JP2018047084A - Ophthalmologic examination apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the precision and accuracy of tear fluid examination.SOLUTION: An ophthalmologic examination apparatus 1 includes an OCT collection unit 30, a segmentation processing unit 41, and a distribution information acquisition unit 42. The OCT collection unit scans the anterior eye part of a subject eye using optical coherence tomography (OCT) to collect three-dimensional images representing tear fluid on the cornea. The segmentation processing unit applies segmentation processing to the three-dimensional images to determine at least one of an oil layer region corresponding to an oil layer of the tear fluid a liquid layer region corresponding to a liquid layer of the tear fluid. The distribution information acquisition unit acquires information representing a distribution of tear fluid thicknesses, based on a processing result of the segmentation processing unit.SELECTED DRAWING: Figure 1

Description

  The present invention relates to an ophthalmic examination apparatus.

  In recent years, the number of dry eye patients has increased due to overuse of the eyes by computer work (VDT work), drying of air by air conditioning, and wearing of contact lenses. There are various types of dry eye, and various techniques for evaluating (specifying, estimating, classifying, and the like) have been proposed (see, for example, Patent Documents 1 to 8).

JP 2011-156030 A JP-A-11-267102 JP 2006-314651 A JP 2007-209370 A Japanese Patent Laying-Open No. 2015-91322 Special table 2010-530282 JP2015-43929A JP 2013-212363 A

  In the conventional typical technique for evaluating the type of dry eye, in order to grasp the state of tears (destruction, movement, etc.) consisting of an oil layer and a liquid layer (including secretory mucin and membrane mucin), An anterior ocular segment image obtained by fluorescence contrast imaging and an interference pattern due to the surface reflection and back surface reflection of the tear film are used. With the “indirect” technique using such a phenomenon, it is difficult to examine the complicated structure and dynamics of tears with high accuracy and high accuracy.

  An object of the present invention is to improve the accuracy and accuracy of tear examination.

In an exemplary embodiment, the ophthalmic examination apparatus uses an optical coherence tomography (OCT) to scan the anterior segment of the subject's eye to collect a three-dimensional image representing tear fluid on the cornea. A segmentation processing unit that identifies at least one of an oil layer region corresponding to the oil layer of the tear fluid and a liquid layer region corresponding to the liquid layer by applying a segmentation process to the three-dimensional image, and the segmentation processing A distribution information acquisition unit that acquires distribution information of the thickness of the tears based on a result of processing by the unit.
In another exemplary embodiment, the ophthalmic examination apparatus displays a three-dimensional image representing tear fluid on the cornea collected by scanning the anterior segment of the subject eye using optical coherence tomography (OCT). A receiving unit that accepts the segmentation processing unit that identifies at least one of an oil layer region corresponding to the oil layer of the tear fluid and a liquid layer region corresponding to the liquid layer by applying a segmentation process to the three-dimensional image; A distribution information acquisition unit configured to acquire distribution information of the tear thickness based on a result of processing by the segmentation processing unit;

  According to the ophthalmic examination apparatus of the embodiment, it is possible to improve the accuracy and accuracy of tear examination.

Schematic showing the structure of an exemplary ophthalmic examination apparatus. Schematic for demonstrating the structure of an exemplary ophthalmic examination apparatus. Schematic for demonstrating the structure of an exemplary ophthalmic examination apparatus. The flowchart showing operation | movement of an example ophthalmic examination apparatus. Schematic for demonstrating operation | movement of an exemplary ophthalmic examination apparatus. Schematic for demonstrating operation | movement of an exemplary ophthalmic examination apparatus. Schematic for demonstrating operation | movement of an exemplary ophthalmic examination apparatus. Schematic for demonstrating operation | movement of an exemplary ophthalmic examination apparatus. Schematic for demonstrating operation | movement of an exemplary ophthalmic examination apparatus. Schematic showing the structure of an exemplary ophthalmic examination apparatus.

  An exemplary embodiment of the present invention will be described with reference to the drawings. In addition, the description content of the literature referred in this specification, and another well-known technique can be used for embodiment.

  The ophthalmic examination apparatus according to the embodiment is based on a three-dimensional image representing tear fluid on the cornea collected by scanning the anterior segment of the eye using optical coherence tomography (OCT). Thickness distribution information (tear thickness distribution information) can be created. The ophthalmic examination apparatus of the embodiment can further specify a tear destruction region based on the tear thickness distribution information (destruction region distribution information). In addition, when the distribution of the location where the tear thickness is equal to or less than the predetermined threshold is created as the tear thickness distribution information, the tear thickness distribution information is (substantially) the same as the distribution information of the destruction region.

  In one typical example, the ophthalmic examination apparatus according to the embodiment performs a temporal change in the tear thickness distribution based on a time-series image (a series of three-dimensional images and a three-dimensional image group) representing the dynamics of tears. Can be acquired. Further, the temporal change in the distribution of the fracture region can be obtained from the temporal change in the tear thickness distribution.

  A time-series image representing the dynamics of tear fluid includes a series of three-dimensional images acquired at different times. Typically, an OCT scan of the anterior segment is repeated at a predetermined repetition interval (a predetermined repetition frequency). Collected by. The scan pattern at this time is, for example, a raster scan including a plurality of line scans parallel to each other.

  The ophthalmic examination apparatus according to the embodiment includes an optical system, a drive system, a control system, and a data processing system for executing OCT, and is configured to execute, for example, Fourier domain OCT.

  The Fourier domain OCT includes a spectral domain OCT and a swept source OCT. Spectral domain OCT is a technique for imaging a subject's eye by acquiring a spectrum of interference light by spatial division using a broadband low-coherence light source and a spectroscope and performing Fourier transform on the spectrum. Swept source OCT uses a wavelength-swept light source (wavelength variable light source) and a photodetector (balanced photodiode, etc.) to acquire the spectrum of interference light in a time-sharing manner, and Fourier transforms the eye to be examined. This is a technique for imaging. The method of OCT is not limited to Fourier domain OCT, but may be time domain OCT or unfaced OCT.

  The ophthalmic examination apparatus according to the embodiment may include a modality (for example, a modality other than OCT) for imaging the eye and / or other parts. Typical examples include a fundus camera, SLO (Scanning Laser Ophthalmoscope), a slit lamp microscope, and an ophthalmic surgical microscope. Further, the ophthalmic examination apparatus according to the embodiment may include a configuration for measuring characteristics of the eye and / or other parts and a configuration for performing an examination.

  In a typical embodiment, the ophthalmic examination apparatus can acquire a front image of an anterior eye part (cornea or the like). An example of the front image is an anterior segment image obtained with a slit lamp microscope or the like. The front image is, for example, an image obtained by using a pigment such as fluorescein, rose bengal, or lissamine green, or an image showing an interference pattern due to the surface reflection and back reflection of a tear layer (for example, oil layer). It's okay.

  In another exemplary embodiment, the ophthalmic examination apparatus may not have a function for performing OCT. The ophthalmic examination apparatus has a function of receiving an OCT image acquired by another apparatus (OCT apparatus) and an OCT image stored in another apparatus (electronic medical chart system, image archiving system, etc.), and this OCT image. And a function to process. That is, the ophthalmic examination apparatus of this example functions as an ophthalmic image processing apparatus that processes an OCT image of the eye to be examined. Conversely, an ophthalmic examination apparatus including an OCT function can be said to have an OCT function added to such an ophthalmic image processing apparatus.

  The function of receiving an OCT image is, for example, receiving an OCT image from another device (image archiving system, slit lamp microscope, OCT device, etc.) via a communication line such as a local area network (LAN), the Internet, or a dedicated line. For example, a communication device for reading data or a data reader for reading data from a recording medium (image reception unit).

  The data processing function (calculation function, image processing function, control function, etc.) in the ophthalmic examination apparatus according to the embodiment includes, for example, hardware such as a processor and a storage device, and software such as a calculation program, an image processing program, and a control program. Realized by collaboration. A part of the hardware may be provided in an external device that can communicate with the ophthalmic examination apparatus. Further, at least a part of the software may be stored in advance in the ophthalmic examination apparatus and / or may be stored in advance in the external apparatus.

  The ophthalmic examination apparatus according to the embodiment may be configured to evaluate the type of dry eye based on tear film thickness distribution information or its change over time. In addition, the ophthalmic examination apparatus according to the embodiment may be configured to evaluate the type of dry eye based on the destruction area distribution information or its change over time.

  Therefore, the ophthalmic examination apparatus according to the embodiment can obtain predetermined information based on such distribution information and its change over time. The predetermined information may include, for example, at least one of the following four pieces of information: information indicating the size of the destruction area (size information); information indicating the shape of the destruction area (shape information); Information indicating the position (position information); Information indicating the elapsed time from opening to the onset of destruction (time information). Here, “destructive expression” is not limited to the occurrence of tear destruction, but may be the occurrence of a predetermined form of destruction. Further, “destructive expression” is not limited to a single time but may be a period.

  Furthermore, the ophthalmic examination apparatus according to the embodiment can evaluate the type of dry eye of the eye to be examined based on the determined predetermined information. That is, the embodiment can estimate the state of tears from the characteristics of the fracture region, and thereby evaluate the type of dry eye. The type of dry eye (that is, the pattern of the tear breaking region) to be evaluated according to the embodiment is arbitrary, and is typically a spot type, a line type, an area type, or a random ( Random type, dimple type, and the like. Details of these types will be described later.

<First Embodiment>
<Constitution>
An exemplary embodiment of an ophthalmic examination apparatus will be described. In the present embodiment, an ophthalmic examination apparatus including a function (OCT collection unit) for acquiring an OCT image will be described. In addition, although illustration is abbreviate | omitted, the ophthalmic examination apparatus of this embodiment may be provided with the function (image reception part) which receives an OCT image from an external device.

  Examples of the configuration of the ophthalmic examination apparatus according to this embodiment are shown in FIGS. 1, 2A, and 2B. The ophthalmic examination apparatus 1 collects one or more three-dimensional images representing tear fluid on the cornea by OCT scan, and identifies the oil layer region and / or the liquid layer region by segmenting the three-dimensional image. And / or tear thickness distribution information is acquired based on the liquid layer region. In addition, it is possible to specify the tear destruction area and evaluate dry eye.

  The ophthalmic examination apparatus 1 can display a three-dimensional image and information obtained therefrom on the display device 2. Examples of information obtained from a three-dimensional image include a map representing the distribution of tear thickness, a map representing the distribution of fractured areas, and dry eye type evaluation results. The display device 2 may be a part of the ophthalmic examination apparatus 1 or may be an external device connected to the ophthalmic examination apparatus 1.

  The ophthalmic examination apparatus 1 includes a control unit 10, a storage unit 20, an OCT collection unit 30, a data processing unit 40, an operation unit 50, and a front image acquisition unit 60.

<Control unit 10>
The control unit 10 controls each unit of the ophthalmic examination apparatus 1. The control unit 10 includes a processor. The “processor” is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), a programmable logic device (for example, SPLD (Simple Programmable L). , A circuit such as a field programmable gate array (FPGA). For example, the control unit 10 can realize the functions according to the embodiment by reading and executing a program stored in a storage circuit or a storage device (such as the storage unit 20 or an external device).

  The control unit 10 may include a communication device for transmitting and receiving data via a communication line such as a LAN, the Internet, or a dedicated line.

<Display control unit 11>
The control unit 10 includes a display control unit 11. The display control unit 11 executes control for displaying information on the display device 2. The display control unit 11 can perform processing (generation, processing, synthesis, etc.) regarding information displayed on the display device 2. You may comprise so that the said process may be performed by cooperation with the display control part 11 and other elements (Other elements of the control part 10, the data processing part 40 grade | etc.,).

<Storage unit 20>
Various information is stored in the storage unit 20. In this example, evaluation criterion information 21 is stored in advance. The evaluation criterion information 21 may be stored in an external device.

<Evaluation criteria information 21>
The evaluation criterion information 21 is information that is referred to for evaluating the type of dry eye, and includes evaluation criteria for each of one or more types of dry eye. The evaluation of the dry eye type need not be performed with reference to the evaluation standard information 21. For example, a part or all of the evaluation may be performed without referring to the evaluation standard information 21, or the evaluation standard information 21 may be evaluated. It is possible to perform part or all of the evaluation with reference to FIG.

  An example of the evaluation criterion information 21 is shown in FIG. 2A. The evaluation reference information 21 in this example includes a pattern of a tear-breaking region as a dry eye type. In this destruction area pattern, five typical types of “Area”, “Spot”, “Line”, “Dimple”, and “Random” are provided. The destruction area pattern is not limited to these, and the type of dry eye is not limited to the destruction area pattern.

  Further, in the evaluation reference information 21 of this example, as the evaluation items of the destruction area pattern, the “elapsed time since opening” item, the “size / shape” item, and the “position” item indicating the position of the destruction area Is provided. The “elapsed time from opening” item represents an elapsed time from opening to the onset of tear destruction, and includes evaluation criteria such as a threshold and a range related to the elapsed time, for example. The “size / shape” item represents the size and shape of the destruction area, and includes, for example, evaluation criteria such as a threshold value and range regarding the size, and evaluation criteria such as a threshold value and range regarding the shape. The “position” item represents the position of the fracture region on the cornea, and includes evaluation criteria such as a threshold value and a range regarding the position, for example. Note that the evaluation items are not limited to these, and the evaluation criterion information 21 may include known evaluation items and / or newly obtained evaluation items such as the extension speed of the fracture region.

  The five destruction area patterns illustrated in FIG. 2A will be described. First, the “Area” type is a destruction area pattern found in the eye to be examined with extremely little tear fluid, and may be accompanied by a high degree of corneal epithelial disorder. In this type, because there is an extremely shortage of water, neither the oil layer stretches nor the water moves, and tears are destroyed in a wide area after the opening (end of blinking). . In other words, in this type, a tear film is not formed even immediately after opening. This type of eye is treated using a punctal plug or the like.

For such an “Area” type, for example, the following evaluation criteria are provided. First, in the “Elapsed time since opening” item, “No tear film is formed even immediately after opening” is set as an evaluation criterion. As shown in Figure 2B, when the time eyelid opening and T = 0 (seconds), evaluation of "Area" type, preset time T = T _A or near the time as the timing of the "eyelid opening immediately" ( T ≒ T _a) to the tear film is performed by determining whether it is formed. In addition, in the “size / shape” item, the shape of the destruction area is “spot-like” as an evaluation criterion. For example, a threshold relating to size (upper limit value, etc.) and a threshold relating to shape (lower limit of circularity) Value). Furthermore, the “position” item is provided as an evaluation criterion that a fracture region occurs in a “wide range” on the cornea, and includes, for example, a threshold value (lower limit value, etc.) relating to the range. In summary, in the “Area” type, a point-like fracture region is generated in a wide area on the cornea immediately after opening.

  The “Spot” type is a characteristic round-shaped tear destruction seen immediately after opening, and is typically due to a decrease in the wettability of the corneal epithelium due to membrane mucin damage. In this type, a destruction region appears in the process of applying moisture in the process of forming a tear film, and is detected as a circular tear destruction immediately after opening. This type is referred to as water wettability reduction type dry eye, BUT shortened type dry eye, or the like. Here, “BUT” means Breakup Time (tear breaking time). In this type, improvement is generally achieved by continuous administration of eye drops.

For such “Spot” type, for example, the following evaluation criteria are provided. First, “immediately after opening” is provided as an evaluation criterion in the “Elapsed time since opening” item. As shown in FIG. 2B, when the opening time is T = 0 (seconds), the evaluation regarding the “Spot” type is time T = T _S set in advance as the timing “immediately after opening” or a time nearby ( T≈T _S ). Here, as shown in FIG. 2A, the evaluation time T _S regarding the “Spot” type may be later than the evaluation time T _A regarding the “Area” type. Conversely, the evaluation time T _S regarding the “Spot” type may be earlier than the evaluation time T _A regarding the “Area” type. Alternatively, these evaluation times T _A and T _S may be equal. In addition, in the “size / shape” item, the size / shape of the destruction area is set to be “large circle” as an evaluation criterion. For example, a threshold relating to size (lower limit value, etc.) Lower limit value, etc.). Furthermore, the “position” item is provided as an evaluation criterion that a fracture region occurs in a “wide range” on the cornea, and includes, for example, a threshold value (lower limit value, etc.) relating to the range. In summary, in the “Spot” type, a large circular fracture region is generated over a wide area on the cornea immediately after opening. In this type, it is known that the destruction area expands rapidly.

  The “Line” type is tear destruction that occurs during the movement of water with the extension of the oil layer, and typically results from a mild to moderate decrease in tears (water). When moderate tear reduction occurs, tear tears often develop in the lower part of the process while water is moving upward. In this type, the effect of eye drops is expected.

For such “Line” type, for example, the following evaluation criteria are provided. First, in the “Elapsed time since opening” item, “in the middle of upward movement of moisture accompanying the upward extension of the oil layer” is provided as an evaluation criterion. As shown in FIG. 2B, when the opening time is T = 0 (seconds), the evaluation regarding the “Line” type is a time T set in advance as a timing at which the upward movement of moisture accompanying the upward extension of the oil layer is started. _{After L} (T ≧ T _L ). In addition, in the “size / shape” item, the shape of the destruction area is “parallel line extending vertically” as an evaluation criterion. For example, a threshold value related to the shape (such as a lower limit value of linearity) The range of the direction of the destruction area with respect to the direction and the threshold value (lower limit value) of the parallelism of the plurality of destruction areas are included. Furthermore, the “position” item is provided with an evaluation criterion that a fracture region occurs in the “lower” (region close to the lower eyelid) on the cornea. For example, a range in the image frame (a range corresponding to the lower portion) The range of the relative position with respect to the predetermined part is included. In summary, in the “Line” type, in the middle of the upward movement of moisture accompanying the upward extension of the oil layer, a parallel line-shaped fracture region extending vertically is generated in the lower part.

  The “Dimple” type is a tear destruction that occurs at various positions during the upward movement of a dye such as fluorescein administered to the subject's eye. Presents a shape.

For such a “Dimple” type, for example, the following evaluation criteria are provided. First, in the “elapsed time since opening” item, “in the middle of upward movement of the pigment” is provided as an evaluation criterion. As shown in Figure 2B, when the time eyelid opening and T = 0 (seconds), evaluation of "Dimple" type, preset time T _D since the timing of the upward movement of the dye is started (T ≧ T _D ). In addition, in the “size / shape” item, it is provided as an evaluation criterion that the shape of the destruction region is “various (circular, linear, planar)”. , A threshold value of linearity (lower limit value, etc.) is included. Furthermore, the “position” item is provided with an evaluation criterion that a fracture region occurs in the “top” (region close to the upper eyelid) on the cornea. For example, a range in the image frame (a range corresponding to the top) The range of the relative position with respect to the predetermined part is included. In summary, in the “Dimple” type, an indefinitely shaped fracture region occurs in the upper part during the upward movement of the pigment. In this type, it is known that the destruction area expands rapidly.

  The “Random” type is tear fluid destruction that appears at various positions after the oil layer (or pigment) extends upward, and exhibits an indefinite destruction shape such as circular, linear, or planar. This type is the mildest dry eye, and eye drops are effective. Further, it is known that this type is frequently used in the dry evaporation type eye that changes every blink.

For such “Random” type, for example, the following evaluation criteria are provided. First, the “elapsed time since opening” item is provided with “after completion of oil layer extension” as an evaluation criterion. As shown in FIG. 2B, when the opening time is T = 0 (seconds), the evaluation regarding the “Random” type is time T _R or later (T ≧ T _R) set in advance as the timing when the upward extension of the oil layer is completed. ). In addition, in the “size / shape” item, it is provided as an evaluation criterion that the shape of the destruction region is “various (circular, linear, planar)”. , A threshold value of linearity (lower limit value, etc.) is included. Furthermore, the “position” item is provided as an evaluation criterion that a fracture region occurs in a “wide range” on the cornea, and includes, for example, a threshold value (lower limit value, etc.) relating to the range. In summary, in the “Random” type, after the upward extension of the oil layer is completed, a fracture region having an indefinite shape occurs in a wide range.

  As shown in FIG. 2B, when a new blink occurs, time T can be reset to zero simultaneously with subsequent opening. For blinking, for example, a metronome or the like may be used to instruct the subject to perform this at predetermined intervals, or an anterior observation image obtained in real time may be analyzed. This may be detected. Alternatively, the collected time-series images can be analyzed to identify the blinking image. Further, instead of resetting the time, the elapsed time may be calculated by calculating the difference between the time corresponding to the opening and the acquisition time of an arbitrary image.

<OCT collection unit 30>
The OCT collection unit 30 collects a three-dimensional image representing tear fluid on the cornea by scanning the anterior segment of the eye to be examined using OCT. In a typical example, the OCT collection unit 30 collects a three-dimensional image group (a series of three-dimensional images and time-series images) representing tear fluid dynamics by repeatedly scanning the anterior segment using OCT. be able to.

  In another typical example, the OCT acquisition unit 30 can form a single three-dimensional image. At this time, the OCT collection unit 30 can perform a three-dimensional scan once. Alternatively, a single three-dimensional image can be formed by, for example, averaging a plurality of three-dimensional images obtained by repeating a three-dimensional scan a predetermined number of times. Note that processing such as addition averaging is also applicable when collecting a three-dimensional image group.

  The OCT collection unit 30 includes a configuration for performing measurement using, for example, a spectral domain OCT or a swept source OCT. This configuration includes an optical system, a drive system, a data acquisition system (DAQ), a control system, an image forming unit (processor), and the like, as in the past. This optical system includes, for example, an interference optical system, an optical scanner, and a photodetector. The interference optical system divides the light output from the light source into measurement light and reference light, projects the measurement light onto the subject's eye, and superimposes the return light of the measurement light from the subject's eye on the reference light to cause interference light. Is generated. The optical scanner includes a galvano scanner and the like, and deflects measurement light. The photodetector detects (the spectrum of) interference light generated by the interference optical system. The OCT collection unit 30 scans a three-dimensional region (including the cornea) of the anterior segment (three-dimensional scan).

  The image forming unit forms a three-dimensional image based on the three-dimensional data set collected by the three-dimensional scan. This processing includes, for example, noise removal (noise reduction), filter processing, FFT (Fast Fourier Transform), and the like, as in the conventional OCT technology. Each three-dimensional image is constructed as stack data or volume data, for example. When the three-dimensional region of the anterior segment is repeatedly scanned, the image forming unit applies a similar process to each of the series of three-dimensional data sets collected by the repeated scanning, thereby obtaining a series of three-dimensional images (3 Dimensional image group, time-series image).

  The image forming unit renders a 3D image to form a B-mode image (longitudinal section image, axial section image), C-mode image (transverse section image, horizontal section image), projection image, shadowgram, etc. can do. An image of an arbitrary cross section such as a B mode image or a C mode image is formed by selecting pixels (pixels, voxels) on a specified cross section from a three-dimensional image. The projection image is formed by projecting a three-dimensional image in a predetermined direction (Z direction, depth direction, A scan direction). The shadowgram is formed by projecting a part of a three-dimensional image (for example, partial data corresponding to a specific layer) in a predetermined direction.

<Data processing unit 40>
The data processing unit 40 performs various data processing. For example, the data processing unit 40 performs image processing and image analysis. The data processing unit 40 includes a segmentation processing unit 41, a distribution information acquisition unit 42, a destruction area specifying unit 43, and an evaluation processing unit 44.

<Segmentation processing unit 41>
The segmentation processing unit 41 applies segmentation to the three-dimensional image collected by the OCT collection unit 30. Segmentation is used to determine a specific organization or organization boundary. Thereby, a corneal tissue and a tear film are specified.

  When a time series image is obtained, the segmentation processing unit 41 applies the segmentation to each of a plurality of three-dimensional images included in the time series image. Here, the plurality of images to be segmented may be a part or all of a series of three-dimensional images constituting the time-series image. As an example in the case of analyzing only a part of the image group, there is a case where an image acquired during blinking is specified in advance and only an image other than them is segmented.

  In a typical example, the segmentation processing unit 41 can identify an oil layer region corresponding to the tear oil layer and a liquid layer region corresponding to the liquid layer. In other words, the boundary between the cornea and the tears (liquid layer), the boundary between the liquid layer and the oil layer, and the boundary between the oil layer and the air can be specified. It is also possible to specify only the oil layer region or only the liquid layer region.

  Although segmentation is widely used in ophthalmic OCT, it is novel to apply it to the identification of any of the tear film (oil layer, liquid layer, mucin layer). It is also novel to apply segmentation to the identification of any one of the tear film and any one of the corneal layers (corneal epithelium, Bowman's membrane, lamina propria, Deure's layer, Descemet's membrane, corneal endothelium).

  The mucin layer may be classified as an inner layer of the liquid layer or an outer layer of the liquid layer. In the embodiment, “specification of the liquid layer region” specifies the region corresponding to the liquid layer including the mucin layer and / or the region corresponding to the liquid layer not including the mucin layer and the region corresponding to the mucin layer. Or one or both of them may be specified.

  It is known that the total tear thickness is about 7 μm. A configuration for realizing sufficient resolution (particularly axial resolution) to perform segmentation of tears having such a thickness can be used. For example, a light source having suitable characteristics (center wavelength, wavelength width, etc.) can be used. In addition, any technique (such as adaptive optics or image processing) for increasing the resolution can be applied.

<Distribution information acquisition unit 42>
The distribution information acquisition unit 42 acquires tear film thickness distribution information based on the result of processing by the segmentation processing unit 41. When a time-series image is obtained and segmentation is applied to each of a plurality of three-dimensional images included therein, tear film thickness distribution information corresponding to each three-dimensional image is acquired.

  The distribution information acquisition unit 42 obtains the thickness of the tear film at each measurement point in the scan range based on the oil layer region and / or the liquid layer region specified by the segmentation. The thickness of the tear film may be, for example, one of the thickness of the oil layer area, the thickness of the liquid layer area, and the thickness of the entire tear film. Here, the thickness of the liquid layer region may be the thickness of the liquid layer including the mucin layer or the thickness of the liquid layer not including the mucin layer. In the latter case, the thickness of the mucin layer can also be obtained.

  By such treatment, for example, the distance between the surface of the oil layer (boundary between the oil layer and air) and the back surface (boundary between the liquid layer of the oil layer) and the front surface of the liquid layer (boundary with the liquid layer of the oil layer) And the back surface (boundary between the liquid layer and the cornea), the distance between the surface of the oil layer and the back surface of the liquid layer, and the like are calculated.

  The thickness at each measurement point is calculated by, for example, a process of counting the number of pixels corresponding to the tear film along a predetermined measurement direction, and a distance (unit) corresponding to the number of pixels and the pixel pitch obtained thereby. And a process of multiplying by (distance).

  Here, the direction in which the number of pixels is counted (the above-described measurement direction) is arbitrary, and for example, the A-line direction in the OCT scan or the normal direction at each position on the corneal surface can be applied as the measurement direction. The process of specifying the normal direction at each position on the corneal surface includes, for example, approximation of a curved surface of the corneal surface, specification of a tangent plane at each position, and specification of a normal line of each tangent plane.

  The distribution information acquisition unit 42 can also apply a process (flattening) for planarizing a predetermined region (for example, the corneal surface) specified by the segmentation to the three-dimensional image. By flattening, the thickness can be easily calculated. Further, by displaying the flattened image, the thickness distribution can be easily grasped.

<Destruction area specifying part 43>
The destruction area specifying unit 43 specifies a tear destruction area based on the tear thickness distribution information acquired by the distribution information acquisition unit 42. The destruction area is, for example, one of the area where the oil layer is destroyed (area where the oil layer area is not detected) and the area where the liquid layer is destroyed (area where the liquid layer area is not detected), or a combination of these areas. . In the region where the entire tear is destroyed, neither the oil layer region nor the liquid layer region is detected.

  In a typical example, the destruction area specifying unit 43 can specify a part where the thickness of the oil layer area is equal to or less than a predetermined threshold as an area where the oil layer is destroyed. Moreover, the destruction area specific | specification part 43 can specify the part whose thickness of a liquid layer area | region is below a predetermined threshold as an area | region where the liquid layer was destroyed. Moreover, the destruction area | region specific | specification part 43 can specify the part whose thickness of a tear film area (combination area | region of an oil layer area | region and a liquid layer area | region) is below a predetermined threshold value as an area | region where the whole tear film layer was destroyed.

  The destruction area specifying unit 43 can perform a labeling process on the specified destruction area. Thereby, one or more connected regions included in the entire specified destruction region are specified. One or more connected regions are also called fracture regions. By such a labeling process, one or more destructive regions drawn in the three-dimensional image are specified so as to be distinguishable from each other.

  When a time-series image is acquired, the destruction area specifying unit 43 executes the above-described process for each of a plurality of three-dimensional images included therein. Thereby, one or more destructive regions drawn in each of the plurality of three-dimensional images are specified. In addition, by the labeling process, it is possible to associate the destructive areas depicted in different three-dimensional images, and to grasp the temporal change of the destructive areas.

  In addition, the thickness of tears can also be obtained based on an image different from the OCT image. For example, when a fluorescence contrast image using a fluorescent dye such as fluorescein is obtained, the thickness of tears can be estimated based on the fluorescence intensity (pixel value). In addition, the tear thickness can be estimated based on the interference pattern due to the surface reflection and back surface reflection of the tear film (for example, oil layer).

  The destruction area can be specified based on an image different from the OCT image. For example, when a front image of the anterior eye part is obtained, the destruction area specifying unit 43 performs, for example, the following processing on the front image. First, when the front image is not a grayscale image (black and white image) (for example, when the front image is a fluorescein fluorescence contrast image), the destruction area specifying unit 43 converts the front image into a grayscale image. This conversion process is performed using, for example, known image processing software or a predetermined lookup table.

  Next, the destructive area specifying unit 43 specifies a range to be analyzed for specifying the destructive area based on the pixel value (luminance value) of the grayscale image. This processing includes, for example, pixel value threshold processing. In this threshold processing, one or more thresholds are used.

  In general, it is not easy to automatically determine whether the decrease (or increase) in luminance is due to tear tear destruction or illumination unevenness. Therefore, a device for this automatic discrimination can be applied. For example, it is possible to devise a threshold value. Further, weighting and brightness correction can be performed for each part of the image frame based on the direction of the illumination light projected on the cornea. As an example, when illumination light is projected from the front onto the cornea, weighting and correction can be performed so as to increase the luminance of the peripheral portion of the image frame. Alternatively, a grayscale image (or an image before grayscale conversion) may be displayed, and range designation, weighting, and correction may be performed manually. Or, by using a light source (surface light source, diffuser plate, etc.) having a shape according to the corneal surface shape or a plurality of light sources arranged in three dimensions according to the corneal surface shape as illumination light sources, uneven illumination is reduced. It is also possible to do.

  After specifying the analysis target range, the destruction region specifying unit 43 specifies the destruction region by binarizing the analysis target range using a predetermined threshold. The destruction area specifying unit 43 performs a labeling process on the specified destruction area. Thereby, one or more connected regions included in the entire specified destruction region are specified. One or more connected regions are also called fracture regions. By such a labeling process, one or more destructive areas drawn in the front image are specified so as to be distinguishable from each other.

  When a time-series image including a series of front images is obtained, the destruction area specifying unit 43 can apply the above process to each of a plurality of front images included in the series of front images. Thereby, one or more destructive regions drawn in each of the plurality of front images are specified. In addition, by the labeling process, it is possible to associate the destructive areas drawn in different front images, and it is possible to grasp the temporal change of the destructive areas.

  In another processing example, the destruction area specifying unit 43 can create a pseudo color map corresponding to the pixel value of the front image or the luminance value (fluorescence intensity or the like) of the grayscale image. Furthermore, the destruction area specifying unit 43 can specify the destruction area by binarizing the pseudo color map based on the hue value (reflecting the thickness of the tear film).

  When two or more types of distribution information (tear thickness distribution information, destruction area distribution information, etc.) are obtained from two or more types of images (image group) relating to the same eye, these distribution information are compared or synthesized. It is possible. For example, a difference between at least a part of the first distribution information created from the OCT image and at least a part of the second distribution information obtained from the front image can be obtained. Moreover, at least a part of the first distribution information and at least a part of the second distribution information can be synthesized. In addition, other distribution information can be used to interpolate or refine one distribution information.

<Evaluation processing unit 44>
The evaluation processing unit 44 determines the dry eye type of the eye to be examined based on the tear thickness distribution information acquired by the distribution information acquisition unit 42 and / or the destruction area distribution information acquired by the destruction area specifying unit 43. evaluate.

  Although illustration is omitted, the evaluation processing unit 44 includes an evaluation information acquisition unit. The evaluation information acquisition unit acquires information (evaluation information) used for dry eye type evaluation based on the destruction region distribution information acquired by the destruction region specifying unit 43. The same processing can be applied to the case where the evaluation information is acquired from the tear thickness distribution information acquired by the distribution information acquisition unit 42.

  The evaluation information acquisition unit determines each destruction identified from the three-dimensional image based on a specific result by the destruction region specifying unit 43 for the three-dimensional image (or each of a plurality of three-dimensional images included in the time-series image). Get evaluation information about a region.

  The evaluation information includes, for example, at least one of size information, shape information, position information, and time information. In this example, a configuration example capable of obtaining all four types of information will be described. Although illustration is omitted, the evaluation processing unit 44 of this example includes a size information acquisition unit, a shape information acquisition unit, a position information acquisition unit, and a time information acquisition unit.

  The size information acquisition unit acquires size information of the destruction area. The size information may be arbitrary information indicating the size of the destruction area, and examples thereof include the area of the destruction area and the longest diameter.

  The process of calculating the area includes, for example, a process of counting the number of pixels included in the destruction area, and a process of multiplying the number of pixels obtained thereby and an area (unit area) corresponding to one pixel. Including.

  The process of calculating the longest diameter (Greatest Linear Dimension, GLD) includes, for example, a process of specifying a combination of two points having the maximum distance among a combination of two points on the outer edge (contour) of the fracture region. This process includes, for example, a step of fixing one point on the outer edge of the fracture area and a step of calculating a distance between this fixed point and each of the other points on the outer edge while changing the fixing point. By repeating, the distance corresponding to all the combinations of two points on the outer edge is obtained, and the maximum value of all the obtained distances is specified.

  The shape information acquisition unit acquires shape information of the destruction area. The shape information may be arbitrary information representing the shape of the destruction area, and examples thereof include the circularity and the straightness of the destruction area.

  The circularity is calculated by, for example, a mathematical expression “[4π × area] / (perimeter length) ^ 2”. The process for calculating the area may be the same as that for the size information. The process of calculating the perimeter is, for example, a process of counting the number of pixels included in the outer edge of the destruction area and a process of multiplying the number of pixels obtained thereby and a distance (unit distance) corresponding to the pixel pitch. Including. The circularity is calculated by substituting the area and perimeter obtained in this way into the above formula.

  Another example of circularity is ellipticity. The calculation of the ellipticity includes, for example, a process for obtaining an approximate ellipse of the fracture area and a process for obtaining the ellipticity of the approximate ellipse.

  The straightness is calculated by, for example, processing for obtaining a linear image representing the shape of the fracture area (thinning processing, processing for specifying a part of the outer edge, etc.) and the cumulative correlation coefficient of the linear image obtained thereby. And a process for obtaining. Alternatively, the linearity can be obtained based on the curvature of the linear image.

  The position information acquisition unit acquires position information of the destruction area. The position information may be arbitrary information indicating the position of the destruction area, and as an example, information indicating the position of the destruction area in the imaging range of the anterior segment (imaged anterior segment range) (that is, Pixel coordinates) and the relative position of the destruction area with respect to a predetermined part (corneal apex, pupil, pupil center, pupil center of gravity, iris, iris center, iris center of gravity, eyelid, etc.) such as the anterior eye segment.

  The process for obtaining the coordinate value of the pixel includes, for example, a process for specifying a feature point (center, center of gravity, upper end, lower end, left end, right end, etc.) of the destruction area and a process for obtaining the coordinate value of the pixel located at this feature point Including. Or the coordinate value of a pixel can also be calculated | required by the process which calculates the statistical value (average value, median value, etc.) of the coordinate of several pixels contained in a destruction area.

  The process for obtaining the relative position with respect to the predetermined part is, for example, a process for obtaining the coordinate value (reference coordinate value) of the predetermined part such as the anterior eye portion by analyzing the image and the coordinate value of the predetermined pixel included in the destruction region. Processing and processing for obtaining a difference between coordinate values of a predetermined pixel with respect to a reference coordinate value. Here, the process for obtaining the coordinate value of the predetermined pixel may be the same as the process for obtaining the coordinate value of the pixel, for example.

  The time information acquisition unit acquires time information of the destruction area. The time information may be any information that represents the elapsed time from the opening to the onset of destruction.

  In one example, the time information acquisition unit first identifies a blinking image (for example, an image in which no pupils, irises, etc. are depicted) among the time-series images. Next, the time information acquisition unit sets the last blink image or the next image in time series among the specified series of blink images as a reference image.

  Subsequently, the time information acquisition unit determines whether the destruction region is specified by the destruction region specification unit 43 for each image after the reference image (and before the next series of blink images). Alternatively, the time information acquisition unit determines whether or not the destruction region of a predetermined mode has been specified by the destruction region specification unit 43 for each image after the reference image (and before the next series of blink images). To do.

  Next, the time information acquisition unit starts from the time corresponding to the reference image (the time corresponding to the opening) from the time corresponding to the image in which the destruction area (in a predetermined mode) is specified in the previous step (for the destruction expression). Time) is calculated. This calculation process includes, for example, a process of multiplying the number of images from the reference image to the specific image by a predetermined image collection interval (scan repetition interval, reciprocal of frame rate, etc.).

  The evaluation processing unit 44 evaluates the type of dry eye of the eye to be examined based on the evaluation information acquired as described above. This evaluation method may be arbitrary. Although illustration is omitted, the evaluation processing unit 44 of this example further includes a score acquisition unit and a score synthesis unit.

  A score acquisition part calculates | requires the score according to each of evaluation information. For example, the score acquisition unit determines whether or not the evaluation information corresponds to an evaluation criterion included in the evaluation criterion information 21 illustrated in FIG. 2A. This determination process may include a comparison between a threshold value as an evaluation criterion and evaluation information (size information, shape information, position information, time information). In addition to this comparison process, or instead of this comparison process, a process for determining whether or not evaluation information is included in a range as an evaluation criterion may be executed.

  When the evaluation information includes size information, the score acquisition unit, for example, compares the size information with a threshold value or the like of the size of each destruction area pattern provided in the “size / shape” item of the evaluation reference information 21. Then, one or more destruction area patterns corresponding to this size information are specified. Further, the score acquisition unit gives a predetermined score (score) to each of one or more destruction region patterns (dry eye type) determined to correspond to the size information.

  When the evaluation information includes shape information, the score acquisition unit, for example, compares the shape information with a threshold value of the shape of each destruction region pattern provided in the “size / shape” item of the evaluation reference information 21. Then, one or more destruction area patterns to which the shape information corresponds are specified. Further, the score acquisition unit assigns a predetermined score to each of the one or more destructive region patterns determined to correspond to the shape information.

  When the evaluation information includes position information, the score acquisition unit, for example, compares this position information with the range of each destruction area pattern provided in the “position” item of the evaluation reference information 21, for example. One or more destruction area patterns corresponding to the above are specified. Further, the score acquisition unit assigns a predetermined score to each of the one or more destructive region patterns determined to correspond to this position information.

  When the evaluation information includes time information, the score acquisition unit, for example, compares this time information with the range of each destruction area pattern provided in the “elapsed time since opening” item of the evaluation reference information 21. Thus, one or more destructive area patterns corresponding to this time information are specified. Further, the score acquisition unit gives a predetermined score to each of the one or more destructive region patterns determined to correspond to this time information.

  The points given based on various evaluation information may be equal or different. As an example of the latter case, weighting can be performed for each evaluation item. Moreover, you may make it provide a different score according to the applicable degree (altitude, medium degree, low degree etc.) to evaluation criteria.

  When a score of 2 or more is acquired by the score acquisition unit, the score synthesis unit synthesizes these scores. The combination may be an arbitrary process, and for example, any one of addition, weighted addition, and statistical calculation (such as average calculation) is applied.

  The evaluation processing unit 44 evaluates the dry eye type (destructive region pattern) of the eye to be examined based on the result of synthesis by the score synthesis unit. For example, the evaluation processing unit 44 can select one or more types based on the size of the combined score obtained by the score combining unit. Typically, the type with the largest number of composite points is selected. Furthermore, a type having the second combination point can be selected. Or you may make it select the type whose composite score is more than a predetermined threshold value.

<Operation unit 50>
The operation unit 50 is used for a user to input an instruction to the ophthalmic examination apparatus 1. The operation unit 50 may include a known operation device used for an ophthalmologic apparatus or a computer. For example, the operation unit 50 may include a mouse, a touch pad, a trackball, a keyboard, a pen tablet, an operation panel, a joystick, a button, a switch, and the like. The operation unit 50 may include a touch panel. In this case, the control unit 10 can display a GUI for operating the ophthalmic examination apparatus 1 on the touch panel.

<Front image acquisition unit 60>
The front image acquisition unit 60 acquires a front image of the anterior segment (cornea or the like). The process for acquiring the front image is arbitrary. In the first example, the front image acquisition unit 60 may include a configuration for photographing the anterior segment. For example, the front image acquisition unit 60 may include an optical system of a slit lamp microscope, an optical system of a fundus camera, and the like.

  In the second example, the front image acquisition unit 60 may include a configuration for acquiring a front image of the anterior eye part of the subject eye from an external device. For example, the front image acquisition unit 60 may include a communication device for transmitting and receiving data via a communication line such as a LAN, the Internet, or a dedicated line. In this case, the front image acquisition unit 60 can acquire, for example, a front image of the anterior eye portion of the subject eye stored in an electronic medical record system or an image archiving system as a search query using a patient ID, a DICOM tag, or the like. it can.

  In the third example, the front image acquisition unit 60 can form a front image from the three-dimensional image collected by the OCT collection unit 30. Such front images include C-mode images, projection images, shadowgrams, and the like.

  Registration of the OCT image collected by the OCT collection unit 30 and the front image acquired by the front image acquisition unit 60 can be performed. Registration includes, for example, processing for detecting feature parts (corneal apex, pupil, pupil center, pupil center of gravity, iris, iris center, iris center of gravity, etc.) from both images, and using both feature parts as references. Through the alignment process.

  Similarly, it is possible to perform registration between various maps such as a tear thickness distribution map, a destruction region distribution map, and an evaluation result distribution map, and the front image acquired by the front image acquisition unit 60. This registration is performed using, for example, a registration result between the three-dimensional image that is the basis of the map and the front image.

<Operation>
Several examples of operations that an exemplary ophthalmic examination apparatus can perform are described. The flow of processing executed in this example is shown in FIG. It is assumed that preparatory processes such as input of a patient ID and the like, alignment of the optical system with respect to the eye to be examined, focus adjustment of the optical system, OCT optical path length adjustment, and setting of an OCT scan range have already been performed.

(S1: Perform 3D OCT scan of the anterior segment)
First, the OCT collection unit 30 collects a three-dimensional image representing tear fluid on the cornea by performing a three-dimensional OCT scan of the anterior segment of the eye to be examined. At this time, the OCT collection unit 30 may collect a three-dimensional image group (time-series image) representing the dynamics of tear fluid on the cornea by repeatedly performing a three-dimensional OCT scan.

  The display control unit 11 can display an image based on the collected three-dimensional image on the display device 2. The displayed image is an image obtained by applying desired rendering to a three-dimensional image, and may be a front image such as a projection image or a shadowgram, or a tomographic image such as a B-scan image, It may be a pseudo three-dimensional image such as a volume rendering image.

  When time-series images are collected, one or more three-dimensional images included therein are rendered, and the one or more rendered images obtained thereby can be displayed on the display device 2. When displaying a plurality of rendering images, these can be arranged in time series. It is also possible to display a plurality of rendered images by switching them in chronological order.

  In addition, when time-series images are collected, blink images can be identified from among a series of three-dimensional images constituting the time-series images. Furthermore, the last blink image in the series of blink images or the next image can be set as the image at the start of opening (the reference image described above).

(S2: Perform 3D image segmentation)
Next, the segmentation processing unit 41 applies a segmentation process to the three-dimensional image in order to identify the oil layer region and / or the liquid layer region in the three-dimensional image collected in step S1.

  Note that segmentation may be applied to a rendering image based on the three-dimensional image collected in step S1. In this case, the segmentation result for the rendered image can be used for the segmentation of the three-dimensional image.

  When time-series images are collected, the segmentation processing unit 41 can perform segmentation for specifying an oil layer region and / or a liquid layer region for each of a plurality of three-dimensional images included in the time-series image. .

(S3: Create tear thickness distribution information)
Subsequently, the distribution information acquisition unit 42 creates tear thickness distribution information based on the result obtained by the segmentation in step S2.

  When time-series images are collected, the distribution information acquisition unit 42 creates tear film thickness distribution information from the segmentation result for each of a plurality of three-dimensional images included in the time-series image. Thereby, a plurality of tear thickness distribution information corresponding to a plurality of three-dimensional images included in the time-series image is obtained. The plurality of tear thickness distribution information represents changes in tear thickness distribution over time, that is, tear fluid dynamics.

(S4: Acquire a front image of the anterior segment)
Next, the front image acquisition unit 60, for example, by photographing the anterior eye part, accessing an electronic medical record system or the like, or rendering the three-dimensional image collected in step S <b> 1, The front image of the part is acquired.

  The timing for acquiring the front image may be arbitrary. For example, the front image of the anterior eye part can be acquired by accessing an electronic medical chart system or the like before or after step S1 or by photographing the anterior eye part. Alternatively, the front image of the anterior eye part can be acquired by rendering the three-dimensional image collected in step S1 at an arbitrary timing after step S1.

(S5: A composite image of the tear thickness distribution image and the front image is displayed)
Subsequently, the display control unit 11 (and the data processing unit 40) forms an image (tear thickness distribution image) based on the tear thickness distribution information created in step S3. 4 is combined with the front image acquired in 4 and displayed on the display device 2. The tear thickness distribution image is, for example, a pseudo color map in which the thickness value of each point represented by the tear thickness distribution information is expressed in a pseudo color.

  In one example, the combined display of the tear thickness distribution image and the front image includes image processing for combining the tear thickness distribution image and the front image, and control for displaying the combined image formed thereby. In another example, the composite display includes control for displaying the tear thickness distribution image and the front image in an overlapping manner by using a layer display function or the like. A display image obtained by superimposing two (or more) images as described above is also an example of a composite image. In the composite display, the tear thickness distribution image and the front image can be registered. This registration is executed, for example, through registration of the three-dimensional image that is the basis of the tear thickness distribution image and the front image.

  When time-series images are collected, a composite image of a tear thickness distribution image and a front image based on one or more three-dimensional images included therein can be displayed on the display device 2. When a plurality of composite images are displayed, these can be arranged in time series. It is also possible to switch and display a plurality of composite images in time series.

(S6: Specify tear fluid destruction area)
Next, the destruction area specifying unit 43 specifies the tear destruction area based on the tear thickness distribution information created in step S3. Thereby, tear thickness distribution information is obtained.

  When time-series images are collected, the destruction area specifying unit 43 obtains a plurality of pieces of destruction area distribution information corresponding to the plurality of tear thickness distribution information. The plurality of pieces of destruction area distribution information represent changes in the distribution of destruction areas with time, that is, tear fluid dynamics.

(S7: A composite image of the destruction area distribution image and the front image is displayed)
Subsequently, the display control unit 11 (and the data processing unit 40) forms an image (destructive region distribution image) based on the destructive region distribution information created in step S6, and acquires this destructive region distribution image and step 4 The displayed front image is synthesized and displayed on the display device 2. The destruction area distribution image is, for example, an image in which the destruction area and other areas are expressed in different modes (for example, different pseudo colors).

  In one example, the combined display of the destruction region distribution image and the front image includes image processing for combining the destruction region distribution image and the front image, and control for displaying the combined image formed thereby. In another example, the composite display includes control for displaying the destruction region distribution image and the front image in a superimposed manner by using a layer display function or the like. A display image obtained by superimposing two (or more) images as described above is also an example of a composite image. In the composite display, registration of the destruction area distribution image and the front image can be performed. This registration is executed, for example, through registration of the three-dimensional image that is the basis of the destruction region distribution image and the front image.

  When the time-series images are collected, a composite image of the destruction region distribution image and the front image based on one or more three-dimensional images included therein can be displayed on the display device 2. When a plurality of composite images are displayed, these can be arranged in time series. It is also possible to switch and display a plurality of composite images in time series.

(S8: Evaluate dry eye type)
Next, the evaluation processing unit 44 acquires evaluation information based on the destruction area specified in step S6. In this example, size information, shape information, position information, and time information are acquired. An exemplary fracture region distribution image is shown in FIG. The destruction area distribution image D is expressed as a front image such as a projection image.

  Note that the time information is acquired, for example, when a time-series image is acquired or when the opening timing and the acquisition timing are recorded in the three-dimensional OCT scan in step S1. In the former case, for example, time information is acquired using a blink image included in a time-series image. In the latter case, for example, the time information is acquired by calculating the elapsed time from the recorded opening timing to the acquisition timing of the three-dimensional image.

  Further, the evaluation processing unit 44 refers to the evaluation criterion information 21 to obtain a score based on the evaluation information acquired in the previous process. In this example, the evaluation processing unit 44 obtains a score corresponding to the size information and shape information, a score corresponding to the position information, and a score corresponding to the time information.

  FIG. 5A to FIG. 5C show tables that represent setting values of points according to the evaluation information. The table shown in FIG. 5A represents the set value of the number of points according to the position information. The table shown in FIG. 5B represents setting values of points according to size information and shape information. The table shown in FIG. 5C represents a set value of points according to time information.

  When the destructive region shown in the destructive region distribution image D in FIG. 4 is obtained, for example, “wide range” is selected based on position information, and “parallel lines extending vertically” is selected based on size information and shape information, “Upward moving” is selected based on the time information.

  When two or more points are acquired as in this example, the evaluation processing unit 44 combines the two or more acquired points. For example, the evaluation processing unit 44 adds two or more acquired scores for each destruction area pattern.

  When the destruction area shown in the destruction area distribution image D of FIG. 4 is obtained, when “wide range”, “parallel line extending vertically” and “moving upward” are selected, these are defined in these three tables. By adding the points for each destruction area pattern, the combined result shown in FIG. 6 is obtained. Specifically, the “Area” type composite point “1”, the “Spot” type composite point “1”, the “Line” type composite point “3”, and the “Dimple” type composite point “2”. And “Random” type composite score “1”.

  The evaluation processing unit 44 selects the destruction area pattern (that is, the type of dry eye of the eye to be examined) represented by the three-dimensional image (time-series image) based on the composite score for each destruction area pattern obtained in this way. . When the composite score shown in FIG. 6 is obtained, for example, the “Line” type having the maximum composite score is selected. Alternatively, the “Line” type with 3 composite points and the “Dimple” type with 2 composite points are selected.

(S9: display the evaluation result)
The display control unit 11 displays the result of the evaluation performed in step S8 (destructive region pattern, dry eye type, etc.) on the display device 2.

  Moreover, the control part 10 can transmit an evaluation result to an external device, and can record it on a subject's electronic medical record. Further, the control unit 10 can store the three-dimensional image in the image archiving system, attach the evaluation result to the stored image, and embed the evaluation result in the stored image.

<Action and effect>
The operation and effect of an exemplary ophthalmic examination apparatus will be described.

  The ophthalmic examination apparatus (1) of the embodiment includes an OCT collection unit (30), a segmentation processing unit (41), and a distribution information acquisition unit (42). The OCT collection unit collects a three-dimensional image representing tear fluid on the cornea by scanning the anterior segment of the eye to be examined using optical coherence tomography (OCT). The segmentation processing unit specifies at least one of an oil layer region corresponding to the tear oil layer and a liquid layer region corresponding to the liquid layer by applying a segmentation process to the three-dimensional image. The distribution information acquisition unit acquires tear fluid thickness distribution information (tear fluid thickness distribution information) based on the result of processing by the segmentation processing unit.

  According to such an embodiment, the structure and dynamics of the tear film can be grasped using a high-resolution modality called OCT. Therefore, it is possible to perform the inspection with higher accuracy and higher accuracy than the conventional inspection using the fluorescence contrast image or the interference pattern.

  In the embodiment, the ophthalmic examination apparatus may further include a front image acquisition unit (60) and a display control unit (11). The front image acquisition unit can acquire a front image of the cornea. The display control unit can cause the display means (display device 2) to display a composite image of the tear thickness distribution image and the front image based on the distribution information acquired by the distribution information acquisition unit.

  According to such an embodiment, it is possible to easily grasp how tear fluid is distributed on the cornea.

  In the embodiment, the ophthalmic examination apparatus may further include a destruction area specifying unit (43). The destruction region specifying unit can specify the tear region of the tear based on the distribution information acquired by the distribution information acquisition unit.

  According to such an embodiment, the tear region of the tear film can be identified using a high-resolution modality called OCT. Therefore, it is possible to perform inspection with higher accuracy and higher accuracy than before.

  Furthermore, the ophthalmic examination apparatus according to the embodiment may further include a front image acquisition unit (60) and a display control unit (11). The front image acquisition unit can acquire a front image of the cornea. The display control unit can cause the display means (display device 2) to display a composite image of the destruction area distribution image representing the position of the destruction area specified by the destruction area specifying unit and the front image.

  According to such an embodiment, it is possible to easily grasp how the tear destruction region is distributed on the cornea.

  In the ophthalmic examination apparatus according to the embodiment, the OCT collection unit can collect a three-dimensional image group representing the dynamics of tears by repeatedly scanning the anterior segment using OCT. The segmentation processing unit can specify at least one of the oil layer region and the liquid layer region for each of the plurality of three-dimensional images included in the three-dimensional image group. The distribution information acquisition unit can acquire a plurality of distribution information corresponding to a plurality of three-dimensional images.

  According to such an embodiment, changes with time in the distribution of tears can be grasped.

  In the ophthalmic examination apparatus according to the embodiment, the OCT collection unit can collect a three-dimensional image group representing the dynamics of tears by repeatedly scanning the anterior segment using OCT. The segmentation processing unit can specify at least one of the oil layer region and the liquid layer region for each of the plurality of three-dimensional images included in the three-dimensional image group. The distribution information acquisition unit can acquire a plurality of distribution information corresponding to a plurality of three-dimensional images. Furthermore, the destructive region specifying unit can specify the destructive region for each of the plurality of distribution information.

  According to such an embodiment, it is possible to grasp the temporal change in the distribution of the tear fluid destruction region.

  The ophthalmic examination apparatus according to the embodiment may further include an evaluation processing unit (44). The evaluation processing unit can evaluate the type of dry eye of the eye to be examined based on the destructive region (destructive region distribution information, its change with time, etc.) specified by the destructive region specifying unit. In addition, the evaluation processing unit can evaluate the type of dry eye of the eye to be examined based on the distribution information acquired by the distribution information acquisition unit (tear fluid thickness distribution information, its change with time, etc.).

  According to such an embodiment, the type of dry eye can be evaluated using a high-resolution modality called OCT. Therefore, it is possible to perform inspection with higher accuracy and higher accuracy than before.

  In addition, the reliability of the inspection can be improved by performing the evaluation with reference to two or more of the plurality of pieces of evaluation information such as the size, shape, position, and expression time of the destruction region.

  The operations and effects of the embodiments are not limited to these, and the operations and effects provided by the respective items described as the embodiments and the operations and effects provided by a combination of a plurality of items should be considered.

Second Embodiment
Another exemplary embodiment of an ophthalmic examination apparatus will be described. In the present embodiment, an ophthalmic examination apparatus including a function (image reception unit) that receives a three-dimensional image of the anterior segment collected using OCT will be described. In addition, although illustration is abbreviate | omitted, the ophthalmic examination apparatus of this embodiment may be provided with the function (OCT collection part) which collects a three-dimensional image.

  The ophthalmic examination apparatus according to the present embodiment may include, for example, part or all of the ophthalmic examination apparatus according to the first embodiment. The configuration of an exemplary ophthalmic examination apparatus is shown in FIG. In addition, the same code | symbol is attached | subjected to the element similar to the ophthalmic examination apparatus 1 (FIG. 1) of the said embodiment, and the description is abbreviate | omitted unless it mentions especially.

  The ophthalmic examination apparatus 100 includes a control unit 10, a storage unit 20, a data processing unit 40, and an operation unit 50 similar to those of the ophthalmic examination apparatus 1. Each of these elements includes at least a part of the functions described in the above embodiment. Further, the ophthalmic examination apparatus 100 includes an image receiving unit 70. The ophthalmic examination apparatus 100 may not include the OCT collection unit 30. The ophthalmic examination apparatus 100 may include a front image acquisition unit 60.

  The image receiving unit 70 receives a three-dimensional image (which may be a time-series image) representing tear fluid on the cornea collected by scanning the anterior segment of the eye to be examined using OCT. The image receiving unit 70 may include, for example, a communication device for transmitting and receiving data via a communication line such as a LAN, the Internet, or a dedicated line. The image receiving unit 70 may include a data reader for reading data from the recording medium.

  The image receiving unit 70 or the control unit 10 can execute a process for acquiring, for example, a patient ID, a DICOM tag, or the like as a search query for a three-dimensional image stored in an electronic medical record system or an image archiving system. .

  The segmentation processing unit 41 applies at least one of the oil layer region corresponding to the tear oil layer and the liquid layer region corresponding to the liquid layer by applying the segmentation process to the three-dimensional image received by the image receiving unit 70. Can be identified.

  The distribution information acquisition unit 42 can acquire tear thickness distribution information based on the processing result of the segmentation processing unit.

  The destruction area specifying unit 43 can specify the destruction area of tears based on the distribution information acquired by the distribution information acquisition unit 42.

  The evaluation processing unit 44 can evaluate the type of dry eye of the eye to be inspected based on the destruction area specified by the destruction area specifying unit 43. Further, the evaluation processing unit 44 can evaluate the type of dry eye of the eye to be examined based on the distribution information acquired by the distribution information acquisition unit 42.

  The display control unit 11 can cause the display device 2 to display a composite image of the tear thickness distribution image based on the distribution information acquired by the distribution information acquisition unit 42 and the front image of the anterior segment of the eye to be examined. . Here, the front image is an image taken by the ophthalmic examination apparatus 100 or an external apparatus.

  Further, the display control unit 11 causes the display device 2 to display a composite image of the destruction region distribution image representing the position of the destruction region specified by the destruction region specification unit 43 and the front image of the anterior eye portion of the eye to be examined. be able to. This front image is also an image taken by the ophthalmic examination apparatus 100 or an external apparatus.

  When the image receiving unit 70 receives a three-dimensional image group representing the dynamics of tears collected by repeatedly scanning the anterior segment using OCT, the ophthalmic examination apparatus 100 executes, for example, the following process: can do. First, the segmentation processing unit 41 can specify at least one of an oil layer region and a liquid layer region for each of a plurality of three-dimensional images included in the three-dimensional image group. The distribution information acquisition unit can acquire a plurality of distribution information corresponding to a plurality of three-dimensional images.

  Furthermore, the destruction area specifying unit 43 can specify the destruction area for each of the acquired plurality of distribution information. In addition, the evaluation processing unit 44 can evaluate the type of dry eye of the eye to be examined based on a plurality of destruction area specifying results (destruction area distribution information) corresponding to a plurality of three-dimensional images.

  The ophthalmic examination apparatus 100 can execute part or all of the processes that can be executed by the ophthalmic examination apparatus 1 (see the first embodiment).

  According to such an ophthalmic examination apparatus 100, it is possible to grasp the structure and dynamics of the tear film from a three-dimensional image collected using a high-resolution modality called OCT. Therefore, it is possible to perform the inspection with higher accuracy and higher accuracy than the conventional inspection using the fluorescence contrast image or the interference pattern.

<Modification>
The configuration described above is merely an example for favorably implementing the present invention. Therefore, arbitrary modifications (omitted, replacement, addition, etc.) within the scope of the present invention can be made as appropriate.

  For example, in an embodiment having an OCT function (OCT collection unit 30 or the like) like the ophthalmic examination apparatus 1, a three-dimensional OCT scan of the anterior eye part is started in response to eye opening or blinking of the eye to be examined. Can be configured.

  Detection of eyelids or blinks is performed by, for example, an anterior segment imaging unit such as the front image acquisition unit 60 and a processor that analyzes the anterior segment image acquired thereby to determine the blink state / open state ( Data processing unit 40 and the like).

  Alternatively, a projection unit that projects a light beam from the first direction onto the cornea, a light receiving unit that receives corneal reflected light of the light beam in the second direction, and a blink state / open state based on a light reception state of the cornea by the light receiving unit And a processor (such as the control unit 10 or the data processing unit 40).

  The control processor (control unit 10 or the like) controls the OCT collection unit according to the blink state / open state obtained by such a method. In the first example, when a transition from the blink state to the open state is detected, the control processor may start the three-dimensional OCT scan and perform the three-dimensional OCT scan for a predetermined time or a predetermined number of repetitions. it can.

  In the second example, when the transition from the open state to the blink state or when the transition to the blink state has occurred for a predetermined time, the control processor starts a three-dimensional OCT scan for a predetermined time or A three-dimensional OCT scan can be performed a predetermined number of iterations.

  In the third example, the control processor starts a repetitive three-dimensional OCT scan, and then when the transition from the blink state to the open state is detected, the transition from the open state to the blink state Alternatively, when a predetermined time elapses after shifting to the blink state, it is possible to start capturing a three-dimensional data set repeatedly collected by OCT or start data processing.

  In the embodiment including the OCT function (OCT collection unit 30 and the like) and the anterior eye imaging function (front image acquisition unit 60 and the like) like the ophthalmic examination apparatus 1, the following configuration can be applied.

  First, the control processor (the control unit 10 or the like) acquires (repeatedly) an anterior segment image. An analysis processor (data processing unit 40 or the like) evaluates the state and dynamics of tears by analyzing the acquired front images (sequentially). The control processor executes a three-dimensional OCT scan based on the evaluation result.

  For example, by analyzing the front image, the analysis processor analyzes the position where the tear fluid is characteristic (the position of the destruction area, the position of the characteristic destruction area, the position where destruction is rapidly progressing, Can be specified. The control processor can set a scan range so as to include the specified position, and can execute a three-dimensional OCT scan on the scan range.

  When the position where the state of tears is characteristic changes with time, the control processor can repeatedly execute the setting of the scan range and the three-dimensional OCT scan according to the change of the position.

  In the embodiment, the ophthalmic examination apparatus can acquire the corneal surface shape of the eye to be examined. The acquisition of the corneal surface shape can be acquired by an inspection method such as a keratometer or a corneal topographer. The ophthalmic examination apparatus may have such an examination function. Alternatively, the ophthalmic examination apparatus may have a function of acquiring past examination results from an external device such as an electronic medical record system or a recording medium.

  The corneal surface shape information acquired in this way includes a curvature (curvature radius) in a predetermined position and direction, and typically includes a curvature distribution (curvature radius distribution).

  A processor (data processing unit 40 or the like) can set the measurement direction at each measurement point of tear thickness based on such corneal surface shape information. At this time, the normal direction at each position on the corneal surface can be set as the measurement direction.

  Further, the processor (data processing unit 40 or the like) can correct the tear thickness distribution information acquired without reflecting the corneal surface shape using the corneal surface shape information.

  Further, the control processor 40 sets the OCT optical system based on the corneal surface shape information and the scan range acquired in advance so that the OCT measurement light is projected as vertically as possible onto the corneal surface in the scan range. It is possible to control or move the OCT optical system (such as turning).

DESCRIPTION OF SYMBOLS 1,100 Ophthalmic examination apparatus 2 Display device 10 Control part 11 Display control part 20 Storage part 21 Evaluation criteria information 30 OCT collection part 40 Data processing part 41 Segmentation processing part 42 Distribution information acquisition part 43 Destruction area specification part 44 Evaluation processing part 50 Operation unit 60 Front image acquisition unit 70 Image reception unit

Claims (7)

An OCT collection unit that collects a three-dimensional image representing tear fluid on the cornea by scanning the anterior segment of the eye to be examined using optical coherence tomography (OCT);
By applying a segmentation process to the three-dimensional image, a segmentation processing unit that identifies at least one of an oil layer region corresponding to the oil layer of the tear fluid and a liquid layer region corresponding to the liquid layer;
An ophthalmologic examination apparatus comprising: a distribution information acquisition unit that acquires distribution information of the tear thickness based on a result of processing by the segmentation processing unit. A front image acquisition unit for acquiring a front image of the cornea;
The display control unit according to claim 1, further comprising: a display control unit configured to display a composite image of a tear thickness distribution image based on the distribution information acquired by the distribution information acquisition unit and the front image on a display unit. Ophthalmic examination device. The ophthalmic examination apparatus according to claim 1, further comprising: a destruction region specifying unit that specifies a destruction region of the tear based on the distribution information acquired by the distribution information acquisition unit. A front image acquisition unit for acquiring a front image of the cornea;
The display control part which displays a synthetic | combination image of the destruction area distribution image showing the position of the destruction area specified by the destruction area specification part and the front image on a display means. Ophthalmic examination equipment. The OCT collection unit collects a three-dimensional image group representing the dynamics of the tear fluid by repeatedly scanning the anterior segment using OCT,
The segmentation processing unit executes at least one of the oil layer region and the liquid layer region for each of a plurality of three-dimensional images included in the three-dimensional image group,
The ophthalmic examination apparatus according to claim 1, wherein the distribution information acquisition unit acquires a plurality of the distribution information corresponding to the plurality of three-dimensional images. The OCT collection unit collects a three-dimensional image group representing the dynamics of the tear fluid by repeatedly scanning the anterior segment using OCT,
The segmentation processing unit executes at least one of the oil layer region and the liquid layer region for each of a plurality of three-dimensional images included in the three-dimensional image group,
The distribution information acquisition unit acquires a plurality of the distribution information corresponding to the plurality of three-dimensional images,
The ophthalmic examination apparatus according to claim 3 or 4, wherein the destructive region specifying unit specifies the destructive region for each of the plurality of distribution information. A reception unit that receives a three-dimensional image representing tear fluid on the cornea collected by scanning the anterior segment of the eye to be examined using optical coherence tomography (OCT);
By applying a segmentation process to the three-dimensional image, a segmentation processing unit that identifies at least one of an oil layer region corresponding to the oil layer of the tear fluid and a liquid layer region corresponding to the liquid layer;
An ophthalmologic examination apparatus comprising: a distribution information acquisition unit that acquires distribution information of the tear thickness based on a result of processing by the segmentation processing unit.