can be implemented within the scope of this application or independently for other eye measurements. This method is also independent of the orientation of the sight lines.

[0091] Figures 8, 9A, 9B and 9C correspond to image processing on one eye of a patient looking at the camera and Figures 10, 11A, 11B and 11C correspond to image processing on one eye of a patient whose gaze is away from the camera.

[0092] According to figure 8, the eye 80 looks straight ahead, the image of the pattern 83 is centered with respect to the iris 82 itself centered with respect to the eyelid 81.

[0093] The image processing method for determining the iris position is schematically illustrated in Figure 13. It involves a first image transformation by applying a horizontally applied anisotropic bandpass filter 400 to detect light transitions along a horizontal axis. This operation aims to distinguish between downward transitions (light to dark) and upward transitions (dark to light). For clarity, the light-to-dark transitions (downward transition) are represented by the dark crescent 84 in the grayscale representation of Figure 9A, and the dark-to-light transitions (upward transition) are represented by the light crescent 85 in Figure 9A.Parts of the image without significant transitions become medium grey, like the crescent 86 for example, and the outline of the iris is materialized by a portion of ring 87 which is found on the left side next to a light to dark transition and on the other side of the eye next to a dark to light transition.

[0094] Returning to Figure 13, a second operation consists of segmenting the image 410 to search for the ascending and descending transition pairs, 84, 85 in Figure 9A for example, which form boundaries of the luminous areas in the image, particularly around the bulbar conjunctiva. These transition pairs, materialized by the boundaries 88, 89 and 90, 91 in Figure 9B, frame areas 92 that potentially define the bulbar conjunctiva.

[0095] From this transformation, the process, as shown in Figure 13, involves filtering the image 420, which removes the central area containing the pattern and the upper and lower areas of the image. On the remaining parts, an RMS circle is calculated around the iris, based on the right extremities of the segments on the left of the image and the left extremities of the segments on the right of the image 430. For this calculation, points too far from the RMS circle, which correspond to imperfections caused by the eyelashes or the eyelid, are rejected in step 440. For the remaining points, a new RMS circle is calculated to follow the contour of the iris; this circle 93 is shown in Figure 9C on the original image of the eye.

[0096] Figure 10 shows an eye 80' looking obliquely, with its iris 82' offset from the pattern 83'. For this eye position, the transitions 84', 85' around dark areas 86', 87' corresponding to homogeneous colors are shifted laterally in Figure 11A, whereas in Figure 11B, the arcs of circles 89' and 90' corresponding to the edge of the iris remain detectable. Applying the tracking method also leads to recreating the RMS circle 93', which is then repositioned on the original image as shown in Figure 11C. The detected deformation areas are then relocated according to step 460 based on the position of the circle defining the contour of the iris. This allows the tear film deformations to be anchored to the contour of the eye rather than to the image.

[0097] This sequence is performed for each image preferably after the analysis of the line pattern described above.

[0098] As mentioned above, this process is applied here to the repositioning of film deformations, but it can also be used for other types of detection and methods using eye position tracking.

[0099] According to one aspect of the application, the device may include a manual trigger that arms the device, with the image capture sequence being initiated upon the occurrence of an event such as a series of two blinks by the patient. To this end, the system includes a blink recognition method that allows the measurement sequence to start automatically. Similarly, the system can automatically stop the measurement sequence upon detection of a subsequent blink or stop the sequence automatically after a delay, for example, 15 seconds.

[0100] The shooting sequence can consist of 30 to 50 images, for example, and in the case of a 15-second shooting sequence with shots taken every 0.3 seconds, the sequence comprises 45 images. Image analysis can be performed after the shooting sequence, and due to the chosen solution of working with a pattern made of lines, the processing time remains reduced, for example, to 15 seconds with a standard computer.

[0101] According to Figure 14, the method comprises, from a time origin tO constituted by a blink of the eyelid, a succession of image captures 200 on a sequence which will last about fifteen seconds and taking images every 0.1 to 0.5 seconds and preferably every 0.3 seconds to have a good compromise between the detection of variations in the ocular film and the amount of data to be processed.

[0102] The sequence of image captures ends with the first arrival of one of the events: end of a time delay, for example 15 seconds which gives 45 images with one image every 0.3 seconds or detection of a blink following 570.

[0103] Between image acquisitions or on delay, the process includes a succession of detections of micro-movement zones in the images 510 and calculations and storage of position, surface and number of micro-movement zones 520 of the tear film in each image by means of image processing and analysis means according for example to the method of figure 12 and in particular polynomial regression which will allow to determine edges of lines estimated by means of a polynomial regression polynomial.

[0104] The method then includes calculating 530 and storing 540 a measurement of the amplitude of the micro-movement zones as a function of time. This measurement provides an overview of the film thickness reductions over the entire extent of the visualized lines.

[0105] To realign the positions of the lines between the images, the process will include tracking the eye of the patient shown in Figure 13.

[0106] In a subsequent step according to Figure 15, the process will make it possible to determine a population of points representative of the micro-movement zones observed on the image of the lines.

[0107] This is done by a calculation 610, along the lines, of the absolute value of the distance to the polynomial along the axis perpendicular to the general direction of the lines of the pixels PI to Pn of the line edges of the image which are deviated from the polynomial by a distance dP in pixels greater than a threshold 620. These representative points PI to Pn and the distances dPl to dPn are then stored. In the case of horizontal lines, the distance is vertical and in the case of vertical lines, the distance is horizontal.

[0108] To determine an extent of areas where the film is deformed, the method comprises for each image, a calculation 640 for each pixel PI to Pn of the equivalent surface of the deformation at the line edge Sp = dP x pixel width x pixel height.

[0109] Then a calculation 650 of the sum S Sp of the equivalent surfaces SP1 to SPn between the image points and their polynomial over the whole image and of a normalized sum NX Sp of said distances by means of the division of the sum X Sp by the total length LT of the lines found on the image.

[0110] This number represents an overall extent of deformations in the line edge areas.

[0111] To obtain a reproducible value between examinations, the method includes the calculation 660 of an overall score consisting of the sum A of the normalized sums N SI S p on a series of images from the origin of time tO up to a given instant t.

[0112] According to the examples of the curves in figures 16 and 17, it can be seen that a sum over a period of approximately 6 seconds, i.e. 18 images when the images are taken every 0.3 seconds, makes it possible to distinguish the differences between patients.

[0113] The method may further include the generation 550 of a map of the locations of micro-movements frame by frame which makes it possible to distinguish the more marked instability areas of the eye film and to observe the variation of the deformations of the film over time.

[0114] It is also possible to calculate and store the time of appearance of micro-movement points of the tear film and / or the kinetics of appearance of micro-movement points of the tear film 560 which can be useful for comparing results during a treatment.

[0115] In addition, all or part of the calculated data can be stored in order to carry out patient follow-up and comparison of said data over several examinations.

[0116] Once the measurement is complete, the practitioner has access to, on the one hand, a spatial and temporal map of the micromovements of the tear film within the corneal surface and, on the other hand, a time curve tracing the evolution of these tear film micromovements over time. The amplitude at each point of the curve reveals the level of stability at a given instant. The slope of this time curve reveals the kinetics of tear film rupture. This allows for a more precise interpretation of the examination performed.

[0117] Figure 16 represents a graph 700 with the normalized NSS p sum filtered with a moving average over three images on the ordinate 701 and the images for five patients Cl to C5 on the abscissa 702.

[0118] Patients C1 and C2 exhibit few micromovements, i.e., low instability due to their ocular film over time; patient C3 exhibits an in average stability but did not keep the eye open during the complete sequence whereas patients C4 and C5 exhibit high instability representative of dry eye.

[0119] Figure 17 represents a graph 710 with the cumulative value A between successive images on the ordinate 711 and the images on the abscissa 702. This graph amplifies the visibility of the growth of micromovement zones for patients C4 and C5 with dry eye, while patients C1 and C2 show very limited progression, with patient C3 showing moderate progression up to the blink stage in image 28.

[0120] The two graphs represent time periods 703 and 713 of approximately two seconds centered around the 18th image, which in this case is 6 seconds after blinking. The curves show that this examination time of approximately 6 seconds is sufficient to normalize the results and distinguish patients without dry eye problems from those with them, without risking an examination time that could cause excessive blinking.

[0121] The invention is not limited to the examples described above, which are given only by way of example, but encompasses all variations, such as different distributions or progressions of line height, that a person skilled in the art might consider within the scope of the protection sought. In particular, as mentioned above, the lines of the pattern, which are horizontal parallel lines according to the example shown, can be replaced by vertical parallel lines. Rotating the image allows, for example, the application of image processing means for detecting line distortions to this configuration without changing its direction.

Claims

Claims

1. Method for measuring the stability of a patient's tear film by means of a device comprising a backlit translucent plate (10a) provided with a target (10) positioned in front of at least one eye (101) of a patient (100), at least one digital photographic camera (22, 23) connected to a computing system (30) provided with image processing and analysis means, a lens of the camera pointing towards the patient's eye in order to photograph a reflection of the pattern of the target on the patient's eye, characterized in that, the target being provided with a pattern consisting of a succession of alternating light and dark lines (12, 13) reflected on the patient's eye and the image processing and analysis means being configured to detect deformations (76) of said light or dark lines of the pattern of the target reflected on the patient's eye and identify,by a comparison of the position of image points of the edge of the lines with respect to an estimated edge of the lines (74, 74'), the micro-movements of the tear film revealed by these deformations, the method comprises, from a time origin (tO) constituted by a blink of the eyelid: - a succession of image captures (200), - a succession of detections of micro-movement zones in the images (510) and calculations and storage of data on positions, surface and number of micro-movement zones (520) of the tear film in each image by means of the image processing and analysis means and - the calculation (530) and storage (540), from the succession of calculations of positions, surface and number of micro-movement zones of the tear film, of a measurement of the amplitude of the micro-movement zones as a function of time.,

2. A method for measuring the stability of the tear film according to claim 1, comprising taking an image (200) every 0.1 to 0.5 seconds and preferably every 0.3 seconds.

3. Method for measuring the stability of the tear film according to claim 1 or 2, for which the succession of image captures ends with the first occurrence of one of the events: end of a time delay or detection of a following eyelid blink (570).

4. A method of measuring tear film stability according to claim 1, 2 or 3 comprising tracking the patient's eye or eyes (400, 410, 420, 430, 440, 460) using an iris tracking process to reposition the detected and stored tear film deformation zones relative to the eye being analyzed.

5. A method of measuring tear film stability according to any preceding claim wherein the estimated line edges are calculated by polynomial regression (285).

6. Method for measuring the stability of the tear film according to claim 5 comprising the determination of a population of points representative of the micro-movement zones observed on the image of the lines by calculation (610), along the lines, of the absolute value of the distance to the polynomial along the axis perpendicular to the general direction of the lines of the pixels PI to Pn of the edges of lines of the image which are separated from the polynomial by a distance dP in pixels greater than a threshold (620) and storage (620) for the representative points PI to Pn of the distances dPl to dPn.

7. Method for measuring the stability of the tear film according to claim 6 comprising for each image, on said population of representative points, a calculation for each pixel PI to Pn of the equivalent surface Sp = dP x pixel width x pixel height (640) and a calculation (650) of the sum X Sp of the equivalent surfaces SP1 to SPn of the image points to their polynomial over the entire image and of a normalized sum NX Sp of said distances by means of the division of the sum XS p by the total length LT of the lines found on the image.

8. Method for measuring the stability of the tear film according to claim 7 comprising the calculation (660) of an overall score consisting of the sum A of the normalized sums NX 5p on a series of images from the origin of times t0 up to a given instant t.

9. A method of measuring tear film stability according to any preceding claim comprising generating (550) a map of the locations of micro-movements image by image.

10. Method for measuring the stability of the tear film according to any one of the preceding claims comprising the calculation and storage (560) of the time of appearance of the micro-movement points of the tear film and / or the kinetics of appearance of micro-movement points of the tear film.

11. A method for measuring tear film stability according to one of any of the preceding claims comprising the storage in a database of all or part of the calculated data so as to carry out monitoring of the patient and a comparison of said data over several examinations.

12. Computer program comprising instructions for implementing the method according to any one of the preceding claims when this program is executed by a processor.

13. A non-transitory recording medium readable by a computer on which is recorded a program for implementing the method according to any one of claims 1 to 11 when this program is executed by a processor.

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