JP7111874B2 - ophthalmic imaging equipment - Google Patents

Description

Embodiments relate to an ophthalmic imaging apparatus.

Image diagnosis occupies an important position in the field of ophthalmology. In recent years, the utilization of optical coherence tomography (OCT) is progressing. OCT has come to be used not only for acquiring B-scan images and three-dimensional images of an eye to be inspected, but also for acquiring front images (en-face images) such as C-scan images and shadowgrams.

Furthermore, acquisition of an image in which a specific portion of the subject's eye is emphasized and acquisition of functional information are also performed. For example, based on time-series data collected by OCT, a B-scan image or a frontal image (called a blood vessel-enhanced image, angiogram, etc.) in which fundus blood vessels are emphasized can be constructed. This technique is called OCT angiography or the like. In addition, information on blood flow can be obtained based on phase information of time-series data collected by OCT. This technique is called OCT blood flow measurement or the like.

Further, the presence or absence and degree of disease are judged by comparing data of an eye to be examined obtained using OCT with standard data. For example, there is known a technique for comparing the retinal thickness of a subject's eye obtained by fundus OCT with a standard value of the retinal thickness of a healthy eye. However, with conventional techniques, it is difficult to suitably compare data of the subject's eye obtained by OCT blood flow measurement with standard data.

Japanese translation of PCT publication No. 2015-515894 JP 2013-184018 A JP 2011-24930 A

An object of the embodiments is to provide a technique for suitably comparing fundus blood flow data of an eye to be examined obtained by OCT blood flow measurement with standard data.

A first aspect of the embodiment is a storage unit that stores pre-created standard data of fundus blood flow dynamics, and acquires data by applying optical coherence tomography (OCT) blood flow measurement to the fundus of the eye to be examined. a data acquisition unit and a display processing unit for displaying information on a display unit, wherein the display processing unit performs time-series changes in blood flow in the blood vessels of the fundus based on the data acquired by the data acquisition unit. and standard information based on the standard data is displayed in parallel with the blood flow graph, and the storage unit stores pre-created standard data of fundus blood flow dynamics in a healthy eye. a first specification unit that stores certain first standard data and specifies a portion that differs from the first standard data in the data acquired by the data acquisition unit; The ophthalmologic imaging apparatus displays a portion of the blood flow graph corresponding to the portion specified by in a manner different from other portions.

A second aspect of the embodiment includes a storage unit storing pre-created standard data of fundus blood flow dynamics, and applying optical coherence tomography (OCT) blood flow measurement to the fundus of the subject's eye to obtain data. a data acquisition unit and a display processing unit for displaying information on a display unit, wherein the display processing unit performs time-series changes in blood flow in the blood vessels of the fundus based on the data acquired by the data acquisition unit. and standard information based on the standard data is displayed in parallel with the blood flow graph, and the storage unit stores pre-created standard data of fundus blood flow dynamics in the affected eye. a second specifying unit that stores certain second standard data and specifies a portion that matches the second standard data in the data acquired by the data acquiring unit; The ophthalmologic imaging apparatus displays a portion of the blood flow graph corresponding to the portion specified by in a manner different from other portions.

According to the embodiment, it is possible to suitably compare the fundus blood flow data of the subject's eye obtained by OCT blood flow measurement with the standard data.

1 is a schematic diagram illustrating an example configuration of an ophthalmic imaging apparatus according to an exemplary embodiment; FIG. FIG. 4 is a schematic diagram for explaining an example of processing executed by an ophthalmologic imaging apparatus according to an exemplary embodiment; 4 is a flow chart representing an example of the operation of an ophthalmic imaging apparatus according to an exemplary embodiment; FIG. 4 is a schematic diagram for explaining an example of processing executed by an ophthalmologic imaging apparatus according to an exemplary embodiment; FIG. 4 is a schematic diagram for explaining an example of processing executed by an ophthalmologic imaging apparatus according to an exemplary embodiment; 4 is a flow chart representing an example of the operation of an ophthalmic imaging apparatus according to an exemplary embodiment; FIG. 4 is a schematic diagram for explaining an example of processing executed by an ophthalmologic imaging apparatus according to an exemplary embodiment; FIG. 4 is a schematic diagram for explaining an example of processing executed by an ophthalmologic imaging apparatus according to an exemplary embodiment; 1 is a schematic diagram showing an example of the configuration of an ophthalmologic information processing apparatus according to an exemplary embodiment; FIG.

Exemplary embodiments of the invention will be described with reference to the drawings. It should be noted that any known technology, including the disclosures of documents cited in this specification, can be combined with the embodiments.

An ophthalmologic imaging apparatus and an ophthalmologic information processing apparatus according to an embodiment have a function of displaying various information based on data obtained by applying OCT to the fundus of an eye to be examined. An ophthalmologic imaging apparatus according to an embodiment acquires data by applying OCT blood flow measurement to the fundus of an eye to be examined, and displays various information based on this data. On the other hand, the ophthalmologic information processing apparatus according to the embodiment receives data obtained by applying OCT blood flow measurement to the fundus of the eye to be examined by a separately provided OCT apparatus, and displays various information based on the data. to run. In particular, the ophthalmologic imaging apparatus and the ophthalmologic information processing apparatus according to the embodiment allow the user to check the similarity or difference between the standard data of the fundus blood flow dynamics created in advance and the data of the subject's eye obtained by OCT blood flow measurement. Display information to understand.

The data obtained by applying OCT to the fundus of the subject's eye (fundus OCT data) may be data in any form. For example, the fundus OCT data may include any one or more of the following (1) to (5).
(1) Data collected by OCT scanning of the fundus (raw data)
(2) Image data obtained by processing raw data (3) Intermediate data obtained during a series of processes for generating image data from raw data (4) Obtained by processing raw data Blood flow data (5) Intermediate data obtained during a series of processes for generating blood flow data from raw data

Note that the types of fundus OCT data are not limited to these. Embodiments can also process a variety of information associated with fundus OCT data. Examples of such information include subject identification information, subject eye identification information, identification information indicating whether the subject eye is the left eye or the right eye, photographing date and time, photographing conditions, and the like.

An ophthalmologic imaging apparatus and an ophthalmologic information processing apparatus according to an embodiment include a processor that executes data display processing. The ophthalmologic information processing apparatus according to the embodiment may further include a processor that processes raw data and intermediate data. The ophthalmologic imaging apparatus according to the embodiment further includes an optical system, drive system, control system, and data processing system for performing OCT.

An ophthalmologic imaging apparatus according to an embodiment is configured to be able to perform Fourier domain OCT, for example. Fourier-domain OCT includes spectral-domain OCT and swept-source OCT. Spectral domain OCT is a method of constructing an image by acquiring a spectrum of interference light by spatial division using a broadband low-coherence light source and a spectroscope and performing a Fourier transform on it. Swept source OCT uses a wavelength swept light source (tunable light source) and a photodetector (balanced photodiode, etc.) to acquire the spectrum of interference light in a time-division manner, and constructs an image by Fourier transforming it. It is a method to The OCT method is not limited to Fourier domain OCT, and may be time domain OCT or amphasic OCT.

The ophthalmologic imaging apparatus and ophthalmologic information processing apparatus according to the embodiments may include modalities (for example, modalities other than OCT) for imaging the eye and/or other parts. Typical examples include fundus cameras, scanning laser ophthalmoscopes (SLO), slit lamp microscopes, and ophthalmic surgical microscopes. Further, the ophthalmologic imaging apparatus and the ophthalmologic information processing 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.

Data processing functions (arithmetic functions, image processing functions, control functions, etc.) in the ophthalmic photographing apparatus and ophthalmic information processing apparatus according to the embodiments include, for example, hardware such as processors and storage devices, arithmetic programs, image processing programs, and control functions. It is realized by cooperating with software such as a program. Part of the hardware may be provided in an external device capable of communicating with the ophthalmologic information processing apparatus or ophthalmologic imaging apparatus according to the embodiment. Also, at least part of the software may be pre-stored in the ophthalmologic information processing apparatus or ophthalmic imaging apparatus according to the embodiment, and/or may be pre-stored in an external device.

〈Ophthalmic imaging device〉
<Constitution>
An ophthalmic imaging apparatus according to an exemplary embodiment is described. FIG. 1 shows a configuration example of an ophthalmologic imaging apparatus according to this embodiment. The ophthalmologic imaging apparatus 1 can collect fundus data using OCT, generate a fundus morphological image and fundus blood flow data based on the collected data, and display various information based on these.

Here, the fundus morphology image is an image representing the morphology of the fundus. In the present embodiment, the fundus morphological image is an image in which at least fundus blood vessels (retinal blood vessels, choroidal blood vessels, etc.) are expressed in a visually identifiable manner. Examples of fundus morphological images include B-scan images, C-scan images, projection images, shadowgrams, phase images, and blood vessel-enhanced images. The fundus blood flow data is data representing the blood flow state (blood flow dynamics) in the fundus blood vessels. Examples of fundus blood flow data include direction of blood flow, blood flow velocity, time-series change in blood flow velocity, blood flow, blood flow per unit time, time-series change in blood flow per unit time, and total blood flow. .

In this embodiment, both morphological images and blood flow data are formed based on data obtained by applying OCT blood flow measurement to the fundus. Note that an OCT scan (for example, a B scan, a three-dimensional scan) for acquiring a morphological image and an OCT scan (OCT blood flow measurement) for acquiring blood flow data may be performed separately. . Also, an OCT scan may be performed to acquire data other than these. For example, OCT angiography can be performed.

Part of the data used to display information may be acquired by another device. For example, one of the fundus morphological image and the fundus blood flow data may be acquired by another device. Alternatively, other devices may perform OCT angiography to obtain vessel-enhanced images. Data acquired by another device is input to the ophthalmologic imaging device according to the embodiment.

The ophthalmologic imaging apparatus 1 can display various types of information such as fundus morphological images, blood flow information, and blood vessel enhanced images on the display device 2 . In particular, the ophthalmologic imaging apparatus 1 can display information based on blood flow information of the fundus of the subject's eye and standard data on blood flow dynamics. For example, the ophthalmologic imaging apparatus 1 can display a graph (blood flow graph) representing the blood flow state of the fundus of the subject's eye and information based on standard data (standard information) side by side.

The standard information may be, for example, a graph (standard blood flow graph) in the same manner as the blood flow graph. Also, the standard information may be statistical values based on standard data. This statistical value may be included in the standard data, or may be a value obtained by statistically processing the standard data.

The display device 2 may be a part of the ophthalmologic imaging apparatus 1 or may be an external device connected to the ophthalmologic imaging apparatus 1 . Further, the ophthalmologic photographing apparatus 1 can send various information to a computer, a storage device, an ophthalmologic apparatus, and the like.

The ophthalmologic imaging apparatus 1 includes a control section 10 , a storage section 20 , a data acquisition section 30 , an operation section 50 and a front image acquisition section 60 . Control unit 10 includes scan control unit 11 , partial data identification unit 12 , and display control unit 13 . The data acquisition unit 30 includes an OCT scanner 31 , an image formation unit 32 and a blood flow data generation unit 33 .

<Control unit 10>
The control unit 10 controls each unit of the ophthalmologic imaging apparatus 1 . Control unit 10 includes a processor. 「プロセッサ」は、例えば、ＣＰＵ（Ｃｅｎｔｒａｌ Ｐｒｏｃｅｓｓｉｎｇ Ｕｎｉｔ）、ＧＰＵ（Ｇｒａｐｈｉｃｓ Ｐｒｏｃｅｓｓｉｎｇ Ｕｎｉｔ）、ＡＳＩＣ（Ａｐｐｌｉｃａｔｉｏｎ Ｓｐｅｃｉｆｉｃ Ｉｎｔｅｇｒａｔｅｄ Ｃｉｒｃｕｉｔ）、プログラマブル論理デバイス（例えば、ＳＰＬＤ（Ｓｉｍｐｌｅ Ｐｒｏｇｒａｍｍａｂｌｅ Ｌｏｇｉｃ Ｄｅｖｉｃｅ）、ＣＰＬＤ（Ｃｏｍｐｌｅｘ Ｐｒｏｇｒａｍｍａｂｌｅ Ｌｏｇｉｃ Ｄｅｖｉｃｅ） , FPGA (Field Programmable Gate Array)). The control unit 10 can realize the functions according to the embodiment by, for example, reading and executing a program stored in a memory circuit or a memory device (the memory unit 20, an external device, etc.).

Also, the control unit 10 may include a communication device for transmitting and receiving data via a communication line such as a local area network (LAN), the Internet, or a dedicated line.

<Scan control unit 11>
The scan controller 11 controls the OCT scanner 31 . For example, the scan control unit 11 controls the OCT scanner 31 to control the light source, control the optical scanner, change the optical path length of the measurement light and/or the reference light, adjust the polarization, adjust the amount of light, adjust the focus, and change the fixation position. Controls the various elements it contains. Some examples of processing that can be executed by the scan control unit 11 will be described later.

<Partial data identification unit 12>
The partial data specifying unit 12 compares the blood flow data (or blood flow information based thereon) of the fundus of the eye to be examined with the standard data (or standard information based thereon), and determines this blood flow data (or this blood flow data). to identify the part of interest in the stream information).

In a typical example, standard data of fundus hemodynamics in healthy eyes are used. In this case, the partial data specifying unit 12 can specify a portion of the fundus blood flow data of the subject's eye that differs from the standard data (or standard information based thereon) as a target portion.

The portion of interest in this case corresponds to a portion in the fundus blood flow data of the subject's eye that deviates from the fundus blood flow dynamics of a healthy eye. In other words, an abnormal portion (for example, a portion presumed to be a sign or influence of a disease) is identified in the fundus blood flow data of the subject's eye.

In addition, two or more standard data regarding healthy eyes can be provided. For example, it is possible to provide two or more pieces of standard data corresponding to items such as gender, age group, physique (height, weight, degree of body mass index (BMI), etc.), medical history, and the like.

In another typical example, standard data of fundus hemodynamics in the diseased eye are used. This standard data may relate to a particular disease (eg, glaucoma, age-related macular degeneration, retinal artery occlusion, retinal vein occlusion, diabetic retinopathy, etc.). Also, for a single disease, it is possible to have two or more normative data corresponding to its severity (eg early, mild, moderate, severe).

When the standard data for the affected eye is used, the partial data identifying unit 12 identifies a portion of the fundus blood flow data of the subject's eye that matches the standard data (or standard information based thereon) as a target portion.

The portion of interest in this case corresponds to a portion of the fundus blood flow data of the subject's eye that matches (or resembles) the fundus blood flow dynamics of the patient's eye. In other words, an abnormal portion (for example, a portion presumed to be a sign or influence of a particular disease) is identified in the fundus blood flow data of the subject's eye.

A specific example of such processing executed by the partial data specifying unit 12 will be described later.

<Display control unit 13>
The display control unit 13 executes control for displaying information on the display device 2 . The display control unit 13 can perform display control based on data stored in the storage unit 20 .

The display control unit 13 can perform processing (generation, processing, synthesis, etc.) related to information displayed on the display device 2 . Such processing may be executed by cooperation between the display control unit 13 and other elements (other elements of the control unit 10, the data acquisition unit 30, etc.).

<Storage unit 20>
Various data are stored in the storage unit 20 . In this example, standard data 21 and OCT data 22 are stored in the storage unit 20 . At least part of the standard data 21 and/or at least part of the OCT data 22 may be stored in an external storage device and provided to the ophthalmologic imaging apparatus 1 upon request. The storage unit 20 includes, for example, storage devices such as a hard disk drive and a semiconductor memory.

<Standard data 21>
The standard data 21 are standard data for arbitrary parameters representing fundus hemodynamics. This parameter may be any parameter obtained by processing data acquired by OCT blood flow measurement. Examples thereof include blood flow velocity, time-series change in blood flow velocity, blood flow, blood flow per unit time, time-series change in blood flow per unit time, and total blood flow.

Creation of the standard data 21 is performed by, for example, collecting data by applying OCT blood flow measurement to a large number of samples (that is, fundus of a large number of eyes to be examined) and statistically processing them. . At this time, the sample may be, for example, a group of healthy eyes, a group of healthy eyes described above for each item, a group of diseased eyes, or a group of specific diseases described above.

Statistical values obtained by statistical processing for creating the standard data 21 include, for example, mean, median, mode, quantile, maximum, minimum, midpoint, standard deviation, variance, standard There are errors.

The standard data 21 are not limited to those created by such statistical processing. For example, the standard data 21 may include data for a subject eye exhibiting standard fundus hemodynamics. Typically, the standard data 21 are data acquired by applying OCT blood flow measurement to the fundus of an eye to be examined that has been diagnosed as a healthy eye, or data obtained from the fundus of an eye to be examined that has been diagnosed as a diseased eye. Data acquired by applying OCT blood flow measurement, data acquired by applying OCT blood flow measurement to the fundus of an eye to be examined that has been diagnosed as having a specific disease, and any of these data are processed. may include data obtained by As another example, the standard data 21 may include data described in articles and books.

<OCT data 22>
The OCT data 22 includes any one or more of the fundus OCT data (1) to (5) described above. Typically, the ophthalmologic imaging apparatus 1 generates a morphological image and blood flow data from raw data collected by OCT scanning of the fundus (including at least OCT blood flow measurement), and stores OCT data 22 including these. Store in section 20 . In other words, in a typical example, the OCT data 22 includes the aforementioned fundus OCT data (2) and (4).

<Data acquisition unit 30>
The data acquisition unit 30 acquires data (for example, at least part of the OCT data 22 stored in the storage unit 20) by applying OCT to the fundus of the subject's eye. As described above, the data acquisition unit 30 includes the OCT scanner 31, the image formation unit 32, and the blood flow data generation unit 33. Image forming unit 32 includes a processor that executes an image forming program. The blood flow data generator 33 includes a processor that executes a blood flow data generation program.

<OCT scanner 31>
The OCT scanner 31 performs an OCT scan of the fundus under the control of the scan controller 11 . Thereby, fundus data (raw data) is collected. The OCT scanner 31 includes a configuration for performing optical interferometry using, for example, spectral domain OCT or swept source OCT. Such an OCT scanner 31 includes an OCT optical system, a driving system, a data acquisition system (DAQ), a control system, etc., as in the conventional art.

The OCT 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 fundus, and superimposes the return light of the measurement light from the fundus on the reference light to generate interference light. do. The optical scanner includes a galvanometer scanner or the like, and deflects measurement light. Thereby, the projection position of the measurement light with respect to the fundus is moved. The photodetector detects (the spectrum of) the interference light generated by the interference optics.

The drive system moves or operates the elements included in the OCT optical system. A data collection system collects detection results obtained sequentially by the OCT optics. The control system controls the OCT optical system, drive system, data acquisition system, etc. under the control of the scan controller 11 (or other elements of the controller 10).

In OCT blood flow measurement, the OCT scanner 31 repeatedly scans a cross section that intersects the blood vessel at a preset measurement position to collect data. In other words, the OCT scanner 31 acquires data by repeatedly scanning a section of interest that intersects the blood vessel of interest. The scan mode at this time is, for example, line scan (B scan). This line scan is, for example, repeatedly executed at a predetermined frequency. Data collected by such repeated scanning is sent to the image forming section 32 .

In the OCT blood flow measurement, the OCT scanner 31 also scans to obtain the inclination angle of the target blood vessel in the target cross section. This scan is performed, for example, on two cross-sections that intersect the vessel of interest. Here, two cross-sections can be placed near the cross-section of interest.

Note that one of the two cross sections for obtaining the inclination angle of the target blood vessel may be the target cross section itself. The other cross section is set near the cross section of interest. In this case, data obtained by repeated scanning of the cross section of interest can be used to calculate the tilt angle.

In summary, typically, the scans performed in OCT blood flow measurement may be a combination of repeated scans of the cross section of interest and scans of two other cross sections, or repeated scans of the cross section of interest and one other cross section. may be combined with the scan of

The mode of scanning for obtaining the inclination angle of the target blood vessel in the target cross section is not limited to these. For example, three or more cross-sections can be scanned. Alternatively, a three-dimensional area containing the section of interest can be scanned (three-dimensional scan). As another example, a cross-section that intersects the cross-section of interest and along the vessel of interest can be scanned. The OCT blood flow measurement will be described in detail in the explanation of the blood flow data generator 33. FIG.

When performing OCT angiography, the OCT scanner 31 scans a three-dimensional area of the fundus. The scan mode at this time is, for example, raster scan (three-dimensional scan). This raster scan is performed, for example, by scanning each of the plurality of B cross-sections (B scan planes) a predetermined number of times (for example, four times each). In other words, this raster scanning is performed so as to sequentially scan a plurality of B slices a predetermined number of times or to scan according to a predetermined sequence. A three-dimensional data set collected by the OCT scanner 31 is sent to the image forming section 32 .

The manner of scanning that can be performed by the OCT scanner 31 is not limited to the manner described above. For example, the OCT scanner 31 can perform line scans, circle scans, radial scans, three-dimensional scans, etc. as OCT scans for obtaining morphological images.

<Image forming unit 32>
The image forming unit 32 forms an OCT image based on data collected by the OCT scanner 31 . For example, in OCT blood flow measurement, the image forming unit 32 forms a plurality of cross-sectional images (B-scan images) for each B cross-section based on a three-dimensional data set acquired by the OCT scanner 31 . The image formation processing at this time includes, for example, noise removal (noise reduction), filtering, fast Fourier transform (FFT), etc., as in the conventional OCT technology.

The image forming unit 32 can construct stack data by embedding these cross-sectional images in a single three-dimensional coordinate system. In this stack data, a number of cross-sectional images corresponding to the number of scanning repetitions is assigned to each B cross-section. Furthermore, the image forming unit 32 can form volume data (voxel data) by performing interpolation processing or the like on this stack data. In this volume data, a number of voxel groups corresponding to the number of scanning repetitions are assigned to positions corresponding to each B section.

The image forming unit 32 renders stack data or volume data to produce B-scan images (longitudinal cross-sectional images, axial cross-sectional images), C-scan images (transverse cross-sectional images, horizontal cross-sectional images), projection images, shadowgrams, and so on. etc. can be formed.

An arbitrary cross-sectional image, such as a B-scan image or a C-scan image, is formed by selecting pixels (pixels, voxels) on a specified cross-section from a three-dimensional data set. Alternatively, an image of an arbitrary cross-section is formed by projecting a slice of preset thickness in its thickness direction.

A projection image is formed by projecting stack data or volume data in a predetermined direction (Z direction, depth direction, A scan direction). A shadowgram is formed by projecting a portion of stack data or volume data (for example, partial data corresponding to a specific layer) in a predetermined direction. A fundus image such as a C-scan image, a projection image, and a shadowgram whose viewpoint is the cornea side of the subject's eye is called a front image.

The image forming unit 32 can perform various image processing other than rendering. For example, there are segmentation for obtaining specific tissues and tissue boundaries, and size analysis for obtaining sizes of tissues (layer thickness, volume, etc.). If a particular layer (or a particular layer boundary) is determined by segmentation, it is possible to reconstruct the B-scan or frontal image so that the particular layer is flat. Such an image is called a flattened image.

The image forming unit 32 can form a blood vessel enhanced image. A blood vessel-enhanced image is an image obtained by specifying an image region (blood vessel region) corresponding to a blood vessel by analyzing OCT data and enhancing the blood vessel region by changing the expression mode of the blood vessel region. A plurality of OCT data obtained by repeatedly scanning substantially the same range of the subject's eye is used to identify the blood vessel region.

A blood vessel-enhanced image expresses, for example, the distribution of blood vessels in a three-dimensional region of the fundus that has been OCT-scanned (that is, the three-dimensional distribution of blood vessels). There are several types of techniques for forming a blood vessel-enhanced image. A typical method for that purpose will be described. For this processing, a three-dimensional data set including a plurality of B-scan images arranged in time series for each B-section is used by repeatedly scanning each of the plurality of B-sections of the subject's eye. As a technique for repeatedly scanning substantially the same B section, there are fixation and tracking.

In the process of forming a blood vessel-enhanced image, registration of a plurality of B-scan images is first performed for each B-section. This alignment is performed using, for example, a known image matching technique. As a typical example, it is possible to extract a characteristic region in each B-scan image and align a plurality of B-scan images by aligning the extracted characteristic regions.

A process is then performed to identify image regions that are changing between the registered B-scan images. This processing includes, for example, finding differences between different B-scan images. Each B-scan image is brightness image data representing the morphology of the subject's eye, and it is considered that the image area corresponding to the site other than blood vessels is substantially unchanged. On the other hand, considering that the backscatter that contributes to the interference signal varies randomly with blood flow, image regions where changes occur between multiple registered B-scan images (e.g. pixels with non-zero difference, or A pixel whose difference is equal to or greater than a predetermined threshold can be estimated to be a blood vessel region.

Information indicating that the image region is a blood vessel region is assigned to the image region specified in this way. Three-dimensionally distributed blood vessel regions are obtained by performing the above processing on a plurality of B cross-sections. By rendering such a three-dimensional blood vessel-enhanced image, a front image representing blood vessel distribution, an image of an arbitrary cross section, a shadowgram of an arbitrary range, and the like are generated.

Processing for forming a blood vessel-enhanced image is not limited to this. For example, it is possible to identify the blood vessel region by a conventional method using Doppler OCT, or to identify the blood vessel region by using a conventional image processing method. Also, by using different techniques depending on the site, it is possible to specify the blood vessel region for each site. For example, for the retina, the above-described typical technique or Doppler OCT technique can be used to identify the vascular area, and for the choroid, the image processing technique can be used to identify the vascular area.

<Blood flow data generator 33>
The blood flow data generator 33 operates in OCT blood flow measurement. The blood flow data generation unit 33, based on the image of the cross section of interest formed by the image forming unit 32 based on the data collected by the OCT scanner 31 in the OCT blood flow measurement, and the inclination angle of the blood vessel of interest in the cross section of interest, Blood flow data representing the state of blood flow in the vessel of interest is generated.

The data collected by the OCT scanner 31 in the OCT blood flow measurement are data (first data) collected by repeatedly scanning a cross section of interest intersecting the blood vessel of interest, and crossing the blood vessel of interest and different from the cross section of interest. and data (second data) obtained by scanning one or more cross-sections (cross-sections in the vicinity of the cross-section of interest). Note that instead of the second data, for example, the inclination angle of the target blood vessel at the position of the target cross section or its vicinity, which is acquired separately from the OCT blood flow measurement, can be used. As an example, it is possible to use the tilt angle obtained from the vessel-enhanced image obtained by OCT angiography.

The image forming unit 32 forms a morphological image and a phase image of the fundus based on the data collected by the OCT scanner 31 in the OCT blood flow measurement. A morphological image and a phase image obtained by OCT blood flow measurement are images corresponding to the same cross section. Typically, a morphological image and a phase image corresponding to the section of interest (section B) are obtained.

As mentioned above, in a typical OCT blood flow measurement, two types of scans (auxiliary scan and main scan) are performed on the fundus. Auxiliary scanning is performed to scan one or more cross-sections different from the cross-section of interest (cross-sections in the vicinity of the cross-section of interest) to acquire second data. In a typical auxiliary scan, two or more cross-sections intersecting the vessel of interest are scanned with the measurement light. The data acquired by the auxiliary scan are used to obtain the inclination angle of the vessel of interest in the section of interest. On the other hand, the main scan is performed to acquire the first data by repeatedly scanning the section of interest that intersects the blood vessel of interest with the measurement light. A cross-section on which the auxiliary scan is performed is placed near the cross-section of interest. This scan is Doppler measurement using OCT.

The target cross sections of the auxiliary scan and the main scan are oriented, for example, so as to be orthogonal to the running direction of the blood vessel of interest. In addition, the distance between the target cross section of the auxiliary scan and the cross section of interest (distance between cross sections) is set in advance or set for each examination. As an example of the latter, it is possible to set the distance between cross-sections based on predetermined factors such as the curvature of the target blood vessel in or near the target cross-section or the inspection accuracy. Alternatively, the user may set a desired cross-sectional distance.

This scan is preferably performed over at least one cardiac cycle of the patient's heart. This provides blood flow data for all phases of the heartbeat. The execution time of the main scan may be a preset constant time, or may be a time set for each patient or each examination.

For example, the image forming unit 32 generates a cross-sectional image representing the morphology of the first auxiliary cross section and a second A cross-sectional image representing the morphology of the target cross section is formed. At this time, it is possible to improve the image quality by using a technique such as averaging, or to select an optimum one from two or more cross-sectional images of each auxiliary cross-section.

Further, the image forming unit 32 forms a group of cross-sectional images representing time-series changes in the cross section of interest based on the data collected by the main scan (repetitive scan) of the cross section of interest. This processing is accomplished, for example, by forming cross-sectional images from the data collected for each scan iteration.

The processing executed by the image forming unit 32 includes, for example, noise removal (noise reduction), filtering, fast Fourier transform (FFT), etc., similar to conventional OCT technology. Note that the process of forming a cross-sectional image of the cross section of interest described here is the same as the morphological image forming process executed by the image forming unit 32 .

Furthermore, the image forming unit 32 forms a phase image representing the time-series change of the phase difference in the cross section of interest based on the data collected by the main scan of the cross section of interest. The data used for this processing is the same as the data used for forming the cross-sectional image(s) of the target cross-section. Therefore, there is a natural positional correspondence between the cross-sectional image of the cross section of interest and the phase image, and the registration is self-evident.

An example of a method of forming a phase image will be described. In a typical example, a phase image is obtained by calculating the phase difference between adjacent A-line complex signals (signals corresponding to adjacent scan points). In other words, the phase image of this example is formed based on time-series changes in the pixel values (luminance values) of each pixel of the cross-sectional image of the cross section of interest. For any pixel, the image forming unit 32 considers a graph of time-series changes in its luminance value. The image forming unit 32 obtains the phase difference Δφ between two times t1 and t2 (t2=t1+Δt) separated by a predetermined time interval Δt in this graph. Then, this phase difference Δφ is defined as the phase difference Δφ(t1) at time t1 (more generally, any time between two times t1 and t2). By executing this process for each of a large number of preset time points, a time-series change in the phase difference at the pixel is obtained.

A phase image is an image representing the phase difference value of each pixel at each point in time. This imaging processing can be realized, for example, by expressing the value of the phase difference by display color or brightness. At this time, the color (for example, red) indicating that the phase has increased along the time series can be made different from the color (for example, blue) that indicates that the phase has decreased. Also, the magnitude of the phase change amount can be expressed by the intensity of the display color. By adopting such an expression method, it becomes possible to express the direction and size of blood flow with colors and densities. A phase image is formed by executing the above processing for each pixel.

The time-series change of the phase difference can be obtained by sufficiently reducing the time interval Δt to secure the phase correlation. At this time, oversampling is performed by setting the time interval Δt to a value less than the time corresponding to the resolution of the cross-sectional image in the scanning of the measurement light.

The blood flow data generation unit 33 can execute, for example, a blood vessel region identification process, an inclination angle calculation process, and a blood flow data generation process. The blood flow data generation process includes, for example, at least a blood flow velocity calculation process, and may further include a blood vessel diameter calculation process and a blood flow volume calculation process.

In the blood vessel region identification process, the blood flow data generator 33 identifies the blood vessel region in each cross-sectional image corresponding to the target blood vessel. Furthermore, the blood flow data generator 33 identifies a blood vessel region in the phase image corresponding to the cross section of interest. Identification of the blood vessel region is performed by analyzing the pixel values of each image (for example, thresholding). The blood vessel region in the phase image may be identified based on the blood vessel region in the cross-sectional image corresponding to the cross section of interest and the result of registration between this cross-sectional image and the phase image.

In the inclination angle calculation process, the blood flow data generator 33 calculates the inclination angle of the target blood vessel in the target cross section based on the image (group) formed from the data acquired by the auxiliary scan.

An example of the tilt angle calculation process will be described. Please refer to FIG. Reference character B0 indicates a cross-sectional image (cross-sectional image of interest) in the cross-section of interest for which the blood vessel inclination angle is calculated. A blood vessel region V0 is depicted in the cross-sectional image of interest B0. Reference numerals B11 and B12 indicate two cross-sectional images (auxiliary cross-sectional images) in two auxiliary cross-sections located near the target cross-section B0. In the auxiliary cross-sectional image B11, a blood vessel region V11 in the auxiliary cross-section B11 of the same blood vessel (target blood vessel) as the blood vessel region V0 is depicted. Similarly, the auxiliary cross-sectional image B12 depicts a blood vessel region V12 in the auxiliary cross-section B12 of the target blood vessel.

The blood flow data generator 33 calculates the inclination of the target blood vessel in the target cross section based on the target cross-sectional image B0 and the auxiliary cross-sectional images B11 and B12. The number of auxiliary cross-sectional images to be referred to is not limited to two, and may be any number of one or more.

The blood flow data generator 33 calculates the inclination of the target blood vessel in the target cross section based on the blood vessel regions V0, V11, and V12 and the inter-section distance. The cross-sectional distance may be the distance between the auxiliary cross-sectional image B11 and the auxiliary cross-sectional image B12. Alternatively, the cross-sectional distance may be defined by at least one of the distance between the auxiliary cross-sectional image B11 and the cross-sectional image of interest B0 and the distance between the auxiliary cross-sectional image B12 and the cross-sectional image of interest B0. good. Let L be the distance between the auxiliary cross-sectional image B11 (or B12) and the target cross-sectional image B0.

The A-scan direction (the direction indicated by the arrow pointing downward) shown in FIG. 2 indicates, for example, the orientation of the A-scan image included in the target cross-sectional image B0. This A-scan image may be, for example, an A-scan image located in the center of a plurality of A-scan images included in the target cross-sectional image B0.

In a typical example, the blood flow data generator 33 can calculate the inclination A of the target blood vessel in the target cross section based on the positional relationship between the three blood vessel regions V0, V11 and V12. This positional relationship is obtained, for example, by connecting three blood vessel regions V0, V11 and V12. More specifically, the blood flow data generator 33 identifies feature points of the three blood vessel regions V0, V11 and V12, and connects these feature points. Feature points referred to here include the center position (axis position), the center of gravity position, the top, and the like. Methods of connecting these feature points include a method of connecting with a line segment, a method of connecting with an approximation curve (spline curve, Bezier curve, etc.).

Furthermore, the blood flow data generator 33 calculates the slope A based on the line connecting these feature points. When line segments are used, the blood flow data generating unit 33 generates, for example, a first line segment connecting the feature point of the blood vessel region V0 in the cross-sectional image of interest B0 and the feature point of the blood vessel region V11 in the auxiliary cross-sectional image B11. and the slope of the second line segment connecting the feature point of the blood vessel region V0 and the feature point of the blood vessel region V12 in the auxiliary cross-sectional image B12. As an example of this calculation process, the average value of the slopes of two line segments can be obtained. Also, as an example of connecting with an approximated curve, the slope of the approximated curve at the intersection position of the approximated curve and the cross section of interest can be obtained.

In this example, blood vessel regions in three cross sections are considered, but it is also possible to obtain the inclination by considering blood vessel regions in two cross sections. As a specific example, the inclination A of the target blood vessel in the target cross section can be obtained based on the blood vessel region V11 in the auxiliary cross-sectional image B11 and the blood vessel region V12 in the auxiliary cross-sectional image B12. Alternatively, the inclination A of the target blood vessel in the target cross section can be obtained based on the blood vessel region V11 in the auxiliary cross-sectional image B11 and the blood vessel region V0 in the target cross-sectional image B0. For example, the slope of the first line segment or the second line segment can be obtained and adopted as the slope A of the vessel of interest.

Also, in the above example, only one value of the slope A is obtained, but the slopes may be obtained for two or more positions (or regions) in the blood vessel region V0. In this case, two or more obtained slope values can be used separately, or one value (for example, average value) statistically obtained from these slope values can be used as the slope A.

In the blood flow data generation process, the blood flow data generation unit 33 generates data related to the blood vessel of interest based on the phase image formed based on the main scan (Doppler OCT) and the tilt angle obtained by the blood flow data generation unit 33. Generate blood flow data. As described above, in a typical example, the blood flow data generation process includes a blood flow velocity calculation process, a blood vessel diameter calculation process, and a blood flow volume calculation process.

The blood flow data generation unit 33 can calculate the blood flow velocity in the cross section of interest of the blood flowing through the blood vessel of interest based on the time series change of the phase difference obtained as the phase image. The value calculated by this process may be the blood flow velocity at a certain point in time, or may be the time series change in the blood flow velocity (blood flow velocity change data). In the former case, for example, it is possible to selectively acquire the blood flow velocity at a predetermined time phase of the electrocardiogram (for example, the time phase of the R wave). Also, the time range in the latter is the whole or an arbitrary part of the time when the section of interest is scanned.

When the blood flow velocity change data is obtained, the blood flow data generator 33 can calculate the statistic value of the blood flow velocity in the range of time. These statistics include mean, standard deviation, variance, median, maximum, minimum, maximum and minimum. It is also possible to create a histogram of blood velocity values.

The blood flow data generator 33 can calculate the blood flow velocity using the Doppler OCT method as described above. For example, the following relational expression is used to calculate the blood flow velocity.

Δf: Doppler shift received by scattered light of measurement light n: Refractive index of medium (blood) v: Flow velocity of medium (blood velocity)
θ: Angle (tilt angle) formed by the incident direction of the measurement light and the direction of the flow of the medium
λ: Center wavelength of measurement light

In a typical example, the refractive power n of the medium and the center wavelength λ of the measurement light are each known, the Doppler shift Δf is obtained from the time-series change of the phase difference, and the tilt angle θ is obtained from the tilt angle calculation process or the blood vessel angle distribution obtained from The blood flow data generator 33 can calculate the blood flow velocity v by substituting these values into the above relational expression.

In the blood vessel diameter calculation process, the blood flow data generator 33 calculates the diameter of the target blood vessel in the target cross section. Examples of this calculation method include a first calculation method using a front image of the fundus and a second calculation method using a cross-sectional image.

When the first calculation method is applied, the part of the fundus including the position of the cross section of interest is photographed in advance. This fundus photographing is performed by the front image acquiring unit 60, for example. Alternatively, a previously acquired and stored front image of the fundus may be read. A blood vessel-enhanced image may also be used.

The blood flow data generation unit 33 generates the image of the fundus based on various factors that determine the relationship between the scale on the image and the scale in the real space, such as the angle of view (magnification), the working distance, and information on the eyeball optical system. Sets the scale for the front image. This scale represents length in real space. As a specific example, this scale is obtained by associating the interval between adjacent pixels with the scale in real space (for example, the interval between pixels=10 μm). It is also possible to previously calculate the relationship between various values of the above factors and the scale in the real space, and to store information expressing this relationship in a table format or a graph format. In this case, scales corresponding to the above factors are selectively applied.

The blood flow data generation unit 33 calculates the diameter of the blood vessel of interest in the cross section of interest, that is, the diameter of the blood vessel region, based on this scale and the pixels included in the blood vessel region. As a specific example, the blood flow data generator 33 can obtain the maximum value and average value of diameters in various directions of the blood vessel region. Alternatively, the blood flow data generator 33 can approximate the contour of the blood vessel region to a circle or ellipse, and obtain the diameter of the circle or ellipse. Since the area of the blood vessel region can be (substantially) determined once the blood vessel diameter is determined, the area may be calculated instead of obtaining the blood vessel diameter.

A second calculation method will be described. In the second calculation method, a cross-sectional image of the fundus on the target cross-section is used. This cross-sectional image may be a cross-sectional image based on the main scan, or may be obtained separately. The scale of this cross-sectional image is determined according to the scanning mode of the measurement light. The length of the section of interest is determined based on various factors that determine the relationship between the scale on the image and the scale in the real space, such as working distance and eyeball optical system information. The blood flow data generator 33 can, for example, find the interval between adjacent pixels based on the length of the cross section of interest, and calculate the diameter of the blood vessel of interest in the cross section of interest in the same manner as in the first calculation method.

In the blood flow rate calculation process, the blood flow data generator 33 calculates the flow rate of blood flowing through the vessel of interest based on the blood flow velocity calculation result and the blood vessel diameter calculation result. An example of this processing is described below.

Assume that the blood flow in the blood vessel is Hagen-Poiseuille flow. Let w be the diameter of the blood vessel, and Vm be the maximum value of the blood flow velocity. In this case, the blood flow Q is represented by the following relational expression.

The blood flow data generation unit 33 substitutes the blood vessel diameter w obtained by the blood vessel diameter calculation process and the maximum value Vm in the blood flow velocity obtained by the blood flow velocity calculation process into the above relational expression to obtain the blood flow volume Q can be calculated.

<Operation unit 50>
The operation unit 50 is used by the user to input instructions to the ophthalmologic imaging apparatus 1 . The operation unit 50 may include known operation devices used in ophthalmologic apparatuses and computers. For example, the operation unit 50 may include a mouse, touch pad, trackball, keyboard, pen tablet, operation panel, joystick, button, switch, and the like.

The operation unit 50 may include a touch panel. In this case, the display control unit 13 can display a GUI for inputting instructions and information on the touch panel.

<Front image acquisition unit 60>
The front image acquisition unit 60 acquires a front image of the fundus. Processing for acquiring a front image is arbitrary. In the first example, the front image acquisition section 60 may include a configuration for photographing the fundus. For example, the front image acquisition unit 60 may include a fundus camera optical system, an SLO optical system, and the like.

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

In a third example, the frontal image acquisition unit 60 may include a processor that forms a frontal image by OCT. OCT front images include C-scan images, projection images, shadowgrams, and the like.

<motion>
An example of the operation of the ophthalmologic imaging apparatus 1 according to this embodiment will be described. Hereinafter, the case where the partial data specifying unit 12 is not used will be described in the first operation example, and the case where the partial data specifying unit 12 is used will be described in the second operation example.

<First operation example>
An example of the operation of the ophthalmologic imaging apparatus 1 is shown in FIG. Here, preparatory processing such as input of the patient ID, alignment of the optical system with respect to the eye to be examined, focus adjustment of the optical system, adjustment of the OCT optical path length, adjustment of the fixation position, setting of the OCT scan range, etc. has already been performed. shall be Also, it is assumed that the standard data 21 has already been stored in the storage unit 20 .

(S1: Execute OCT blood flow measurement of the fundus)
The ophthalmologic imaging apparatus 1 performs OCT blood flow measurement on a section of interest of a blood vessel of interest in the fundus of an eye to be examined. OCT blood flow measurement is performed for each of one or more cross sections of interest in each of one or more blood vessels of interest. Also, when there are a plurality of blood vessels passing through the target cross section, at least one of these blood vessels can be set as the target blood vessel. Conversely, a section of interest can also be set so as to cross a plurality of blood vessels of interest.

In OCT blood flow measurement, the scan controller 11 controls the light source and optical scanner included in the OCT scanner 31 . Under the control of the scan control unit 11, the OCT scanner 31 repeatedly scans a first cross section that intersects the target blood vessel at a preset measurement position (that is, target cross section) to collect first data. Second data is acquired by scanning one or more auxiliary cross-sections intersecting the vessel of interest in the vicinity of . The order of collecting the first data and collecting the second data is arbitrary.

(S2: form a morphological image)
The image forming unit 32 forms one or more morphological images (B-scan images) corresponding to the cross section of interest based on the first data collected by repeatedly scanning the cross section of interest in step S1. Typically, the same number of morphological images can be formed as the number of scanning repetitions. As a result, time-series B-scan images corresponding to the cross section of interest are obtained. Note that the number of morphological images may be formed in a number smaller than the number of repetitions of scanning.

Further, the image forming unit 32 forms a morphological image (B-scan image) corresponding to each auxiliary cross section based on the second data collected by scanning one or more auxiliary cross sections in step S2.

Each morphological image formed in step S2 is stored in the storage unit 20 as the OCT data 22. FIG.

(S3: Find the inclination angle of the target blood vessel)
The blood flow data generator 33 obtains the inclination angle of the target blood vessel in the target cross section based on two or more morphological images among the plurality of morphological images formed in step S2. For this processing, for example, a combination of two morphological images corresponding to two auxiliary cross sections, or a combination of a morphological image corresponding to one auxiliary cross section and a morphological image corresponding to a cross section of interest is used.

(S4: Form a phase image)
The image forming unit 32 forms a phase image corresponding to the cross section of interest based on the first data collected by repeatedly scanning the cross section of interest in step S1.

The phase image formed in step S4 is stored in the storage unit 20 as the OCT data 22. FIG.

(S5: Obtain blood flow data)
The blood flow data generation unit 33 generates blood flow data for the blood vessel of interest passing through the cross section of interest based on the inclination angle of the blood vessel of interest obtained in step S3 and the phase image formed in step S4. This blood flow data includes, for example, data representing time-series changes in blood flow in the vessel of interest. Examples of such data include time-series changes in blood flow velocity during the measurement period (typically, a period longer than one cardiac cycle) of the OCT blood flow measurement performed in step S1, and time-series changes in blood flow volume per unit time.

The blood flow data generated in step S5 is stored in the storage unit 20 as the OCT data 22. FIG. When considering a plurality of vessels of interest, blood flow data is obtained for each of the plurality of vessels of interest. Furthermore, for each of the plurality of vessels of interest, the identification information (for example, the position information of the vessel of interest) and the corresponding blood flow data are associated with each other and stored in the storage unit 20 .

(S6: Create a blood flow graph)
The display control unit 13 creates a blood flow graph representing the fundus blood flow dynamics of the eye to be examined based on the blood flow data generated in step S5. A blood flow graph represents time-series changes in blood flow in a blood vessel of interest in a cross section of interest.

The blood flow graph creation process includes, for example, the following processes.
(1) The blood flow data (for example, blood flow velocity or blood flow volume per unit time) generated in step S5 is represented by the horizontal axis (first coordinate axis) indicating time t and the vertical axis (second coordinate axis). (2) A process of connecting the plotted point groups with a line.

Here, the values of the plotted point cloud (that is, the values on the vertical axis) are, for example, the values of a plurality of pixels (that is, blood values corresponding to the magnitude of the flow velocity, etc.). This statistic may be, for example, mean, median, mode, maximum, minimum, and the like. Alternatively, the value on the vertical axis may be the value of a predetermined pixel (for example, the pixel located at the center, the pixel located at the center of gravity, etc.) in the target blood vessel section at the corresponding time phase.

The process of connecting the plotted point groups with lines includes the process of connecting temporally adjacent points with lines. Lines connecting adjacent points may be straight or curved. When the connection line is a curve, for example, it is possible to apply any approximation curve (eg, spline curve, Bezier curve, etc.) with plotted point groups as control points. Also, the point group may be interpolated by applying Lagrangian interpolation or the like.

(S7: Create standard information)
The display control unit 13 creates standard information based on standard data 21 stored in the storage unit 20 .

For example, if the standard data 21 includes data representing time-series changes in a predetermined parameter (for example, blood flow velocity or blood flow volume per unit time), the display control unit 13 controls the blood flow in the same manner as in step S6. A graph (standard blood flow graph) can be created. Alternatively, the display control unit 13 can obtain statistical values of predetermined parameters in each time phase based on the standard data 21 . This statistic may be, for example, mean, median, mode, maximum, minimum, and the like.

Note that if the standard data 21 already contains standard information, there is no need to execute step S7.

As an optional process, the display control unit 13 can execute a process of matching the scale of the blood flow graph and the scale of the standard information. For example, in order to cancel the difference between the subject's heart rate and the standard heart rate, the display control unit 13 can adjust the time scale between the blood flow graph and the standard blood flow graph. It is possible.

Although this is also an arbitrary process, the display control unit 13 can execute a process of matching the timing of the blood flow graph with the timing of the standard information. For example, the display control unit 13 adjusts the timings of the blood flow graph and the standard blood flow graph so that the peak position of the blood flow graph and the peak position of the standard blood flow graph match (that is, relatively move both in the direction of the time axis). is possible.

(S8: Display blood flow graph and standard information)
The display control unit 13 causes the display device 2 to display side by side the blood flow graph of the fundus of the subject's eye created in step S6 and the standard information created in step S7.

An example of information displayed in step S8 is shown in FIG. 4A. In this example, a blood flow graph 140 representing time-series changes in blood flow in the vessel of interest and a standard blood flow graph 160 representing time-series changes in standard blood flow are displayed.

Each of the blood flow graph 140 of this example and the standard blood flow graph 160 is represented by a two-dimensional orthogonal coordinate system in which the horizontal axis indicates time t and the vertical axis indicates blood flow velocity (v). Note that even when other parameters such as the blood flow rate per unit time are applied, for example, a graph showing the time on the horizontal axis and the parameter on the vertical axis can be displayed.

In this example, the time axis t of the blood flow graph 140 and the time axis t of the standard blood flow graph 160 are synchronized. That is, the blood flow graph 140 and the standard blood flow graph 160 are displayed so that the user can recognize the corresponding relationship between the time phase of the blood flow graph 140 and the time phase of the standard blood flow graph 160 .

Also, in this example, the blood flow graph 140 and the standard blood flow graph 160 are displayed so as to satisfy the following conditions: (1) the scale of the time axis t of the blood flow graph 140 and the standard blood flow graph 160; (2) the period represented by the time axis t of the blood flow graph 140 is equal to the period represented by the time axis t of the standard blood flow graph 160; (3) the same time phase (time) are arranged at corresponding positions (corresponding positions in the vertical direction).

In general, the scale of time axis t of blood flow graph 140 and the scale of time axis t of standard blood flow graph 160 need not be equal. For example, by setting the scale of _{one time} axis t1 to an integral multiple of the scale of the other time axis t2, the mutual correspondence can be clarified.

Also, in general, the period represented by the time axis t of the blood flow graph 140 and the period represented by the time axis t of the standard blood flow graph 160 need not be equal. For example, one period may be part of the other period, or part of one period may be equal to part of the other period.

The display control unit 13 can display the blood flow graph 140 and the standard blood flow graph 160 overlaid on the same time axis (same coordinate system). At this time, the display color of the blood flow graph 140 and the display color of the standard blood flow graph 160 can be different.

The display processing unit 13 can display the fundus blood flow information and the biometric information as a moving image so that their time phases are synchronized with each other. In this example, the display control unit 13 can synchronously move the blood flow graph 140 and the standard blood flow graph 160 along their respective time axes t.

Another example of information displayed in step S8 is shown in FIG. 4B. In this example, a blood flow graph 140 representing time-series changes in blood flow in the vessel of interest and statistical values as standard information are displayed. Additionally, a standard blood flow graph 160 similar to that of FIG. 4A may be displayed in parallel with the blood flow graph 140. FIG.

A reference numeral 161 denotes a line indicating the average value of blood flow velocities calculated from the standard data 21 . In this case, it is possible to further display a line 141 indicating the average value of the blood flow velocity calculated from the blood flow graph 140 (or blood flow data). This allows the user to easily compare the average values of both blood flow velocities.

Reference numeral 161 is a line indicating the maximum value of blood flow velocity obtained from standard data 21 . By comparing the maximum value line 161 and the blood flow graph 140, the user can easily compare the maximum values of both blood flow velocities.

The display control unit 13 can display the morphological image and the phase image of the cross section of interest along with such a blood flow graph and standard information. Further, when OCT angiography is performed in addition to OCT blood flow measurement, the display control unit 13 can cause the display device 2 to display a blood vessel-enhanced image acquired by the OCT angiography.

<Second operation example>
Another example of the operation of the ophthalmologic imaging apparatus 1 is shown in FIG. Here, preparatory processing such as input of the patient ID, alignment of the optical system with respect to the eye to be examined, focus adjustment of the optical system, adjustment of the OCT optical path length, adjustment of the fixation position, setting of the OCT scan range, etc. has already been performed. shall be Also, it is assumed that the standard data 21 has already been stored in the storage unit 20 . In this example, the partial data specifying unit 12 is used.

(S11-S17)
Steps S11 to S17 are executed in the same manner as steps S1 to S7 of the first operation example, respectively.

(S18: Identifying a portion of interest in the blood flow graph)
The partial data specifying unit 12, for example, combines the blood flow data generated in step S15 and/or the blood flow graph generated in step S16 with the standard data 21 stored in the storage unit 20 and/or the data generated in step S17. A portion of interest in the blood flow graph created in step S16 is specified based on the obtained standard information.

For example, when the standard data 21 of the fundus blood flow dynamics in a healthy eye is applied, the partial data specifying unit 12 uses this standard data in the blood flow data generated in step S15 and/or the blood flow graph created in step S16. A portion different from the data 21 is specified. This specific processing is executed, for example, by comparing the blood flow graph and a standard blood flow graph.

In a typical example, the partial data specifying unit 12 executes the following series of processes. First, the partial data specifying unit 12 obtains a feature amount (for example, an arbitrary statistical value of blood flow velocity, a period of the blood flow graph, an amplitude of the blood flow graph, etc.) from the blood flow graph. Similarly, the partial data specifying unit 12 obtains the same feature amount from the standard blood flow graph. These processes are executed for each section, for example, by dividing the time axis into a plurality of sections. Furthermore, the partial data specifying unit 12 specifies a portion of the blood flow graph that does not match the feature amount of the standard blood flow graph by comparing the feature amount of the blood flow graph and the feature amount of the standard blood flow graph. The identified portion is treated as the portion of interest.

Another example will be described. When standard data 21 of fundus blood flow dynamics in a diseased eye (for example, an eye with a specific disease) is applied, the partial data specifying unit 12 uses the blood flow data generated in step S15 and/or the blood flow data generated in step S16. A portion that matches the standard data 21 is specified in the blood flow graph obtained. This specific process can also be executed in the same way.

(S19: Process the target portion)
The display control unit 13 processes the portion of interest identified in step S18. This processing is, for example, a process of changing the form of the attention part (e.g., shape, color, line form, etc.) and/or a process of adding an object (e.g., image, text, etc.) indicating the attention part. including.

(S20: Display the blood flow graph in which the part of interest is processed)
The display control unit 13 causes the display device 2 to display the blood flow graph in which the target portion has been processed in step S19. At this time, similarly to step S8 in the first operation example, it is possible to display the standard information, the morphological image and the phase image of the cross section of interest, and the blood vessel-enhanced image.

An example of the blood flow graph displayed in step S20 is shown in FIG. 6A. In the blood flow graph 140 of this example, the portion of interest identified in step S18 is represented by a thicker line than the other portions. Specifically, six portions of interest in the blood flow graph 140 are represented by thick lines 151-156. Thereby, the user can easily grasp the part of interest of the blood flow graph 140 (for example, the part presumed to be a sign or influence of a disease).

Another example of the blood flow graph displayed in step S20 is shown in FIG. 6B. The blood flow graph 140 of this example is added with a circular image indicating the portion of interest identified in step S18. Specifically, six portions of interest in blood flow graph 140 are surrounded by circular images 171-176. Thereby, the user can easily grasp the part of interest of the blood flow graph 140 (for example, the part presumed to be a sign or influence of a disease).

Furthermore, in the example shown in FIG. 6B, a description of the portion of interest is added to the blood flow graph 140 . For example, a balloon 182 indicating that the peak value of the blood flow velocity is low is displayed for the portion of interest surrounded by the circular image 172 . Although illustration is omitted, similar balloons can be displayed for target portions surrounded by other circular images 171, 173 to 176 as well. Further, for example, when the user designates a desired portion of interest using the operation unit 50, the display control unit 13 can be configured to display a balloon corresponding to the designated portion of interest.

<Ophthalmic information processing device>
An ophthalmologic information processing apparatus according to an exemplary embodiment will be described. FIG. 7 shows a configuration example of the ophthalmologic information processing apparatus of this embodiment. The ophthalmologic information processing apparatus 200 stores fundus data (including blood flow data) acquired using OCT blood flow measurement, and displays various information based on the stored data. Further, the ophthalmic information processing apparatus 200 may be configured to store data acquired using OCT angiography and display information based on this data.

The ophthalmologic information processing apparatus 200 can display, on the display device 2, various types of information such as blood flow information, fundus morphological images, and blood vessel-enhanced images. The display device 2 may be a part of the ophthalmologic information processing apparatus 200 or may be an external device connected to the ophthalmologic information processing apparatus 200 . In addition, the ophthalmologic information processing apparatus 200 can send various types of information to a computer, a storage device, an ophthalmologic apparatus, and the like.

The ophthalmologic information processing apparatus 200 includes a control unit 210 , a storage unit 220 , a data processing unit 230 , a data input unit 240 and an operation unit 250 . Control unit 210 includes a partial data specifying unit 212 and a display control unit 213 . The storage unit 220 stores standard data 221 and OCT data 222 .

Each element of the ophthalmologic information processing apparatus 200 has, for example, the same configuration and function as the corresponding element included in the ophthalmologic photographing apparatus 1 described above. That is, the control unit 210 has the same configuration and functions as the control unit 10, the partial data specifying unit 212 has the same configuration and functions as the partial data specifying unit 12, and the display control unit 213 has the same configuration and functions as the display control unit 13. The storage unit 220 has the same configuration and functions as the storage unit 20 , and the operation unit 250 has the same configuration and functions as the operation unit 50 .

The standard data 221 and the OCT data 222 may be similar to the standard data 21 and the OCT data 22, respectively, stored in the ophthalmologic imaging apparatus 1 described above.

The data processing unit 230 executes various data processing. The data processing section 230 may have the same configuration and functions as the image forming section 32 . For example, when the OCT data 222 includes at least one of the OCT data (1), (3) and (5) described above, the data processing unit 230 performs the same processing as the image forming unit 32 to obtain an OCT image. (morphological image, phase image, etc.) can be formed.

The data processor 230 may have the same configuration and functions as the blood flow data generator 33 . For example, when the OCT data 222 includes at least one of the OCT data (1) and (5) described above, the data processing unit 230 performs the same processing as the blood flow data generation unit 33 to generate blood flow data ( blood flow velocity, blood flow volume, etc.) can be generated.

The data input unit 240 inputs the standard data 221 from the outside to the ophthalmologic information processing apparatus 200 . Further, the data input unit 240 inputs the OCT data 222 and/or the original data to the ophthalmologic information processing apparatus 200 from the outside. The data input unit 240 may include, for example, a communication interface for data communication with an external device, a device for reading data from a recording medium, and the like.

The display control unit 213 can display the same information as the information displayed by the display control unit 13 of the ophthalmologic imaging apparatus 1 described above in the same manner. For example, the display control unit 213 can perform control for displaying on the display device 2 information similar to at least one of FIGS. 4A, 4B, 6A, and 6B.

〈Action and effect〉
Actions and effects of the ophthalmic photographing apparatus and the ophthalmic information processing apparatus according to the exemplary embodiment described above will be described.

An ophthalmologic imaging apparatus (1) according to an embodiment includes a storage section (20), a data acquisition section (30), and a display processing section (display control section 13, etc.). The storage unit stores pre-created standard data (21) of fundus hemodynamics. The data acquisition unit acquires data (OCT data 22) by applying at least OCT blood flow measurement to the fundus of the subject's eye. The display processing unit causes the display means (display device 2) to display information.

Specifically, the display processing unit displays a blood flow graph representing time-series changes in blood flow in the blood vessels of the fundus based on the data acquired by the data acquisition unit. Further, the display processing unit displays the standard information based on the standard data stored in the storage unit in parallel with the blood flow graph.

An ophthalmologic information processing apparatus (200) according to the embodiment includes a storage unit (220) and a display processing unit (display control unit 213, etc.). The storage unit stores standard data (221) of fundus blood flow dynamics created in advance and data (OCT data 222) obtained by applying optical coherence tomography (OCT) blood flow measurement to the fundus of the eye to be examined. Remember. The display processing unit causes the display means (display device 2) to display information.

Specifically, the display processing unit displays a blood flow graph representing time-series changes in blood flow in the blood vessels of the fundus based on the data acquired by the OCT blood flow measurement. Furthermore, the display processing unit displays the standard information based on the standard data in parallel with the blood flow graph.

According to such an embodiment, the user can easily visually compare the fundus blood flow data of the subject's eye obtained by OCT blood flow measurement with the standard information based on the standard data. .

In an embodiment, the display processing unit may be configured to display a standard blood flow graph based on standard data as the standard information.

According to such a configuration, the user can graphically compare both the fundus blood flow data of the subject's eye obtained by OCT blood flow measurement and the standard data.

In an embodiment, the blood flow graph may be configured to be represented by a two-dimensional rectangular coordinate system in which the first coordinate axis indicates time and the second coordinate axis indicates blood flow velocity or blood flow per unit time. .

According to such a configuration, both the blood flow graph and the standard blood flow graph can be displayed in the same manner, so it is possible to more easily compare the fundus blood flow data of the eye to be examined and the standard data. become.

In an embodiment, the display processing unit may be configured to display statistical values based on standard data as the standard information.

According to such a configuration, the blood flow graph of the subject's eye can be observed while referring to the statistical values based on the standard data.

In the embodiment, the storage unit may store first standard data that is pre-created standard data of fundus hemodynamics in healthy eyes. In this case, the ophthalmologic imaging apparatus and the ophthalmologic information processing apparatus according to the embodiment include a first identification unit (partial data identification unit 12, 212). Furthermore, the display processing section may be configured to display a portion of the blood flow graph corresponding to the target portion specified by the first specifying portion in a manner different from other portions.

Further, in the embodiment, the storage unit may store second standard data, which is standard data of fundus blood flow dynamics in the diseased eye created in advance. In this case, the ophthalmologic photographing apparatus and the ophthalmologic information processing apparatus according to the embodiment include a second identification unit (partial data identification unit 12, 212). Furthermore, the display processing section may be configured to display a portion of the blood flow graph corresponding to the target portion specified by the second specifying portion in a manner different from other portions.

According to such a configuration, the user can easily grasp a portion of interest (for example, a portion presumed to be a sign or influence of a disease) in the blood flow graph of the eye to be examined.

In the ophthalmologic imaging apparatus according to the embodiment, the data acquisition unit (30) may be configured to perform the following series of processes in OCT blood flow measurement: Collecting first data by repeatedly scanning one section; Collecting second data by scanning one or more second sections intersecting the blood vessel in the vicinity of the measurement position; Collecting second data; Measurement position based on the second data obtaining blood flow data representing time-series changes in blood flow in the blood vessel passing through the first cross section based on the calculated inclination angle and the first data;

According to such a configuration, it is possible to suitably perform OCT blood flow measurement to generate blood flow data, and display a blood flow graph based on this blood flow data.

In the ophthalmologic imaging apparatus according to the embodiment, the data acquisition unit (30) may be configured to acquire data by applying OCT angiography to the fundus of the subject's eye. Furthermore, the display processing section (13) may be configured to display a blood vessel-enhanced image based on data obtained by OCT angiography.

In the ophthalmologic information processing apparatus according to the embodiment, the storage unit (220) may be configured to store data obtained by applying OCT angiography to the fundus of the subject's eye. Furthermore, the display processing unit (213) may be configured to display a blood vessel-enhanced image based on data obtained by OCT angiography.

With such a configuration, the user can grasp the distribution of the fundus blood vessels in addition to the fundus blood flow dynamics of the subject's eye.

The actions and effects of the embodiments are not limited to these, and actions and effects provided by each item described as the embodiment and actions and effects provided by a combination of a plurality of items should also be considered. In addition, any of the above-described embodiments, other embodiments, known techniques, and the like can be arbitrarily combined in order to obtain desired actions and/or effects, or for other purposes.

The configuration described above is merely an example for suitably implementing the present invention. Therefore, any modification (omission, substitution, addition, etc.) within the scope of the gist of the present invention can be applied as appropriate.

1 ophthalmic imaging apparatus 2 display device 10 control unit 11 scan control unit 12 partial data identification unit 13 display control unit 20 storage unit 21 standard data 22 OCT data 30 data acquisition unit 31 OCT scanner 32 image formation unit 33 blood flow data generation unit 50 Operation unit 140 Blood flow graph 160 Standard blood flow graph 200 Ophthalmic information processing apparatus 210 Control unit 212 Partial data identification unit 213 Display control unit 220 Storage unit 221 Standard data 222 OCT data 230 Data processing unit 240 Data input unit 250 Operation unit

Claims (9)

a storage unit that stores pre-created standard data of fundus hemodynamics;
A data acquisition unit that acquires data by applying optical coherence tomography (OCT) blood flow measurement to the fundus of the eye to be examined;
a display processing unit that causes the display means to display information;
The display processing unit
displaying a blood flow graph representing time-series changes in blood flow in blood vessels of the fundus based on the data acquired by the data acquisition unit;
displaying standard information based on the standard data in parallel with the blood flow graph;
The storage unit stores first standard data that is pre-created standard data of fundus hemodynamics in a healthy eye,
a first identification unit that identifies a portion of the data acquired by the data acquisition unit that differs from the first standard data;
The display processing unit causes the portion of the blood flow graph corresponding to the portion specified by the first specifying unit to be displayed in a manner different from other portions,
Ophthalmic imaging equipment. The first standard data is created in advance by statistically processing a group of healthy eyes,
The ophthalmic photographing apparatus according to claim 1. The first identifying unit obtains a predetermined feature amount from the blood flow graph, obtains the feature amount from the standard information, and compares the feature amount of the blood flow graph with the feature amount of the standard information. Identifying the portion different from the first standard data by identifying the portion of the blood flow graph that does not match the feature amount of the standard information;
The ophthalmologic imaging apparatus according to claim 1 or 2. The first identifying unit divides the time axis of each of the blood flow graph and the standard information into a plurality of sections, obtains the feature amount of the blood flow graph for each of the plurality of sections, and Find features,
The ophthalmic photographing apparatus according to claim 3. a storage unit that stores pre-created standard data of fundus hemodynamics;
A data acquisition unit that acquires data by applying optical coherence tomography (OCT) blood flow measurement to the fundus of the eye to be examined;
a display processing unit that causes the display means to display information;
The display processing unit
displaying a blood flow graph representing time-series changes in blood flow in blood vessels of the fundus based on the data acquired by the data acquisition unit;
displaying standard information based on the standard data in parallel with the blood flow graph;
The storage unit stores second standard data that is pre-created standard data of fundus hemodynamics in the affected eye,
a second specifying unit that specifies a portion of the data acquired by the data acquiring unit that matches the second standard data;
The display processing unit displays a portion of the blood flow graph corresponding to the portion specified by the second specifying unit in a manner different from other portions,
Ophthalmic imaging equipment. The second standard data is created in advance by statistically processing a group of affected eyes,
The ophthalmic photographing apparatus according to claim 5. The second identifying unit obtains a predetermined feature amount from the blood flow graph, obtains the feature amount from the standard information, and compares the feature amount of the blood flow graph with the feature amount of the standard information. Identifying the portion that matches the second standard data by identifying the portion of the blood flow graph that matches the feature amount of the standard information;
The ophthalmologic imaging apparatus according to claim 5 or 6. The second identifying unit divides the time axis of each of the blood flow graph and the standard information into a plurality of sections, obtains the feature amount of the blood flow graph for each of the plurality of sections, and Find features,
The ophthalmic imaging apparatus according to claim 7. The feature amount of the blood flow graph includes any one of a statistic value of blood flow velocity, a period of the blood flow graph, and an amplitude of the blood flow graph,
The standard information includes a standard blood flow graph,
The feature amount of the standard information includes any one of a statistic value of blood flow velocity, a period of the standard blood flow graph, and an amplitude of the standard blood flow graph,
9. The ophthalmic imaging apparatus according to any one of claims 3, 4, 7 and 8.

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