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    • 专利摘要:
    Method and computer program to analyze ocular diffusion. The method, from one or more images captured by an ophthalmoscopic double-pass system through the projection of a point beam of light in the retina and the subsequent capture of the light reflected in the retina, performs an analysis, by a device of computation, of said one or more images captured analyzing the content relative to the ocular diffusion thereof. The relative content of the ocular diffusion is determined by the implementation of a computation algorithm that executes a function in the frequency domain with which quantification parameters of the ocular diffusion are calculated from one or more frequency values corresponding to some frequencies spatially within a range equal to or below approximately 12 cycles/degree. (Machine-translation by Google Translate, not legally binding)
    公开号:ES2629169A1
    申请号:ES201630135
    申请日:2016-02-05
    公开日:2017-08-07
    发明作者:Jaume Pujol Ramo；Meritxell Vilaseca Ricart；Juan Antonio MARTINEZ RODA；Carlos Enrique GARCIA GUERRA
    申请人:Universitat Politecnica de Catalunya UPC；
    IPC主号:
    专利说明:

    DESCRIPTION

    Computer method and program to analyze eye diffusion
    Technical sector
    The present invention relates generally to methods for evaluation of ocular quality. In particular, the present invention concerns a method, and a computer program, for analyzing ocular diffusion using retinal images (or retinal images) of a patient's eye captured by a double-pass ophthalmoscopic system.
    Low spatial frequencies means a range of frequencies below 10-12 cycles / degree. 10
    Prior art
    Knowing the ocular optical quality is a topic of great importance in the field of visual optics due to its direct relationship with the vision of people, which definitely has an impact on the standard of living. As a whole, the visual process includes related aspects both at the optical level and at the neuronal level, while the ocular optical quality 15 is only influenced by the first stage, which is the formation of the retinal image after the light has passed through the entire half eye
    On the other hand, double-pass ophthalmoscopic systems provide a good objective evaluation of ocular optical quality because they take into account the actual degradation of the retinal image. These types of systems are based on the recording of images of an object after reflection on the retina and double-pass through the ocular means. A basic scheme of a double-pass system is shown in Fig. 1. A collimated laser beam of a certain wavelength passes through the entrance pupil EP and a Badal system, which consists of two lenses L3, L4 and two mirrors M2, M3 and allows the spherical ametropia of the patient's eye to be compensated. Then, the optics of the eye focus the beam 25 on the retina, where it is reflected, passes again through the ocular means, the Badal system and the ExP pupil exit. Finally, the L5 lens focuses the beam on a CCD1 camera. To minimize the patient's eye movements and alignment with the control system, the double-pass ophthalmoscopic system also includes an FT fixation stimulus and a second CCD2 camera that allows the patient's pupil to be visualized. 30
    A device and a method for optically measuring ocular transmission and diffusion of the frontal segment of the eye are known from US-B2-8398237. In this patent
    US, as in the present invention, the Fourier transform module, or Modulation Transfer function (MTF), is used to calculate said ocular diffusion, however, unlike the present invention, in this US patent said MTF function uses all corresponding frequencies with a ring of a certain radius and not only those frequencies corresponding to the first frequency components. 5
    An apparatus for observing the retina and a method for correcting the aberrations of the eye by means of an optical compensation device are known from US-B2-7270415. In this US patent, the MTF function is also used to perform said correction of the aberrations, however, unlike the method proposed in the present invention, also only the frequencies corresponding to the first 10 frequency components of the MTF are not used.
    A method for designing intraocular lenses and correcting variations of different parameters is known from US-B2-8211172. The mentioned method can in this case model the visual performance of an intraocular lens using the corresponding frequencies with the first frequency components of the MTF, however, this method does not evaluate the ocular diffusion index, but calculates different parameters such as: the axial ocular length, the sphericity of the cornea, the radius or the length of the anterior ocular chamber, to design different intraocular lenses. Likewise, the system for obtaining the image (s) of the retina used in this US patent, unlike the present invention, is not a double-pass ophthalmoscopic system. twenty
    On the other hand, other methods are also known to evaluate intraocular diffusion from an image of the retina, for example by patent ES2315171B1 of the inventors themselves of this patent application. However, in none of these methods is it planned to use only the first frequency components to evaluate the said diffusion. 25
    There is, therefore, the need to offer a method capable of evaluating ocular diffusion from images of the retina, or from an area of the retina, captured by a double-pass ophthalmoscopic system, from the analysis of the image in the frequency space and taking into account the first frequency components.
    Explanation of the invention 30
    To that end, embodiments of the present invention provide according to a first aspect a method for analyzing ocular diffusion, where from one or more
    images captured by a double-pass ophthalmoscopic system by projecting a spot beam of light on the retina of an eye of a patient and the subsequent capture of the light reflected on it, an analysis is performed, by a computing device which includes one or more processors, of said one or more images captured analyzing the content related to the ocular diffusion thereof. 5
    Characteristically, in the proposed method the aforementioned relative content of the ocular diffusion is determined by the implementation of a computation algorithm that executes a function in the frequency domain with which quantification parameters of the ocular diffusion are calculated from one or more frequency values corresponding to spatial frequencies in a range equal to or below 10 approximately 12 cycles / degree.
    In a preferred embodiment, an optimal low spatial frequency value used by said algorithm is approximately 9.09 cycles / degree.
    Preferably, said function in the frequency domain is the Fourier transform or the Modulation Transfer (MTF) function of the captured image or images.
    In an exemplary embodiment, the method comprises calculating the parameters of quantification of the ocular diffusion by making a comparison of an initial value of the slope of the Fourier transform module taking into account different areas, central and preferably of square perimeter, with a certain content of 20 pixels per side of the image or images captured. For example, according to this exemplary embodiment, said calculation can be performed according to the following expression: _ = × �10 1 - 2 1−1�
    where K is a constant and corresponds to a value of the lowest spatial frequency, other than zero, obtained from the calculation of the Fourier transform module for a square central area of pixels per side. 25
    In another exemplary embodiment, the quantification parameters of the ocular diffusion are calculated by making a comparison of the MTF values in said low spatial frequency range taking into account the same area, central and also preferably of square perimeter, of a given pixel content per side of the image or images captured by comparing values of said MTF 30
    For different frequencies. For example, according to this exemplary embodiment, said calculation can be made according to the following expression: = 1 - 2 × 1 - 2 3 - 4
    where: K1 and K2 are two constants; corresponds to a value of the Fourier transform module of said area, central and square, of pixels per side of the image or images captured at a spatial frequency ; 1 e 3 correspond to the value of 5 the lowest frequencies that can be obtained with the calculation of the MTF function, with said area, central and square, of pixels per side; 2 and 4 correspond to a reference frequency value used to calculate the slope of the curve of said MTF.
    In another exemplary embodiment, said calculation of the ocular diffusion quantification parameters comprises adjusting the decreasing exponential type MTF function 10 in said low spatial frequency range. For example, the mentioned function of decreasing exponential type can be performed according to the following expression: = � - + �
    where: a, b, and c correspond to adjustment parameters, said parameter being related to the optical quality of the eye, b related to ocular diffusion, and c with a measure of the quality of the adjustment. fifteen
    In yet another exemplary embodiment, the calculation of the parameters of quantification of the ocular diffusion comprises comparing the MTF values in said low spatial frequency range with a curve obtained from the MTF adjustment for spatial frequencies of a value greater than said value. range of spatial frequencies. For example, this calculation can be performed according to the following expression: 20 = 1 � [ ] [ ] = 1
    where: [ ] corresponds to the MTF function obtained after the execution of the Fourier transform and [ ] corresponds to the MTF function obtained after having performed a peak correction, or normalization, in that function.
    Other embodiments of the invention described herein also include computer programs for performing the steps and operations of carrying out the method proposed in the first aspect. More particularly, a computer program is an embodiment that has a computer-readable medium that includes code instructions encoded therein when executed on at least one processor in a computer.
    computer system produce the processor to perform the operations indicated herein as embodiments of the invention.
    Brief description of the drawings
    The foregoing and other advantages and features will be more fully understood from the following detailed description of some embodiments with reference to the 5 attached drawings, which should be taken by way of illustration and not limitation, in which:
    Fig. 1 shows an example of a double-pass ophthalmoscopic system used by the present invention to capture one or more images of the retina.
    Fig. 2 is a flow chart that schematically describes the different steps performed by the proposed method to analyze ocular diffusion. 10
    Detailed description of the invention and some examples of realization
    According to the present invention, in an exemplary embodiment, once the image or images of a retina plane of an eye of a patient (not illustrated) have been captured by a double-pass ophthalmoscopic system, as illustrated in Fig. 1, projecting a spot beam of light on said retina and capturing the subsequent light reflected on it, an analysis is performed, by a computing device (not illustrated) such as a PC, a laptop, or any device of computing that includes one or more processors and at least one memory, of said one or more images captured analyzing the content related to the ocular diffusion of the same / s by means of the implementation of a computing algorithm that executes a function in the domain 20 frequency (for example the Fourier transform or the MTF function) with which quantification parameters of ocular diffusion are calculated from one or more frequency values corr sponges at spatial frequencies in the range of low spatial frequencies. Fig. 2 illustrates this described process.
    Preferably, according to the present invention, the low spatial frequency may be, for example, a spatial frequency of about 10 cycles / degree (equal or below). Although preferably the proposed method operates at low spatial frequencies in said range equal to or below 10 cycles / degree, other frequency values, for example about 11 cycles / degree or even 12 cycles / degree could also be used without leaving of the scope of protection of the present invention. 30
    An optimal low spatial frequency value used by the aforementioned algorithm is approximately 9.09 cycles / degree.
    In a first embodiment, for the calculation of a frequency diffusion index (FSI), said algorithm compares an initial value of the slope of the Fourier transform module taking into account different areas, central and preferably perimeter. square, with a certain pixel content per side, of the image or images captured. The mathematical function for this purpose can be defined according to the following equation:
    _ = × �10 1 - 2 1−1� (1)
    where: 10
    K is a constant; Y
    corresponds to a value of the lowest spatial frequency, other than zero, obtained from the calculation of the Fourier transform module for a square central area of pixels per side.
    In a second embodiment, for the calculation of an SCT parameter (of the word 'scattering' in English), the algorithm compares the MTF values in said low spatial frequency range taking into account the same area, central and preferably also of square perimeter, of a certain pixel content per side, of the image or images captured by making a comparison of values of said MTF for different frequencies. Therefore, in this second embodiment, the algorithm instead of comparing the Fourier transform module of different areas of interest calculates the value of the MTF function for the same area. The mathematical function for this purpose can be defined according to the following equation: = 1 - 2 × 1 - 2 3 - 4 (2)
    where:
    K1 and K2 are two constants; 25
    corresponds to a value of the Fourier transform module of said area, central and square, of pixels per side of the image or images captured at a spatial frequency ;
    1 e 3 correspond to the value of the lowest frequencies that can be obtained with the calculation of the MTF function, with said area, central and square, of pixels per side, and 30
    2 and 4 correspond to a reference frequency value used to calculate the slope of the curve of said MTF.
    In a third example of embodiment, the algorithm for quantifying ocular diffusion in said low spatial frequency range is based on analyzing the shape of the MTF function curve, that is, the algorithm makes an adjustment of the initial values of the 5 MTF function in a decreasing exponential function. In this case, to obtain a relatively simple mathematical expression, the algorithm performs some transformations in the MTF function. First, the X and Y axes are transposed. Thus, after normalizing the MTF function, the values of the X axis range from 0 to 1, representing spatial frequencies on the Y axis. Finally, the mathematical expression given by equation (3) is incorporated into the transformed function.
    = � - + � (3)
    where:
    a, b, and c correspond to adjustment parameters, said parameter being related to the optical quality of the eye, b related to ocular diffusion, and c with a measure of the quality of the adjustment.
    In a fourth embodiment, or calculation of an aberration-free diffusion index (AFSI), which is defined as the average value of the relationship between the MTF before and after a peak correction, or normalization. For this, the algorithm compares the MTF values in said low spatial frequency range with a curve obtained from the MTF adjustment for spatial frequencies of a value greater than said spatial frequency range. The mathematical function for this purpose can be defined according to the following equation:
    = 1 ∑ [ ] [ ] = 1 (4)
    where: 25
    N represents a set of consecutive values on which n varies, in a case of discrete frequencies;
    [ ] corresponds to the MTF function obtained after the execution of the Fourier transform; Y
      [ ] corresponds to the MTF function obtained after having performed a peak correction in that function.
    Preferably, according to the present invention, inlet and outlet diameters of the pupils of 2 mm and 4 mm respectively are used to capture the image or images of said plane of the retina. Also, the CCD cameras used include a cooling system to minimize noise and improve sensitivity. Its dynamic range is 14 bits, the focal length of its target 50 mm and the pixel size 8 µm. In addition, an exposure time between capture and image capture of 200 ms is taken.
    Image or image captures are preferably taken after an eye blink to avoid the effect of tear film on double-pass images. Once the images are captured, with the naked eye, different diffuser filters are placed in front of the patient's eyes to simulate different levels of ocular diffusion. 10 Consecutively different measurements of each eye are taken with each filter.
    Similarly, in an exemplary embodiment, blurs of +2.50 D to -2.50 D (in steps of 0.50 D) can be induced by using said Badal system to study the influence of aberrations.
    One skilled in the art could make changes and modifications in the examples of embodiment described without departing from the scope of the invention as defined in the appended claims.
    权利要求:
    Claims (14)
    [1]
    1. A method to analyze ocular diffusion, where from one or more images captured by a double-pass ophthalmoscopic system by projecting a spot beam of light into the retina of an eye of a patient and subsequent capture of the light reflected in the retina, an analysis is performed, by a computing device, of said one or more 5 images captured analyzing the content related to the ocular diffusion of the same / s, the method being characterized in that said relative content of The ocular diffusion is determined by the implementation of a computing algorithm that executes a function in the frequency domain with which quantification parameters of the ocular diffusion are calculated from one or more frequency values corresponding to about 10 spatial frequencies comprised in a range equal to or below about 12 cycles / degree.

    [2]
    2. The method according to claim 1, characterized in that said function in the frequency domain is the Fourier transform of the image or the Transfer function of the Modulation, MTF, of the image.
    [3]
    3. The method according to claim 2, characterized in that it comprises calculating the quantification parameters of the ocular diffusion by comparing an initial value of the slope of the Fourier transform module taking into account different central areas with a certain content of pixels per side, of image 20 or captured images.
    [4]
    4. The method according to claim 3, wherein said central areas are square perimeter.
    [5]
    5. The method according to claim 4, characterized in that it comprises calculating the quantification parameters of the ocular diffusion according to the following expression: _ = × �10 1 - 2 1−1�
    where:
    K is a constant; Y
    corresponds to a value of the lowest spatial frequency, other than zero, obtained from the calculation of the Fourier transform module for a square central area of pixels per side. 30
    [6]
    6. The method according to claim 2, characterized in that said analysis comprises comparing the MTF values in said spatial frequency range taking into consideration the same central area of a certain pixel content per side of the captured image or images making a comparison of values of said MTF for different frequencies. 5
    [7]
    7. The method according to claim 6, wherein said central area is square perimeter.
    [8]
    8. The method according to claim 7, characterized in that it comprises calculating the parameters of quantification of ocular diffusion according to the following expression: = 1 - 2 × 1 - 2 3 - 4
    where: 10
    K1 and K2 are two constants;
    corresponds to a value of the Fourier transform module of said area, central and square, of pixels per side of the image or images captured at a spatial frequency ;
    1 e 3 correspond to the value of the lowest frequencies that can be obtained with the calculation of the MTF function, with said area, central and square, of pixels per side; Y
      2 and 4 correspond to a reference frequency value used to calculate the slope of the curve of said MTF.
    [9]
    9. The method of claim 2, characterized in that it comprises calculating the parameters of quantification of the ocular diffusion by performing an adjustment of the MTF function 20 of decreasing exponential type in said spatial frequency range.
    [10]
    10. The method according to claim 9, characterized in that the decreasing exponential type function is performed according to the following expression: = � - + �
    where:
    a, b, and c correspond to adjustment parameters, said parameter being related to the optical quality of the eye, b related to ocular diffusion, and c with a measure of the quality of the adjustment.
    [11]
    11. The method according to claim 2, characterized in that it comprises calculating the parameters of quantification of ocular diffusion by performing a
    comparison of the MTF values in said spatial frequency range with a curve obtained from the MTF adjustment for spatial frequencies of a value greater than said spatial frequency range.
    [12]
    12. The method according to claim 11, characterized in that said calculation is performed according to the following expression: 5 = 1 � [ ] [ ] = 1
    where:
    [ ] corresponds to the MTF function obtained after the execution of the Fourier transform and [ ] corresponds to the MTF function obtained after having performed a peak correction in that function.
     10
    [13]
    13. Method according to any one of the preceding claims, characterized in that a low spatial frequency value used by the algorithm is 9.09 cycles / degree.

    [14]
    14. Computer program that includes code instructions that when executed by one or more processors of a computer system implement a method according to any one of claims 1 to 12.

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    同族专利:
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    WO2017134324A1|2017-08-10|
    ES2629169B1|2018-05-11|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    WO2001082791A1|2000-04-28|2001-11-08|University Of Rochester|Improving vision and retinal imaging|
    US20030086063A1|2000-10-20|2003-05-08|Williams David R.|Rapid, automatic measurement of the eye's wave aberration|
    US20120033182A1|2002-12-06|2012-02-09|Amo Manufacturing Usa, Llc|Compound modulation transfer function for laser surgery and other optical applications|
    US20110085133A1|2006-05-17|2011-04-14|Xin Hong|Correction of higher order aberrations in intraocular lenses|
    EP2147633A1|2007-05-04|2010-01-27|Universitat Politecnica de Catalunya|System and method for measuring light diffusion in the eyeball or eye region, by recording and processing retinal images|
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    PCT/ES2017/070058| WO2017134324A1|2016-02-05|2017-02-03|Method and computer program for analysing ocular diffusion|
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