JP2020182680A - Visual perception simulation method and visual perception simulation program - Google Patents

Abstract

To provide a visual perception simulation method and a visual perception simulation program that effectively motivate a patient to undergo treatment for the patient's eye.SOLUTION: A visual perception simulation method to be implemented by an ophthalmologic system includes at least: an estimation information acquisition step of a computer acquiring estimation information indicating a visual perception state of a patient's eye at a certain point of time; and an output step of a PC outputting a simulation image that indicates visual performance of the patient's eye at the certain point of time and corresponds to the estimation information in order to present the simulation image to the patient's eye. As a result of the presentation of the simulation image to the patient's eye, the patient is effectively motivated to undergo treatment for the eye.SELECTED DRAWING: Figure 3

Description

The present disclosure relates to a visual simulation method and a visual simulation program.

As eye diseases, diseases that cause visual field disorders such as glaucoma are known. The progress of the disease can be inspected by a perimeter and an inspection device such as an OCT (optical coherence tomography).

In recent years, methods for estimating the field of view of patients in the future have been proposed. For example, in the method disclosed in Patent Document 1, the field of view of a patient in the future is estimated based on the test results of a plurality of perimeters.

Japanese Unexamined Patent Publication No. 2014-166250

Visual field impairment often progresses gradually without the patient's awareness. Also, visual field impairment is irreversible. Therefore, in order to prevent the progression of disability and prevent blindness, it is important that the patient is actively involved in the treatment, and that the patient goes to the hospital and takes appropriate medicine.

However, patients are less likely to notice symptoms, especially in the early stages of visual field impairment. In addition, since the visual field disorder progresses slowly and is irreversible, it is difficult for the patient to realize the therapeutic effect. Therefore, the present inventor has focused on and studied a method for effectively motivating a patient for treatment.

The present disclosure has been made in view of the above circumstances, and it is a technical subject to effectively motivate patients for eye treatment.

The visual simulation method according to the first aspect of the present disclosure shows an estimation information acquisition step in which a computer acquires estimation information indicating a visual state in the patient's eye at a certain time point, and how it looks in the patient's eye at the time point. It is a simulation image, and includes an output step output by the computer to present the simulation image corresponding to the estimated information to the patient's eye.

The visual simulation program according to the second aspect of the present disclosure causes the computer to execute the visual simulation method according to the first aspect.

According to the present disclosure, the patient can be effectively motivated for the treatment of the eye.

It is a figure which showed the outline of the ophthalmic system which concerns on 1st Embodiment. It is a figure which showed the detailed structure of a patient terminal. It is a figure for demonstrating the flow of the visual simulation method in embodiment. It is a graph which showed the time-dependent change of MD value when the progress rate of a disorder is different from each other.

Hereinafter, the present disclosure will be described based on an embodiment with reference to the drawings.

FIG. 1 shows a schematic configuration of an ophthalmic system 1 according to the first embodiment. The ophthalmic system 1 is used to present to the patient's eye a simulated image showing how it looks in the patient's eye at a given point in time. The time point referred to here may be a time point other than the present, or may be a time point in the past and in the future. It may also be at some point in the past, present, and future. In the following description, the ophthalmic system 1 is used, as an example, to present a simulation image corresponding to a future time point.

The ophthalmic system 1 shown in FIG. 1 includes an eye examination device 10, a PC 20, and a patient terminal 30. The devices may be connected to each other via a network.

<Eye examination device>
The eye examination device 10 is used to examine the visual function of the patient's eye.

In the first embodiment, the retinal function is mainly examined as the visual function. The eye examination device 10 may be used to examine the retinal luminosity factor for each site. Such an eye examination device 10 may be, for example, a perimeter, an ERG (electroretinogram), or an FRG (functional retinography). The perimeter may be a static perimeter (eg, Humphrey perimeter, microperimeter, etc.) or a dynamic perimeter (eg, Goldman perimeter, etc.).

Further, in recent years, a method of estimating the visual state of a patient based on the structural features of the retina imaged by a fundus imaging device has attracted attention. Examples of the fundus imaging device that can be used for such a method include OCT, fundus camera, SLO, and the like. The fundus imaging device may be a device that images the fundus at the cellular level. As an example of a method for estimating the visual state of a patient based on the structural characteristics of the retina, the visual field of the patient is obtained from the layer thickness information (layer thickness distribution information) of the retina measured by an optical coherence tomography (OCT). A method for estimating is proposed in the following literature.
Sugiura, H. et al. (2018) Estimating Glaucomatous Visual Sensitivity from Retinal Thickness with Pattern-Based Regularization and Visualization, in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining --KDD '18. New York, New York , USA: ACM Press, pp. 783-792.

Hereinafter, unless otherwise specified, the eye examination device 10 will be described as a perimeter, and as an examination result by the eye examination device 10, information indicating the luminosity factor of the retina for each site can be obtained.

<Computer>
In the first embodiment, the PC 20 executes a visual simulation program. In the first embodiment, the PC 20 generates a simulation image and outputs it to a display device (in the first embodiment, a patient terminal). The simulation image is an image showing the appearance in the patient's eye at a certain point in time, and here, the future appearance is shown. In the first embodiment, the simulation image will be described as being generated by image processing by the PC 20.

In the first embodiment, the PC 20 includes a processor 21 (processing device). In the first embodiment, the processor 21 also serves as an image processor. The PC 20 may accept an operation input from an examiner or the like via a user interface (not shown) provided in the PC 20. For example, the PC 20 may accept information indicating a time point for simulating the appearance (for example, the age of the patient) via the user interface, and a simulation image at the received "time point" is generated by each process described later. May be done.

In the first embodiment, the visual simulation program may be stored in the non-volatile memory of the PC 20 (for example, the memory 22) accessible from the processor 21.

<Patient terminal>
In the first embodiment, the patient terminal 30 is used as a display device. That is, the patient terminal 30 presents the simulation image to the patient's eye. In the first embodiment, the patient terminal 30 can simultaneously present individual images to each of the left and right patient eyes. That is, different simulation images can be presented between the left and right eyes to be inspected.

The patient terminal 30 may be a wearable device, and as an example, it may be a head-mounted display as shown in FIGS. 1 and 2. For convenience of explanation, the patient terminal 30 will be described below assuming that the patient terminal 30 includes a screen 31 for allowing the patient to observe the image. In the first embodiment, the screen 31 is divided into two regions, left and right. The left half of the screen 31 (the left half when viewed from the patient) is used to present the image to the left eye, and the right half of the screen 31 (the right half when viewed from the patient) is the right eye. It is used to present an image to.

However, the present invention is not limited to this, and the patient terminal 30 may include a projector that projects an image directly onto the retina of the patient's eye. In this case, the projector may individually project an image to each of the left and right patient eyes. As a specific example, one projector may be provided for each of the left and right patient eyes. When the patient terminal 30 is a head-mounted display, the patient terminal 30 may be a portable computer such as a smartphone and a tablet attached to a headset, or may be a stand-alone device.

The patient terminal 30 may include a diopter correction unit. The diopter correction unit may have a correction lens 33 arranged between the screen 31 and the patient's eye. The diopter correction unit is used to correct the refraction error of the patient's eye. The diopter correction unit may include a mechanism for moving the position of the screen 31 or the correction lens in the front-rear direction.

<Operation explanation>
Next, the visual simulation method by the ophthalmic system 1 in the first embodiment will be described with reference to FIGS. 3 and 4.

<Inspection step>
In advance, the eye examination device 10 performs a plurality of examinations on the visual function of the patient's eye. It is desirable that each test be performed, for example, at intervals of several months. Further, for example, in order to estimate the state of visual function (visual state) of the patient's eye at a certain time point (here, a certain point in the future) by using the estimation processing method disclosed in Patent Document 1 described above. The number of inspections is preferably 3 or more.

In the first embodiment, the eye examination device 10 performs a plurality of examinations related to visual function on the left and right patient eyes in advance. As a result, data showing the distribution of luminosity factor in each of the left and right patient eyes is acquired in each examination.

The data showing the distribution of luminosity factor is transferred from the eye examination device 10 to the PC 20 and stored in the memory of the PC 20 (for example, the memory 22). In the first embodiment, the visual simulation program is executed by the PC 20 in this state.

<Estimated information acquisition step>
First, the PC 20 acquires the estimation information. Estimated information indicates the visual state of the patient's eye at a point in time (here, a future point in time). In the first embodiment, as shown in FIG. 3, estimated information in each of the left and right patient eyes is acquired. The estimated information may indicate the visual state at a predetermined time point (for example, 1 year, 3 years, 10 years, etc.), or the visual state at the desired time point of the examiner or the patient. It may indicate. The desired time point may be preset, for example, based on the operational input to the input interface. In addition, a plurality of estimated information indicating the visual state at a plurality of future time points may be acquired. Here, it means that the estimated information is placed in a state where it can be processed by the processor 21 of the PC 20. For example, the estimated information is acquired by storing the estimated information in a predetermined memory area accessible by the processor 21.

In the first embodiment, an estimation process (also referred to as “prognosis estimation”) based on past inspection results is executed by the processor 21 of the PC 20, and as a result, estimation information is acquired. In the estimation process, the future visual state in the patient's eye is estimated based on the results of multiple past tests.

For example, the processing content of Patent Document 1 can be applied to the estimation processing. In this case, for example, based on the data showing the retinal luminosity factor of each part of the patient's eye obtained in each of a plurality of past examinations, the data showing the retinal luminosity factor of each part in the future (including at any time point) is obtained. , Processor 21 may estimate by Bayesian estimation. Further, the estimation method is not necessarily limited to Bayesian estimation, and other estimation methods may be used.

In addition, the processor 21 refers to data indicating a visual state in the future (including at any time point) from the results of a plurality of past examinations in light of a learning model by machine learning (for example, data indicating retinal luminosity factor of each part). May be estimated. In this case, the learning model can be formed, for example, based on the results of multiple tests in each of the plurality of patient eyes. For each patient's eye, a learning model may be formed based on the test results accumulated over years to decades of follow-up.

<Image processing step>
In the first embodiment, the processor 21 performs image processing on the input image based on the estimated information, and as a result, a simulation image is generated. The simulation image is an image obtained by processing the input image by image processing and showing the appearance of the input image in the future with the patient's eye. A simulation image is generated by performing processing (in other words, processing that makes it difficult to see) on the input image so as to hide a portion having a poor visual state by the processor 21.

In the first embodiment, as shown in FIG. 3, a simulation image (L) for the left eye is generated based on the estimated information (L) for the left eye, and the estimated information (R) for the right eye is used. Based on this, a simulation image (R) for the right eye is generated.

In addition, simulation images corresponding to each of a plurality of time points in the future are generated based on the estimated information.

The input image may be, for example, an image representing the outside world, and may be, for example, an image showing a landscape as shown in FIG. It may also be an image of a person or an animal. The input image may be a still image or a moving image. If it is a moving image, it may be shot in real time. In this case, for example, the patient terminal 30 may be further provided with an external camera for capturing input images and moving images in real time. Further, there may or may not be parallax between the input image for the left eye and the input image for the right eye.

Each region in the input image and each region in the visual field corresponding to the estimated information (in other words, each region of the retina) can be associated with each other on a one-to-one basis. Utilizing this correspondence, the processor 21 performs processing (in other words, processing that makes it difficult to see) to hide a portion having a poor visual state with respect to the input image by image processing, and generates a simulation image.

In the first embodiment, for example, among the regions in the input image, the region having a worse degree of visual state (here, the region having a lower retinal luminosity factor) is made more difficult to see by the image processing. At this time, each area of the input image may be divided into three or more stages according to the degree of the visual state, or may be divided into two stages of a region having a relatively good degree of visual state and an area having a bad visual state. Good.

The image processing for generating the simulation image (processing that hides the part with poor visual condition) may be, for example, inpainting (repair processing), interpolation processing, or blurring. It may be a process or a fill process.

For example, in the in-painting and interpolation processing, the information of the deteriorated region is interpolated based on the information of the peripheral region, with the portion of the input image having a poor visual state as the deteriorated region. At this time, the deteriorated region may be formed by pixels having no information of the input image. However, the deteriorated region does not necessarily have to be formed only by pixels that do not have the information of the input image, and some pixels that retain the information of the input image may exist. The number of pixels that retain the information of the input image may be set according to the visual state, or may be reduced as the visual state is worse. Note that, for example, by performing dithering on the deteriorated region, it is possible to provide pixels in the deteriorated region while retaining the information of the input image. Further, in this case, inpainting or interpolation processing is performed on the pixels that do not have the information of the input image.

Various algorithms are known for inpainting and interpolation processing, respectively, and any of the algorithms can be applied as appropriate. For example, the inpainting algorithm may be, for example, an algorithm based on the Fast Marching Method (see Non-Patent Document 2) or an algorithm using a partial differential equation (for example, the Navier-Stokes equation) (non-patent). It may be an algorithm using machine learning (see Patent Document 3) or an algorithm using machine learning (see Non-Patent Document 4). Further, for the interpolation processing, any one of various interpolation methods such as polynomial interpolation, spline interpolation, linear interpolation, and cubic interpolation may be used.
Telea, Alexandru. “An image inpainting technique based on the fast marching method.” Journal of graphics tools 9.1 (2004): 23-34. Bertalmio, Marcelo, Andrea L. Bertozzi, and Guillermo Sapiro. “Navier-stokes, fluid dynamics, and image and video inpainting.” In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on, vol. 1, pp. I-355. IEEE, 2001. Liu et al. “Image Inpainting for Irregular Holes Using Partial Convolutions.” ArXiv: 1804.07723

In the blurring process, a part with poor visual condition may be strongly blurred and a part with good visual condition may be weakly blurred. An average value filter, a Gaussian filter, and a median filter may be used for the blurring process. Further, in the case of filling, the above-mentioned deteriorated region (more specifically, each pixel having no information of the input image among them) may be filled with a predetermined color (for example, gray). Alternatively, the entire image or a part of the image may be filled with an average color. Further, each area may be filled with a different color depending on the visual state. For example, an area having a relatively good visual state may be filled with a bright color, and an area having a relatively poor visual state may be filled with a dark color.

It is preferable that the angle of view of the input image is substantially the same in shape and size as the field of view corresponding to the estimated information. As shown in FIG. 3, when the field of view corresponding to the estimated information is circular and the input image is rectangular, there may be a region in the input image where there is no corresponding estimated information. In this case, in the area where there is no corresponding estimation information, either the above-mentioned inpainting or the filling process may be performed as in the case of the deteriorated area. Alternatively, extrapolation processing may be performed.

<Output / presentation step>
Next, the PC 20 outputs a simulation image according to the estimated information for presenting to the patient's eye. In the first embodiment, the simulation image is output to the patient terminal 30. Along with this, the patient terminal 30 presents the simulation image to the patient's eye. As a result, the patient can intuitively grasp the future visual state through the simulation image. As a result, the patient can be effectively motivated for treatment of visual field impairment. In other words, it is expected that patient adherence will improve.

<Simulation images are output and presented individually to the left and right patient eyes>
In the first embodiment, simulation images for the left and right patient eyes are obtained in the image processing step. The PC 20 may output a simulation image for each of the left and right patient eyes to individually present to each of the left and right patient eyes. That is, the PC 20 may output the simulation image so that the simulation image for the left eye is presented to the left eye and the simulation image for the right eye is presented to the right eye. Further, along with the simulation image, information for instructing the presentation mode in the terminal device 30 may be output from the PC 20. As an example, in the first embodiment, information for instructing the display position on the screen 31 in each of the simulation image for the left eye and the simulation image for the right eye may be output from the PC 20. The terminal device 30 may display the simulation image for the left eye on the left half of the screen 31 and the simulation image for the right eye on the right half of the screen 31 based on the instruction information. The simulation image for the left eye and the simulation image for the right eye may be presented at the same time, or may be presented one by one. One of the reasons why patients are less likely to notice symptoms in anopsia is that binocular vision complements the area lacking in visual field in one eye with the opposite eye. As described above, by simultaneously presenting the simulation image for the left eye and the simulation image for the right eye, the patient can experience the appearance in the binocular vision state in consideration of complementation. .. In addition, by presenting one simulation image for each of the left and right patient eyes, it is possible to intuitively and satisfactorily show the future vision of each eye. When presenting one by one, the patient terminal 30 displays an index (for example, symbols such as "L" and "R") for identifying which of the left and right patient eyes the simulation image is, at the same time as the simulation image. You may.

However, when the simulation images for each of the left and right patient eyes are presented one by one, it is not always necessary to present the simulation image to only one eye, and even if the simulation image corresponding to one eye is presented to both eyes. Good. That is, the same simulation image may be presented to both eyes. The future vision in each eye can be well observed by the patient with binocular vision.

<Output / present multiple simulation images corresponding to multiple time points>
In the image processing step, when a plurality of simulation images corresponding to a plurality of future time points in the patient's eye are obtained, the PC 20 may output the plurality of simulation images to the patient terminal 30. A plurality of simulation images corresponding to a plurality of future time points may be presented to the patient's eye in chronological order by, for example, the patient terminal 30. The simulation image may be presented while being switched in chronological order so that the appearance shown by the simulation image changes from the past or the present to the future. However, the present invention is not necessarily limited to this, and a plurality of simulation images corresponding to a plurality of time points may be presented to the patient's eye at the same time (in other words, in parallel). In this case, the patient can list and compare appearances at multiple time points.

<Generate and output (and present) simulation images for each obstacle progression speed>
The PC 20 may acquire estimated information indicating the visual state at a certain point in the future by the computer for each speed of failure, and in this case, further, in the image processing step, a simulation showing the appearance at a certain point in the future. Images may be generated for each failure progression rate.

For example, the time course of the degree of progression of the disorder is shown by the graph shown in FIG. In the graph shown in FIG. 4, the vertical axis represents the MD (mean deviation) value [dB], and the horizontal axis represents time. The MD value indicates a decrease in average sensitivity in the visual field, and is a kind of index indicating the degree of visual field impairment obtained by the visual field test. In FIG. 4, the straight line (which may be a curve) fitted to the MD value at each time point is called an MD slope. The rate of failure progression can be described by the slope of the MD slope [dB / year]. For example, the MD value at the past inspection point can be used to determine the MD slope when the progress rate does not change between the past and the future. The MD value at a certain age can be estimated based on the MD slope.

At this time, the rate of progression of the disorder differs between when properly treated and when not. Properly treated, the rate of progression is slower, and untreated, the rate of progression is faster.

Therefore, in the first embodiment, by assuming a second MD slope different from the above MD slope (referred to as the first MD slope for convenience), when the obstacle progresses at a different speed than before, The visual condition in the patient's eye at each point in the future is identified by the second MD slope. Here, the estimation information indicating the visual state at a certain point in time on the first MD slope can be obtained based on the above estimation process. Also, by assuming that the MD value and the visual state data have a one-to-one relationship, the visual state at one point in the second MD slope is different from the visual state at another point in the first MD slope. It is considered the same. Therefore, by correcting the time point at which the visual state is obtained in the above estimation process based on the correspondence relationship between the first MD slope and the second MD slope based on the MD value, at an arbitrary time point on the second MD slope. Estimated information indicating the visual state can be obtained. Further, based on the obtained estimated information, a simulation image at an arbitrary time point on the second MD slope can be obtained.

In addition, in FIG. 4, the second MD slope shows a worse prognosis with respect to the first MD slope. The difference in slope between the second MD slope and the first MD slope may be a statistical value based on the MD slopes of a plurality of patient eyes in the past. This value may be, for example, a default value or a value based on machine learning.

In the first embodiment, as described above, a simulation image showing the appearance at a certain point in the future is generated for each progress rate of the obstacle, and each simulation image is presented to the patient's eye. Since the two simulation images with different progression rates correspond to the case where the treatment is properly performed and the case where the treatment is not performed, the patient can be affected by the disability by presenting the respective simulation images. It is possible to make a good comparison of the difference in the future appearance due to the difference in the progress speed. As a result, the patient can be more effectively motivated for treatment.

It should be noted that a plurality of simulation images having different progression rates of the disorder may be presented to the patient's eye at the same time, or may be alternately displayed to the patient's eye. This allows patients to better compare future visions due to different rates of disability progression. When multiple simulation images with different disability progression rates are alternately presented to the patient's eye, a simulation image assuming a slower disability progression rate and a slower disability progression rate The assumed simulation image and the presentation order may be predetermined. Further, the presentation order may be changed according to the operation input from the examiner.

In addition, when presenting a plurality of simulation images in which the progression rates of disorders are different from each other, information indicating whether or not blindness may occur before the end of life may be presented to the patient.

Further, the PC 20 may receive information indicating the degree of failure via the user interface, generate and output a simulation image according to the degree of failure, and obtain and output a period until the degree of failure is reached. .. The information indicating the degree of disability may be, for example, an MD value, or information such as early, middle, and late stages. For example, when a certain MD value is accepted, the PC 20 provides information indicating how many years later the appearance will be reached together with a simulation image showing the appearance at the MD value, based on, for example, the above-mentioned MD slope. It may be acquired and output to the display device. For example, a plurality of information indicating the period until the degree of the input failure may be obtained for each failure progress rate.

<Display of simulation image at desired time point>
The above-mentioned MD slope can also be used when the PC 20 accepts information regarding a "time point" indicating the appearance by a simulation image via a user interface and generates a simulation image at that time point. For example, a simulation image showing the appearance at the time point may be generated based on the MD value corresponding to the input "time point" in the above-mentioned MD slope. This makes it possible to confirm the appearance of the examiner or the patient at a desired time point.

In addition, the PC 20 displays a simulation image at the input "point in time" based on the time (for example, age) correspondence between the first MD slope and the second MD slope, which have different speeds of failure. , It may be generated for each failure progress speed (for example, for each MD slope) and further output.

<Comparison display with how a normal person looks>
The PC 20 may output a simulation image and an image showing the appearance of a normal person to the patient's eye at the same time or alternately to switch and present the image. The image showing the appearance of a normal person may be, for example, an input image. By presenting the simulation image and the image showing the appearance of a normal person, the patient can better grasp the future appearance.

Although the above description has been made based on the embodiment, the present disclosure is not necessarily limited to the above embodiment, and can be appropriately modified and implemented.

<About the execution subject of the visual simulation program>
For example, in the first embodiment, the case where the visual simulation program is executed on the PC 20 has been described. However, the present invention is not necessarily limited to this, and the visual simulation program may be executed on a computer other than the PC 20. For example, it may be executed by either the examination device 10 and the patient terminal 30, or may be executed by a server computer (not shown).

Further, in the first embodiment, the device for inspecting the visual function of the patient's eye, the device for obtaining the simulation image based on the estimated information, and the device for presenting the simulation image to the patient's eye are separate bodies. However, the present invention is not limited to this, and any two or all of the above may be integrated. For example, Japanese Patent Application Laid-Open No. 2017-217016 discloses a head-mounted perimeter. Further, with such a device, a simulation image may be acquired based on the estimation information, and further, the simulation image may be presented to the patient's eye.

<Estimate future visual state based on degree classification>
For example, in the first embodiment, the simulation image has been described as being generated by the patient terminal 20 performing image processing based on the estimated information. However, the simulation image does not necessarily have to be obtained by image processing. For example, a plurality of simulation images may be prepared in advance according to the degree of disability classification.

For example, as an example of the degree classification due to glaucoma, the Lakezaki classification, the Aulhorn classification Greve modified method, and the degree classification of visual field defect in the Humphery perimeter are known. For example, according to any of these classifications. , A plurality of simulation images may be prepared in advance.

<About the output destination of the simulation image in the output / presentation step>
For example, in the first embodiment, the case where the simulation image is output from the PC 20 to the patient terminal 30 in the output / presentation step has been described. However, the simulation image is not necessarily limited to this, and the simulation image may be output to a memory accessible from the PC 20 (for example, a non-transient memory 22 and a memory of a server computer). Further, when the patient terminal 30 itself obtains the simulation image based on the estimation information, the output of the simulation image in the output / presentation step can be realized by the presentation output to the patient's eye via the monitor or the projector.

<Tracking by head-mounted display>
The terminal device 30 may detect the line-of-sight direction of the patient's eye and control the display position of the simulation image on the screen according to the line-of-sight direction (tracking). As a result, even if the line-of-sight direction of the patient's eye changes, the patient can appropriately observe the visual state of the patient's eye in the future.

<Other Examples of Display Device (Presentation Device)>
Further, for example, in the above embodiment, the display device for presenting the simulation image to the patient has been described as being a head-mounted display (patient terminal 30). However, it is not necessarily limited to this. The display device may be, for example, a stationary display, a projector that projects an image on a screen, or another display device. When a stationary display or projector is used as the display device, the estimated visual condition can be seen not only with the patient but also with his / her family and the examiner (for example, a doctor), and informed consent. It is useful for.

In the above embodiment, by using the head-mounted display (patient terminal 30) as a display device, images can be presented independently to the left eye and the right eye of the patient's eye. However, for example, when the above-mentioned stationary display or projector is used as a display device, the same image is presented to both eyes of the patient's eyes. At this time, the display device may display a simulation image showing how the image looks in the state of binocular vision at a certain point in time. The simulation image showing the appearance in the state of binocular vision with one image may be, for example, ORed by the logical sum of the two simulation images for each of the left and right eyes. The simulation image showing the appearance in the binocular vision state on one sheet is not limited to the case where the display device is a stationary display or a projector, and may be displayed on various display devices.

<Application to the estimation result of the visual state of the anterior segment>
In the above embodiment, a case where the retinal function at a certain time point is estimated as the visual function in the patient's eye and a simulation image is generated and presented based on the estimated retinal function has been described. As the visual function in the patient eye, the function related to the anterior segment of the patient eye at a certain time point may be estimated, and a simulation image may be generated and presented based on the estimated function of the anterior segment. In addition, the functions of both the anterior segment and the retina may be estimated, and simulation images may be generated and presented in consideration of both estimated functions. As the function of the anterior segment of the eye, for example, the refraction function (eye refractive power) may be estimated, the axial length value may be estimated, or the accommodation function (accommodation power) may be estimated. , The degree of turbidity in the translucent body may be estimated. These various functions can be appropriately measured by various ophthalmic measuring devices.

For example, when the refraction function is estimated, the refraction estimated by acquiring the PSF (point image intensity distribution) corresponding to the estimated refractive power and performing image processing (for example, convolution integration) between the PSF and the input image. A simulation image showing how it looks with force may be generated. Further, a simulation image may be generated by image processing (convolution integration) with the input image of the optical transfer function (OTF) obtained by further Fourier transforming the point image intensity distribution (PSF). The estimation of the refractive power is estimated based on, for example, a plurality of past inspections. For example, it may be estimated based on the fitting straight line (or curve) of the past inspection point, or it may be a value based on machine learning.

Other measurements of the patient's eye may be used to estimate visual function in the patient's eye. Furthermore, the visual function in the patient's eye may be estimated by using the test results of all test devices such as MRI, CT, PET, and ultrasound that image the body other than the eye, including the brain.

<Supplement: Embodiment included in the present disclosure>
Further, the embodiment of the present disclosure may be the following first visual simulation method and a visual simulation program for causing a computer to execute the visual simulation method.

The first visual simulation method is a simulation image showing how the patient's eye (the eye to be inspected) looks in a visual state different from the current visual state, and is different between the left eye and the right eye of the patient's eye. A simulation image for the left eye is displayed on the left eye and a simulation image for the right eye via a display device capable of independently presenting images to the left eye and the right eye of the patient's eye in the acquisition step of acquiring the simulation image. Is included in the presentation step, which is presented to the right eye at the same time. According to the first visual simulation method, the appearance when the visual state changes can be individually assumed for the left eye and the right eye, and the appearance by binocular vision at that time can be determined by the patient (subject). Can be experienced. Therefore, it is possible to experience the appearance when the visual state changes in a form closer to the actual appearance.

10 Eye examination device 20 PC
30 Patient terminal E Patient eye

Claims (12)

An estimation information acquisition step in which a computer acquires estimation information indicating a visual state in the patient's eye at a certain point in time, and
A visual simulation method including a simulation image showing the appearance in the patient's eye at a certain time point, and an output step output by the computer to present the simulation image according to the estimated information to the patient's eye. The first aspect of claim 1, further comprising an image processing step of generating the simulation image showing the appearance of the input image at a certain time point by processing the input image by the computer based on at least the estimated information. Visual simulation method. In the estimation information acquisition step, a plurality of the estimation information corresponding to a plurality of time points are acquired, and the estimation information is acquired.
The visual simulation method according to claim 2, wherein in the image processing step, the simulation images corresponding to each of a plurality of time points are generated based on the estimated information. The visual simulation method according to claim 3, wherein the simulation images corresponding to a plurality of time points are presented to the patient's eye in chronological order. In the estimation information acquisition step, the computer acquires the estimation information, which is a plurality of the estimation information and indicates the visual state at a certain point in the future, for each failure progress speed.
The visual simulation method according to any one of claims 2 to 4, wherein in the image processing step, the simulation image is generated by the computer based on each of the plurality of estimated information for each failure progress speed. In the estimation information acquisition step, the estimation information of each of the left and right patient eyes is acquired, and the estimation information is acquired.
The visual sense according to any one of claims 1 to 5, wherein in the output step, the simulation image corresponding to the estimated information of each of the left and right patient eyes is output for presenting to the left and right patient eyes individually. Simulation method. The visual simulation method according to claim 6, wherein the left eye is presented with the simulation image generated for the left eye, and at the same time, the simulation image generated for the right eye is presented to the right eye. The estimated information acquired in the estimated information acquisition step is an estimated value of the degree in a predetermined degree classification regarding a disability.
The visual simulation method according to claim 1, further comprising a selection step in which the computer selects one of the plurality of simulation images prepared in advance for each degree of the predetermined degree classification according to the estimated information. The visual simulation method according to any one of claims 1 to 8, wherein in the estimation information acquisition step, the estimation information is acquired by an estimation process based on a past test result regarding the visual function in the patient's eye. The visual simulation method according to claim 9, wherein past test results relating to visual function indicate retinal luminosity factor for each site. The visual simulation method according to claim 9, wherein the past examination results regarding the visual function are OCT data of the fundus or a frontal image. A visual simulation program for causing the computer to execute the visual simulation method according to any one of claims 1 to 11.