WO2009148067A1 - Système de diagnostic d'informations rétiniennes - Google Patents

Système de diagnostic d'informations rétiniennes Download PDF

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WO2009148067A1
WO2009148067A1 PCT/JP2009/060111 JP2009060111W WO2009148067A1 WO 2009148067 A1 WO2009148067 A1 WO 2009148067A1 JP 2009060111 W JP2009060111 W JP 2009060111W WO 2009148067 A1 WO2009148067 A1 WO 2009148067A1
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retinal
blood vessel
infarction
diagnostic system
retinal blood
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PCT/JP2009/060111
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English (en)
Japanese (ja)
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礼治 川田
大介 阪本
正博 篠田
信一 田村
佑治 平井
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株式会社 網膜情報診断研究所
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Priority to JP2010515882A priority Critical patent/JP5535905B2/ja
Publication of WO2009148067A1 publication Critical patent/WO2009148067A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/0016—Operational features thereof
    • A61B3/0025—Operational features thereof characterised by electronic signal processing, e.g. eye models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30041—Eye; Retina; Ophthalmic
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular

Definitions

  • Cerebral infarction is a high-frequency disease that accounts for many of the causes of death in Japanese people, and in many cases, care is required with a sequelae.
  • Cerebral infarction is classified into several categories, and representative examples include cardiogenic cerebral infarction, atherothrombotic cerebral infarction, and lacunar infarction.
  • cardiogenic cerebral infarction is an acute and severe case where a heart-like thrombus causes infarction in a brain blood vessel due to heart disease such as atrial fibrillation or cardiac surgery.
  • heart disease such as atrial fibrillation or cardiac surgery.
  • atherothrombotic cerebral infarction causes infarction by gradually narrowing the arterial lumen due to atheroma deposited on the arterial wall due to arteriosclerosis, and a certain amount of time is required until the symptoms become apparent. is necessary.
  • economy class syndrome refers to acute pulmonary thromboembolism associated with deep vein thrombosis that occurs while traveling (especially in an airplane).
  • thrombus is formed in the pulmonary artery or in the heart to occlude the coronary artery, which is the heart's nutritional blood vessel, resulting in acute myocardial infarction and cerebral infarction in the brain.
  • the present inventor has proposed a detection device for arteriosclerosis that is extremely useful in preventive medicine as a device that uses “retinal information”, which is information related to retinal blood vessels and fundus.
  • Patent Document 2 In order to further generalize the above-mentioned detection device, detection of arteriosclerosis that can synchronize a biological signal and a fundus image on the computer screen, which is one of the most important and difficult processes.
  • Patent Document 1 and Patent Document 2 described above are limited to detecting retinal vascular sclerosis, and can only indirectly detect a precursor of atherothrombotic cerebral infarction. It is difficult to grasp even cerebral infarction and systemic economy class syndrome.
  • the present inventor has found that the above problem can be solved by providing the following retinal information diagnostic system.
  • the present inventor firstly includes the following (1) and (2), and provides a retinal information diagnosis system (hereinafter also referred to as a first present system) for detecting an infarction in a retinal blood vessel. It was found that the problem can be solved.
  • Imaging means for capturing a retinal image of a subject (2) A retinal blood vessel is identified in the retinal image photographed by the photographing means (1), a region where blood flow in the retinal blood vessel is substantially not detected is detected, and the number or presence or absence of the poor blood flow region (1) an infarct detection means for detecting an infarction in the retinal blood vessel of the subject in association with the infarction in the retinal blood vessel.
  • the “system” is not limited to the “device” in the narrow sense provided with the above-described means (1) and (2) as a unit, but these means (1) and (2) are the same or the same. Including the cases where the individual mechanisms within each means work in concert with each other to achieve the goal of “detection of retinal vascular infarction”, despite being spatially distinct It is a concept. Note that, even when the number of means constituting this system varies depending on the mode of the present system, the “system” is a concept including “apparatus” in the same manner. In addition, the “region where blood flow in the retinal blood vessels is not substantially recognized” may be referred to as a “blackout region”.
  • Imaging means As a retinal image photographing means, a camera having a mechanism capable of photographing the retina (specifically, a so-called fundus camera may be mentioned: an analog camera or a digital camera) may be mentioned.
  • the period of a human biological signal is normally about 0.6 to 1.0 seconds, and is preferably 0. It is preferable that the shutter is lowered at a frequency of at least once every 4 seconds, and that the time difference between the time when the shutter is lowered and the time of exposure is as short as possible. Therefore, a digital camera using an image sensor such as a CCD that is technically easy to satisfy such conditions is preferable.
  • detecting a retinal image with a digital video camera capable of continuously obtaining digital image information is suitable for synchronizing the retinal image on a computer screen. That is, as one of the most preferable aspects of the present system, the detection of the retinal image in this system is based on the state in which the retinal blood vessels are substantially identical (the blood vessel diameter is substantially By selecting and extracting the same images, it is possible to detect retinal blood vessel infarction with high accuracy.
  • an aspect of using software capable of providing a retinal image synchronized with the biological signal by extracting a still image of the retina synchronized with the biological signal on a display screen of the computer is also an excellent aspect. Can be mentioned.
  • the SLO is a scanning laser ophthalmoscope, which is an inspection device that can observe a state of a thin blood vessel and an enlarged affected part by scanning the fundus with a laser.
  • SLO high-resolution processing using a plurality of images can be performed as necessary.
  • the procedure for synchronizing with a biological signal is the same as that of the above fundus camera or digital video camera.
  • a captured moving image of a retinal image is, for example, a DV terminal (media converter is also possible), IEEE1394 card, EZDV (Canopus), DVRapter (Canopus), DVRex (Canopus).
  • the digital information can be taken into a computer through a DV capture card or the like.
  • Encoding including such compression can be performed by following an encoding method such as MPEG or MP3.
  • the compressed / encoded data is decompressed partly or entirely using existing compression / decompression technology (for example, compression / decompression technology developed by Celartem) as necessary. Can be used.
  • the digital synchronization data obtained in this way can be stored, for example, on a magnetic tape, magnetic disk, CD-ROM, MO, DVD-R, USB chip, or the like.
  • the first aspect of the present system is suitable when a digital video camera is used as the photographing means (1).
  • Infarct detection means (2) ( Blackout area )
  • the infarction detection means (2) detects a blackout region in the retinal image photographed by the photographing means (1), and the number or presence, location, or degree of the blackout region and the retinal blood vessel.
  • the retina is a transparent tissue that is rare in the human body, including the retinal vascular wall tissue. Therefore, it is usual that the part where the retinal blood vessel exists in the fundus image of the subject is observed with the color of blood flowing inside the blood vessel.
  • the blood flow in that portion is interrupted, which is recognized as a poor blood flow region in the retinal blood vessel. That is, the retinal blood vessels ahead of the infarcted part are observed as if they disappeared or are observed in a discolored state.
  • a poor blood flow region is the “blackout region” described above.
  • the color component in the region where the retinal blood vessel exists flows into the retinal blood vessel. It is possible to specify the location, presence or absence, or degree of the region that is outside the range of the value in the state of being.
  • the color component for example, RGB (R: red, G: green, B: blue) component
  • RGB red, G: green, B: blue
  • the color of the retinal blood vessel appears darker than the surrounding tissue due to the flowing blood color (in other words, the pixel values of the RGB components are generally low), so when blood is interrupted in the retinal blood vessel, Observation is performed in a state where the pixel values of the RGB components in the subsequent blackout region (that is, the evaluation values of the RGB components in each pixel) are increased overall.
  • the region of the retinal blood vessel beyond the infarcted portion becomes transparent, and is observed as the color of the tissue other than the retinal blood vessel, for example, the color of the melanin pigment contained in the retinal pigment epithelium layer or choroid.
  • the reduction rate of the area of the retinal blood vessels between multiple images or the reduction rate of the blood vessel width in the length direction of the retinal blood vessels in a single image is normal Observed in a state exceeding the range assumed in the state. Therefore, by using these characteristics, it is possible to specify the location, presence, degree, or number of blackout regions.
  • the identified blackout region indicates the presence of an infarction in the retinal blood vessel of the subject, and the location, presence, degree, and number of the infarct can be detected.
  • the G component that is, the green component
  • the G component has a higher contrast between the retinal blood vessels and the surrounding tissues than the R (red) component and B (blue) component, and these three primary colors. It is preferable to use only the green component rather than performing color component analysis by mixing them in terms of highly accurate analysis.
  • color component analysis is performed by mixing the R component and the B component, there is a tendency that unevenness in the distribution probability occurs or a problem such that the unevenness should exist but is too uniform.
  • auxiliary processing such as contrast enhancement processing, gray scale processing, or black and white reversal processing can be additionally performed. These auxiliary processes can further clarify the retinal blood vessels.
  • the inventor secondly includes the following (1) to (3) and detects an infarction in a retinal blood vessel (hereinafter also referred to as a second main system. "" Unless otherwise specified, means both the first system and the second system.) It has been found that the above problem can be further solved by providing .
  • a biological signal detection means for detecting a biological signal of a subject
  • Imaging means for capturing the retinal image of the subject in (1) in synchronization with the biological signal detected by the biological signal detection means (1)
  • a retinal blood vessel is identified in the retinal image photographed by the photographing means (2), a region where blood flow in the retinal blood vessel is substantially not detected is detected, and the number or presence or absence of the poor blood flow region
  • an infarct detection means for detecting an infarction in a retinal blood vessel of a subject in association with an infarction in a retinal blood vessel.
  • the second present system is characterized in that “biological signal detection means (1)” that is not permitted in the first present system is recognized as an essential configuration.
  • the imaging means (2) has a great feature that “synchronization with a biological signal” is recognized as an indispensable configuration, which is not recognized by the imaging means (1) in the first system.
  • the infarct detection means (3) is substantially the same as the infarct detection means (1) of the first present system.
  • the second present system is an aspect in which synchronization of a biological signal and a retinal image is essential, and is particularly suitable when a still image photographing unit (fundus camera or the like) is used. However, it is one of the preferable modes to perform the synchronization for a moving image using a digital video camera or the like because an image can be selected based on a stable timing.
  • a “biological signal” is a continuous signal having a constant rhythm that a living body spontaneously generates along with its life activity. Specifically, a pulsating signal of a heart or an artery, or these pulsating signals. Examples of the signal generated accompanying the signal include arterial blood oxygen saturation (SpO 2 ). Therefore, the “biological signal detection means” means a means for detecting by replacing these biological signals with electrical signals or the like. Specifically, if the biological signal is a signal accompanying the heartbeat, it is a biological signal detected by an electrocardiograph, and if it is a blood vessel beat, a pulse indicating a pulse wave detected by the pulse wave meter It is a wave signal.
  • the pulse wave signal examples include a fingertip pulse wave, a pulse wave in the orbital artery, and a pulse wave in the carotid artery. If the biological signal is arterial blood oxygen saturation, a pulse oximeter signal is applicable. All of these can detect a desired biological signal by performing a conventional method.
  • an electrocardiogram signal that is a heart pulsation signal can select any electrocardiogram signal in an established pattern on the electrocardiogram, but is preferably a signal that can be grasped as an established wave pattern.
  • any wave pattern of P wave, Q wave, R wave, S wave, or T wave can be selected, and R is a pattern signal at the stage of discharging blood from the heart toward the body. It is preferred and realistic to select a wave or a T wave that indicates the recovery process of ventricular excitement.
  • the guidance method for obtaining an electrocardiogram signal from the subject is not particularly limited, and can be selected from so-called “standard 12 leads” or the like.
  • the R wave is selected as the wave pattern of the electrocardiogram signal
  • the electrocardiogram signal detected by the electrocardiogram signal detection means is sensed, and a specific pattern signal is extracted as an electric signal from the sensed electrocardiogram signal. It is a premise to synchronize with (2). Also, it is possible to perform appropriate processing such as amplification processing, correction processing, trimming processing, etc. on such an electrocardiogram signal as necessary.
  • the pulse wave signal can be measured as a change in blood flow by, for example, irradiating the pulse wave detection portion with an LED and measuring the transmitted light with a photodiode.
  • the volume pulse using an ultrasonic Doppler (a method in which an ultrasonic echo is applied to a blood vessel and a blood flow rate component is obtained from the Doppler effect observed in the reflected wave: for example, an ultrasonic color Doppler method) Waves can be detected.
  • Such an ultrasonic Doppler is preferably used for the retinal artery.
  • the pulse wave signal obtained in this manner is extracted as a specific pattern signal in the same manner as the above-described electrocardiogram signal, and it is assumed that the pulse wave signal is synchronized with the imaging means (2) described later. Furthermore, it is possible to perform an appropriate process on the pulse wave signal as necessary, as in the case of the above-mentioned electrocardiogram signal.
  • SpO 2 can be obtained by subtracting components (such as veins and tissues) that are not pulsating from the total light absorption component. From the light emitting part of the sensor (consisting of a light emitting part and a light receiving part) attached to the probe of the pulse oximeter, two wavelengths of red light and infrared light are alternately emitted at a frequency of several hundred times / second. The SpO 2 can be measured over time based on the signal obtained by subtraction calculation as described above.
  • the SpO 2 displayed on the pulse oximeter displays the average value of SpO 2 for a few seconds, but the “pulse oximeter pulse signal” used in the second system is like this It is not an average value but a pulse wave signal obtained directly from the sensor, and can be said to be a type of the pulse wave signal.
  • the pulse wave signal is obtained as a weak electric signal, and it is possible to perform appropriate processing as necessary, as described above.
  • Shooting means (2) “Synchronization with the biological signal detected by the biological signal detection means (1)” means that the biological signal detection means (1) is operated in response to a specific phase in the biological signal at a fixed timing. means. For example, it means that the retinal image detection mechanism is operated at a certain timing from any time point in one wave unit constituting a biological signal such as an electrocardiogram signal or a pulse wave signal, for example, from the rising point of the wave unit. To do. This timing is not particularly limited as long as it is kept constant and is shorter than the timing at which the same pattern of the biological signal is generated again.
  • the moving image data taken into the computer and the biosignal data are combined in parallel as described in the photographing means (2) in the first system.
  • the moving image data of the retinal image and the biological signal can be synchronized in the same frame, and the moving image data of the retinal image and the digital synchronization data of the biological signal can be obtained.
  • the synchronization data can be compressed and stored in an electronic medium as in the first system (1).
  • the infarct detection means (3) itself in the second main detection method is substantially the same as the infarction detection means (2) in the first main detection method as described above, but the fundus is synchronized with the biological signal. It is characterized in that retinal blood vessel infarction is detected based on the image.
  • the system preferably includes means for measuring and recording the blood pressure of the subject at the time of detecting an infarct in the retinal blood vessel. It is known that the blood flow in the retinal blood vessels varies depending on the blood pressure level. For example, the system detects retinal blood vessel infarction using this system, compares the blood pressure at each continuation, and Evaluation can be made. For example, by measuring the blackout region at the lowest blood pressure among the measured values, it is possible to evaluate infarcts in a situation where blood does not flow easily from the blood pressure of the subject, and detection of infarction of retinal blood vessels Positive criteria can be set low (easy to detect). On the other hand, when the state of blood flow with the highest blood pressure is used as a reference, the reference for infarction of the retinal blood vessel can be set high (hard to detect).
  • the infarction detection means (2) or (3) of the present system includes means for determining whether the retinal blood vessel is an artery or a vein when the visible portion of the retinal blood vessel is specified by color component analysis. be able to. By discriminating between arteries and veins in this way, it is possible to determine whether the blackout accompanying infarction is biased to either the network artery or vein, or whether both are equally recognized. If the infarct is unevenly distributed in the retinal vein, for example, the risk of venous infarction, such as economy class syndrome, is increased. This suggests that the risk of arterial cerebral infarction is increased.
  • fundus images are taken before and after the administration, and among the retinal blood vessels in each fundus image, only the retinal vein is noticed and the blackout region is selected.
  • the reduction rate of the number of blackout regions that is, the degree of infarction elimination
  • the infarction detection means (2) or (3) determines whether the retinal blood vessel is an artery or a vein when the visible portion of the retinal blood vessel is specified by color component analysis.
  • the retinal blood vessels determined to have an infarction after correlating the number or presence, location, or degree of the poor blood flow region of the retinal artery or retinal vein with the infarction in the retinal blood vessel If it is an artery, there is a medication means to administer a drug that selectively acts on the artery, or if the determined retinal blood vessel is a vein, a drug that selectively acts on the vein.
  • a dosing effect evaluating means for evaluating the effect of dosing by the dosing means based on the result of infarct detection by the infarct detecting means (2) or (3) before and after the dosing by the dosing means.
  • the “medication means” refers to an arterial or venous subject automatically in response to the signal indicating the type of retinal blood vessel in which the infarction has occurred, by means of injection, oral or inhalation.
  • the signal can be visually or audibly shown to the system administrator to indicate the function of the mechanism that shows the optimum type of medication.
  • a plurality of retinas for each RGB Analyzing the color component value of the blood vessel and comparing the G component value of each blood vessel with each other, or considering that the range to which the color component value of the artery and vein belongs differs, Calculations for determining the arteriovenous by storing in advance the ranges to which the color component values of each arteriovenous belong, and comparing the stored ranges with the analysis results of the color component values of a plurality of retinal blood vessels Apparatus.
  • detection means capable of detecting retinal blood vessel infarction and diagnosing cerebral infarction or infarction throughout the circulatory system regardless of whether acute or chronic is provided as a detection system based on a detection device.
  • FIG. 1 It is a block diagram which shows the structure of the retinal information diagnostic system which concerns on embodiment A of this invention. It is a flowchart which shows the process in the infarct detection part 14 which concerns on embodiment A of this invention.
  • FIG. 10 is a flowchart showing processing in an infarct detection unit 14 according to Embodiment B.
  • FIG. 10 is a top view of a retinal blood vessel showing how the retinal blood vessel becomes fibrotic in embodiment C.
  • 10 is a flowchart showing processing in an infarct detection unit 14 according to Embodiment D. It is a top view of the retinal blood vessel which shows a mode that the vein around the artery of a retinal blood vessel meanders.
  • 18 is a flowchart showing processing in an infarct detection unit 14 according to embodiment E.
  • Infarct detection means In particular, the infarct detection means (2) or (3) described above has some typical aspects in order to detect a blackout region efficiently and accurately.
  • the rate of change in the width with respect to the length direction of the blood vessel in the vicinity of the front side of the distal portion of the visible portion is substantially blood in the retinal blood vessel.
  • a mode in which the case where the blood vessel ahead of the distal end is in an infarct state is used when the value is outside the range of the limit value indicating the state in which the flow is recognized.
  • the “near side of the tip of the visible part of the retinal blood vessel” means the vicinity of the visible part starting from the beginning of the blackout region of the retinal blood vessel, and is often upstream of the blood flow. To the side.
  • the “blood vessel length direction” means the direction of blood flow in the blood vessel, and the “width” means the blood vessel width of the retinal blood vessel.
  • the rate of change of the width with respect to the length direction is within a predetermined range.
  • a normal retinal blood vessel is recognized as a taper at a substantially constant rate along the direction of blood flow at the tip. Therefore, when the change rate of the blood vessel width is outside the range of the limit value indicating the state in which substantial blood flow is recognized in the retinal blood vessel, it can be specified as a blackout region indicating infarction.
  • the retinal blood vessel ahead of the sudden change portion of the change rate of the blood vessel width is interrupted because the blood does not flow completely due to infarction, or the cross-sectional area of the retinal blood vessel through which the blood flows becomes smaller due to atheroma etc.
  • the range of color components of the retinal blood vessels and other surrounding tissues that are recognized is determined for each photographed fundus image, and these individual results are taken into consideration and the "limit of color components that are considered to allow blood flow" It is possible to determine an appropriate limit of the change rate of the blood vessel width on the basis of the limit regarding the color component.
  • the blood flow is substantially recognized means a state in which the blood flow can be constantly recognized, for example, a state in which the blood flow is recognized even when the retinal blood vessels are contracted. Is.
  • this rate of change is generally from ⁇ 30 to ⁇ 50%, that is, “to a decrease in blood vessel width 3 to 5 with respect to the distance 10 in the length direction of the retinal blood vessels” as the normal range limit. Is possible. This shows the above-described “recognition of substantial blood flow in the retinal blood vessel” when the reduction rate of the blood vessel width with respect to the distance in the length direction is larger than the limit value set in the range of the change rate. It means that it can be “out of the limit value range”.
  • the limit value of the change rate of the width of the visible portion relative to the length direction of the blood vessel in the vicinity of the front side of the “tip portion of the visible portion of the retinal blood vessel” When the angle is about 90 degrees to about 180 degrees with respect to the direction toward the inside of the blood vessel, an index indicating the presence of infarction in the blood vessel ahead of the distal end portion can be used.
  • the angle with respect to the length direction of these retinal blood vessels is expressed as “about” because the angle can be finely adjusted according to the convenience of the user of the system. This is because it is preferable to enable adjustment.
  • the above “about” means to give a width of about ⁇ 10 degrees, preferably about ⁇ 5 degrees with respect to the above-mentioned angle.
  • the criterion for the rate of change is “the concave tip shape” of the “tip portion of the visible portion of the retinal blood vessel”, that is, “the state of being recessed in the R shape on the inside or the flat shape”. Is recognized as a blackout area beyond the tip.
  • the tip portion has a “convex round shape”, there is a strong possibility that the retinal blood vessel that is the target of the infarction is simply lurking in the back.
  • the infarction in the retinal blood vessel can be detected based on the tendency of the veins around the artery to meander.
  • This second aspect can be performed separately or in combination with the first aspect described above.
  • This combination mode is preferable because it can improve the accuracy of detection of infarction of a network vessel.
  • the venous meandering is considered to be a result of changes in the veins acting as a saucer for the supply of enzyme nutrition against chronic ischemia in the surrounding tissues when the artery of the retinal blood vessel is infarcted.
  • Blood column reflex is a phenomenon in which when a blood vessel is observed in a fundus examination, illumination is reflected on the blood in the blood vessel and the center of the blood vessel appears to shine.
  • the “blood column reflection region” may include dark red blood portions in both sides of the blood column reflection.
  • the limit value is a value determined in advance by experiment, experience, or simulation as a range in which the rate of change in the absence of infarction falls, and may be appropriately corrected for each fundus image, but is generally ⁇ 30 to ⁇ 50. %, That is, “to a decrease of the blood column width 3 to 5 with respect to the distance 10 in the length direction of the retinal blood vessel”.
  • RGB component values can be converted into luminance values as preprocessing for “luminance analysis”.
  • organic fiber formation (silvering) of retinal blood vessels is specified by color component analysis, and the organic fiber formation part is used as an index of an infarct state.
  • This fourth aspect can be performed separately from or in combination with the first to third aspects described above. This combination mode is preferable because it can improve the accuracy of detection of infarction of a network vessel.
  • This organic fibrosis part is a chronic vascular ischemic region and is a part that has been ischemic over a long period of time. Therefore, the fourth aspect is a suitable index for specifying the current state of the subject and detecting the progress of the infarction of the retinal blood vessel from the past to the present.
  • the detection of organic fiber formation is a specific phenomenon that appears in organic fiber formation by color component analysis, specifically, it is silver or white compared to the surrounding tissue, that is, each color component of RGB It can be detected as an index that the value variation is smaller than that of the surrounding tissue.
  • the system stores the data indicating the progress and result of the diagnostic process at different time points in the same subject in the retinal information diagnostic system, performs the data comparison at different time points, and uses the comparison data as an index for the latest Means for diagnosing the degree of progression of retinal blood vessel infarction at the time may be added.
  • the “data to be compared at different time points” includes individual or all combinations of the data provided in the first to fourth aspects described above. It is preferable that data representing the shape of the retinal blood vessel is included, and the “means for diagnosing the progress of the infarction of the retinal blood vessel at the latest time point” includes the tip of the visible portion of the retinal blood vessel provided by the shape data. Compare the past data with the latest data on the rate of change of the width in the length direction of the blood vessel in the vicinity of the near side, and compare the limit value range that indicates the state of substantial blood flow in the retinal blood vessels. It is preferable to include means including a step of detecting a relative change and using the change as an index of the progress degree of retinal blood vessel infarction.
  • the above-described detection of infarction by specifying organic fiber formation (silvering) of retinal blood vessels by color component analysis is one of the preferred embodiments for use in the detection over time. That is, the silver-lined portion is one in which the blackout region of the retinal blood vessels changes over time and becomes silver-lined. In the subsequent detection, the degree of progression of retinal blood vessel aging (infarction) can be confirmed by detecting silvering.
  • the retinal vascular infarction indicated by the first blackout is not healed, rather The possibility of further progress is shown, and when the normal part of the first time is silvered by subsequent detection, it indicates that the infarction of the retinal blood vessel has progressed very prominently and seriously.
  • the above-mentioned “data to be compared at different time points” is used to colorize the organic fibrosis of the retinal blood vessels at different time points at which the diagnostic process is performed, other than the first time point. It is possible and preferred to include an embodiment that includes data obtained by detection means that is specified by component analysis and that uses the organic fiberized portion as an index of being infarcted.
  • the “data to be compared at different time points” is an area corresponding to the blood color in which blood flow is substantially recognized in the retinal blood vessels obtained by color component analysis, A case where the latest area data is decreased as compared with the past area data can be regarded as an infarct tendency of the retinal blood vessel.
  • Embodiment A is an example showing a basic configuration of the present system
  • FIG. 1 is a block diagram of the embodiment A.
  • the retinal information diagnostic system 10 includes a biological signal detection unit 11, an imaging unit 13, and an infarct detection unit 14.
  • the biological signal detection unit 11 includes an electrode sensor 111, an amplification unit 112, and an output unit 113.
  • the electrode sensor 111 is composed of, for example, a piezoelectric element or an infrared light receiving / emitting element, and is attached to a biological part selected according to the type of means for detecting the biological signal of the subject and is derived. This is a mechanism for detecting biological signals (for example, heart and artery pulsation signals and signals generated accompanying these pulsation signals).
  • the amplifying unit 112 is configured by, for example, a filter amplifier and selectively amplifies the biological signal detected by the electrode sensor 111.
  • the amplification unit 112 may be provided with an A / D conversion mechanism for digitizing a biological signal that is an analog signal, if necessary.
  • the output unit 113 is a mechanism (for example, an output terminal) for outputting the biological signal selectively amplified by the amplification unit 112 toward the imaging unit 13.
  • the imaging unit 13 includes an input unit 131, a waveform signal sensing / transmitting unit 132, a shutter mechanism 133, a light receiving unit 134, a photoelectric conversion unit 135, and an output unit 136.
  • the input unit 131 is a mechanism (for example, an input terminal) for inputting a selectively amplified biological signal output from the output unit 113.
  • the waveform signal sensing / transmitting unit 132 is a mechanism that senses a biological signal input from the input unit 131 and transmits this to the shutter mechanism 133 as an appropriate ON / OFF signal.
  • the shutter mechanism 133 detects the “ON” signal of the ON / OFF signal (for example, a specific pulse signal corresponding to a biological signal, for example, an R wave or a T wave for an electrocardiogram signal).
  • the light receiving unit 134 is operated, and means for suppressing the operation of the light receiving unit 134 is provided for the “OFF” signal (for example, a state other than the pulse signal). That is, the light receiving unit 134 can operate only at a timing synchronized with a specific pulse signal accompanying a biological signal and can photograph the fundus of the subject.
  • the light receiving unit 134 includes a mechanism for photographing the fundus of the subject, such as an eyepiece lens and a light source (for example, not only visible light but also appropriate ultraviolet light or appropriate red light, which is included in a normal fundus camera.
  • a light source for example, not only visible light but also appropriate ultraviolet light or appropriate red light, which is included in a normal fundus camera.
  • the light source may be an external light source
  • an alignment mechanism for example, not only visible light but also appropriate ultraviolet light or appropriate red light, which is included in a normal fundus camera.
  • the light source may be an external light source
  • an alignment mechanism for example, not only visible light but also appropriate ultraviolet light or appropriate red light, which is included in a normal fundus camera.
  • an angle of view adjustment mechanism for example, optical information of a fundus image captured in synchronization with a specific biological signal is converted into electrical information in a photoelectric conversion unit 135 including a CMOS image sensor or a CCD image sensor (typically, digital information).
  • the electrical information may be output from the output unit 136 and input to the input unit 141 of the infarct detection unit 14 via a wired, wireless, or recording medium.
  • the electrical information of the fundus image may be output to a display device other than the infarct detection unit 14, for example, a monitor image or a printer image, and the fundus image at the time of photographing may be provided to the measurer in real time.
  • the photoelectric conversion unit 135 is provided with an A / D conversion mechanism for digitizing the electrical information signal of the fundus image, which is an analog signal, and generating data of the fundus image.
  • the output unit 136 is also a mechanism (for example, an output terminal) for outputting fundus image data to the infarct detection unit 14.
  • the output unit 136 corrects the optical characteristics of the imaging unit 13 and the shooting situation (correction of lens aberration, tilt correction, etc.) for the generated fundus image data, and divides and captures images. May perform geometric correction such as compositing images.
  • the infarct detection unit 14 includes an input unit 141, a storage unit 142, and an analysis unit 143.
  • the infarct detection unit 14 may be configured to be incorporated in the imaging unit 13 as well as a single independent configuration such as a personal computer.
  • the input unit 141 is a mechanism (for example, an input terminal) for inputting fundus image data output from the output unit 136 to the infarct detection unit 14.
  • the input unit 141 and the output unit 136 are connected by a signal line or a communication line.
  • a communication line a network such as the Internet may be used.
  • the function as the infarct detection unit 14 can be provided by an application service provider (ASP) system.
  • ASP application service provider
  • the storage unit 142 is, for example, a large-capacity storage device such as a hard disk, and sequentially stores input fundus image data.
  • the fundus image data is stored in association with, for example, the identification information of the subject and the photographing date and time.
  • the analysis unit 143 is a known computer, for example, and includes a microprocessor and peripheral devices such as a RAM and a ROM necessary for the operation thereof.
  • ROM of the analysis unit 143 retinal blood vessels are captured in the photographed fundus image by performing predetermined image processing and pattern recognition processing on appropriate software, for example, data of the fundus image stored in the storage unit 142. Identifies the location, presence, or degree of the blackout region, where the color component is different from the value when blood flows through the retinal blood vessels.
  • software including a program for detecting an infarction in the retinal blood vessel is stored in advance.
  • the retinal information diagnostic system 10 can detect an infarction in the retinal blood vessel.
  • the imaging unit 13 and the infarct detection unit 14 can be provided except the biological signal detection unit 11.
  • imaging of the fundus is performed at an arbitrary timing, and the infarct detection unit 14 extracts a fundus image having a phase matching from a plurality of fundus images, and examines the extracted image, thereby The retinal blood vessel infarction can be detected in the same manner.
  • the analysis unit 143 reads the fundus image data stored in the storage unit 142 into the main memory (step S1).
  • the analysis unit 143 may read the fundus image data input from the input unit 141 as it is.
  • the analysis unit 143 extracts retinal blood vessels from the read fundus image data (step S2). At this time, by analyzing the color component for the data of the read fundus image, it is determined for each pixel or for each predetermined section whether or not it is a color component region in a state where blood flows in the retinal blood vessels, It is recommended to extract retinal blood vessels.
  • the “color component in a state where blood flows through the retinal blood vessels” will be supplemented with reference to FIG.
  • FIG. 3 is a diagram partially showing fundus images when (a) RGB components are mixed, (b) only G components, and (c) only G components after contrast enhancement processing.
  • the color component used may be only the G component of the RGB components. Then, retinal blood vessels can be extracted with higher accuracy than when color component analysis is performed by mixing R and B components. In addition, since such color components vary depending on shooting conditions, characteristics of the imaging unit 13, and the like, there is a possibility that the extraction results may vary. Therefore, a predetermined hue correction may be performed before the color component analysis. . Further, before and after the color component analysis, for example, contrast enhancement correction based on a color component difference between two pixels in fundus image data may be performed. Then, as can be seen from a comparison between FIG. 3A and FIG. 3B, the color component in the state in which blood flows through the retinal blood vessels does not have to be an absolute value. It may be determined as a relative value. In addition, a known region of interest extraction technique may be applied.
  • FIG. 4 is a schematic diagram showing the fundus image and the tip of the retinal blood vessel.
  • the left side of FIG. 4 shows a state in which retinal blood vessels 101 (more specifically, retinal arteries and retinal veins) are formed radially from the optic disc 102 on the fundus.
  • the retinal blood vessel 101 is branched as it goes in the blood vessel progression direction.
  • the right side of FIG. 4 shows a state in which the periphery of the distal end portion of the retinal blood vessel 101 is enlarged.
  • a region surrounded by a dotted line indicates the tip of the branched retinal blood vessel 101.
  • “with BO” in the tip portion shown on the right side of FIG. 4 means a tip portion with a blackout region ahead, and “without BO” means that the blackout region is over there. Means no tip.
  • the analyzing unit 143 identifies the tip of the extracted retinal blood vessel in the fundus image data (step S3).
  • This tip can be identified by pattern recognition processing that searches for the shape of the tip, or processing that scans the retinal blood vessels along the extension direction.
  • the tip portion of all of the fundus image may be specified, or for simplification, the tip portion included in the specimen region may be specified using a predetermined fundus region as a specimen.
  • the analysis unit 143 calculates the change rate of the blood vessel width with respect to the traveling direction of the retinal blood vessels (step S4).
  • FIG. 5 is a characteristic diagram showing the change rate of the blood vessel width with respect to the traveling direction of the retinal blood vessel, which is measured in the fundus image.
  • FIG. 5A shows the vascular width with respect to the vascular progression direction of the retinal blood vessel in the vicinity of the tip of the retinal blood vessel.
  • FIG. 5B shows the change rate of the blood vessel width corresponding to FIG.
  • “BO”, that is, a tip portion with a blackout region ahead is indicated by a dotted line
  • BO that is, a tip portion without a blackout region is indicated by a dotted line. Yes.
  • FIG. 5 shows the change rate of the blood vessel width with respect to the traveling direction of the retinal blood vessel, which is measured in the fundus image.
  • FIG. 5A shows the vascular width with respect to the vascular progression direction of the retinal blood vessel in the vicinity of the tip of the retinal blood vessel.
  • FIG. 5B shows the change rate of the blood vessel width corresponding to FIG.
  • the blood vessel width is gradually attenuated as the blood vessel reaches the front end at the “BO-free” front end portion, and as shown in FIG. 5 (b), the blood vessel width is reduced.
  • the rate of change is within a predetermined range. This is the normal state of the tip of the retinal blood vessel.
  • the blood vessel width is abruptly attenuated or interrupted, and as shown in FIG. It has been found by the present inventor that the rate of change deviates from the aforementioned predetermined range (generally decreases more rapidly than ⁇ 30 to ⁇ 50%).
  • the analysis unit 143 confirms whether or not the change rate of the blood vessel width with respect to the traveling direction of the retinal blood vessels is within a predetermined range for each distal end portion (step S5). If the change rate of the blood vessel width is within the predetermined range (step S5: Yes), it is determined that the tip portion is not a blackout region (step S6). That is, it is determined that there is no infarction at the distal end portion (step S7).
  • step S4 (1) the analysis unit 143 calculates the rate of change of the blood vessel width with respect to the direction of travel of the retinal blood vessels, but instead of or in addition to this, (2) the analysis unit 143 extracts Based on luminance analysis on the retinal blood vessels, a blood column reflection region that is reflecting the blood column is extracted as a region having a predetermined luminance value or more, and the width of the extracted blood column reflection region is changed with respect to the length direction of the retinal blood vessel.
  • the rate may be calculated (step S4).
  • the blackout region can also be identified by determining whether or not this result exceeds the above-described predetermined range in the rate of change in the blood column width (generally abruptly less than ⁇ 30 to ⁇ 50%). It is.
  • step S5 when the change rate of the blood vessel width deviates from the predetermined range (step S5: No), there is a high possibility that the tip portion is a blackout region.
  • the tip portion of the retinal blood vessel simply dives in the depth direction of the fundus (that is, the direction perpendicular to the light receiving surface of the light receiving unit 134), and may not be a blackout region. This possibility will be described with reference to FIG.
  • FIG. 6 is a top view and a side view of the tip portion of the retinal blood vessel showing the presence or absence of infarction according to the difference in shape.
  • the tip of the retinal blood vessel shown in FIG. 6B is only in the depth direction of the fundus and there is no infarction. . That is, in FIG. 6B as well, in FIG. 6C and FIG. 6D, the change rate of the blood vessel width deviates from the predetermined range, so that the tip portion is ahead in the blackout region. There is a risk of misjudging that there is.
  • the reason why the change rate of the blood vessel width deviates from the predetermined range is that there is an infarction as shown in FIGS. 6C and 6D, or FIG. As shown in FIG. 6 (b), it is necessary to discriminate whether there is no infarction and the tip of the retinal blood vessel is merely in the depth direction of the fundus.
  • the distinction may be performed with high accuracy by using together with a device that displays a cross section of a retina of OCT (Optical Coherence Tomography: OCT).
  • OCT Optical Coherence Tomography
  • the convex round shape means a gentle convex shape or a shape protruding in an R shape on the outside.
  • the change rate of the width of the visible portion with respect to the length direction of the blood vessel in the vicinity of the front side of the tip is about 90 degrees to about 0 degrees toward the inside of the blood vessel with respect to the length direction.
  • the concave round shape means a gentle concave shape or a shape recessed in an R shape inside.
  • the change rate of the width of the visible portion with respect to the length direction of the blood vessel in the vicinity of the front side of the tip is about 90 degrees to about 180 degrees toward the inside of the blood vessel with respect to the length direction.
  • the flat shape means a flat shape intermediate between the convex round shape and the concave round shape.
  • the change rate of the width of the visible portion with respect to the length direction of the blood vessel in the vicinity of the front side of the distal end portion is in the vicinity of 90 degrees toward the inside of the blood vessel with respect to the length direction.
  • the analysis unit 143 further determines whether or not the tip has a convex round shape (step S8).
  • step S8 when the distal end portion has a convex round shape (step S8: Yes), it is considered that the distal end portion of the retinal blood vessel is merely submerged in the depth direction of the fundus as shown in FIG. Therefore, it is determined that the tip part is not the blackout area (step S6). That is, it is determined that there is no infarction at the distal end portion (step S7).
  • the convex round shape as described above, only with the analysis result that the rate of change of the blood vessel width deviates from the predetermined range, it is determined that the distal end portion is not infarcted, and “hold”, Can also be processed (step S7).
  • step S8 when the tip portion is not a convex round shape (step S8: No), as shown in FIG. 6C or FIG. 6D described above, the tip portion is a blackout region. (Step S9). That is, it is determined that there is an infarction at the tip (step S10).
  • Embodiment B is an embodiment related to the above-mentioned “detection over time”, and the configuration and operation processing of the retinal information diagnosis system will be described below.
  • the structure may be the same as that of the above-mentioned embodiment A, the same reference numerals are given to the same structures, and detailed description thereof will be omitted as appropriate.
  • FIG. 7 is a flowchart showing processing in the infarct detection unit 14 of the embodiment B.
  • each fundus image data is preferably stored in the storage unit 142 as a file name associated with information on the subject and the photographing time, or stored in a database together with the correspondence information.
  • the analysis unit 143 extracts retinal blood vessels from each read fundus image data (step S22). Then, typically, the extracted shape and area of the retinal blood vessel are compared (step S23). In addition, without extracting the retinal blood vessel, a density histogram for each color component may be extracted for each fundus image data, and the similarity to the pattern of each histogram may be compared. From these, the presence or absence or degree of the blackout region is specified (step S24). For example, if the retinal blood vessel shapes extracted for the respective fundus image data are compared with each other and the shapes are different from each other, it can be specified that there is a blackout region.
  • Embodiment C is an embodiment relating to the fiberization (silvering) associated with the retinal blood vessel infarction described above, and the configuration and operation processing of the retinal information diagnostic system will be described below.
  • the structure may be the same as that of the above-mentioned embodiment A, the same reference numerals are given to the same structures, and detailed description thereof will be omitted as appropriate.
  • FIG. 8 is a top view of the retinal blood vessel showing how the retinal blood vessel becomes fibrotic in embodiment C.
  • the storage unit 142 accumulates fundus images taken for the same subject over time.
  • FIG. 8 illustrates a state in which a fundus image is taken for the same subject in January 2006, January 2007, and January 2008, and the data is stored in the storage unit 142. .
  • the analysis unit 143 identifies the silver lined region 102 by extracting a region of a color component corresponding to a color in which the retinal blood vessel is turned into a silver line from the fundus image data taken at each time.
  • the “color component corresponding to the color of the retinal blood vessel turned into a silver line” is a color that has been observed in advance in an experiment and may have a predetermined margin.
  • the analysis unit 143 is a fundus image in which a region at a position corresponding to the identified silvered region 102 is still detected as a blackout region from the fundus image accumulated in the storage unit 142,
  • the photographing time of the last photographed fundus image is specified. For example, in FIG. 8, no silver line area is extracted from fundus image data taken in January 2006 and January 2007, and only from fundus image data taken in January 2008. The silver line region is extracted.
  • the region at the position corresponding to the identified silvered region 102 is a fundus image that is still detected as a blackout region, and the photographing time of the last photographed fundus image is January 2007. is there. Then, with respect to the subject, it can be estimated that silvering occurred between January 2007 and January 2008.
  • Embodiment D is an embodiment relating to the meandering of the peripheral retinal vein accompanying the retinal artery infarction described above, and the configuration and operation processing of the retinal information diagnostic system will be described below.
  • the structure may be the same as that of the above-mentioned embodiment A, the same reference numerals are given to the same structures, and detailed description thereof will be omitted as appropriate.
  • FIG. 9 is a flowchart showing processing in the infarct detection unit 14 of the embodiment D.
  • the analysis unit 143 reads the fundus image data stored in the storage unit 142 into the main memory (step S1).
  • the analysis unit 143 extracts retinal blood vessels for each arterial and vein from the read fundus image data (step S32). Specifically, the color component in the state where arterial blood flows in the retinal blood vessels (also simply referred to as arterial color) and the color component in the state in which venous blood flows in the retinal blood vessels (simply simply the vein color) are also extracted separately.
  • the vein color typically has more blue components than the arterial color, but there are individual differences in the difference. Therefore, the operator of the apparatus designates the subject's artery and vein with a pointing device or the like while viewing the fundus image, and extracts the color component at the designated location, thereby registering the subject's arterial color and vein color in advance. You may keep it.
  • the analysis unit 143 specifies the tip of the retinal artery (that is, the artery of the retinal blood vessel) among the extracted retinal blood vessels in the fundus image data (step S33). Similar to the first embodiment, the distal end portion can be specified by pattern recognition processing for searching for the shape of the distal end portion or processing for scanning the retinal artery along the extension direction. Next, the tip portion of the retinal artery identified in this way is identified that is expected to be the blackout region (step S34). This technique may be the same as that shown in the first embodiment.
  • step S35 it is determined whether or not the retinal vein 104 around the tip of each retinal vein 103 is meandering. This is generally based on the tendency of the peripheral retinal veins to meander when the retinal artery is infarcted. Note that the “periphery of the front end” is a search range that is experimentally predetermined as the existence range of the meandering retinal vein observed based on the above tendency.
  • Whether or not the retinal vein is “meandering” can be determined by expressing the path of the retinal vein with an approximate curve and quantitatively and statistically evaluating the change in curvature of the curve. For example, it can be determined based on the degree of curvature dispersion at a plurality of points on the approximate curvature.
  • FIG. 10 is a top view of the retinal blood vessel showing how the veins around the artery of the retinal blood vessel meander. If the retinal vein around the tip of the tip that is expected to be the blackout region is not meandering (step S35: Yes), the tip beyond the tip is expected. On the contrary, it is determined that it is not a blackout region (step S6). That is, it is determined that there is no infarction at the distal end portion (step S7).
  • step S35 when the retinal vein around the tip portion is meandering (step S35: No), it is determined that the tip portion is a blackout region as expected (step S9). That is, it is determined that there is an infarction at the tip (step S10).
  • the retinal information diagnostic apparatus As described above, according to the retinal information diagnostic apparatus according to Embodiment D, it is possible to improve the accuracy when detecting an infarction in a retinal blood vessel.
  • Embodiment E is a mode in which a medication unit and a medication effect determination unit are added to the system, and the configuration and operation process of the retinal information diagnostic system will be described below.
  • the structure may be the same as that of the above-mentioned embodiment A, the same reference numerals are given to the same structures, and detailed description thereof will be omitted as appropriate.
  • FIG. 11 is a flowchart showing processing in the infarct detection unit 14 of the embodiment E.
  • the retinal vein has a higher expression rate in the blackout region than the retinal artery. This is thought to be due to the difference in pressure between the two and the difference in blood components.
  • the arterial blood component contains a lot of oxygen and nutrient components
  • the venous blood component contains a lot of carbon dioxide and waste components, so that the retinal vein is harder than the retinal artery (that is, , Which is likely to cause infarction).
  • a drug that has an effect of dissolving a waste product of venous blood components can be evaluated as follows.
  • fundus images are taken before and after a drug to be evaluated is administered to a subject, and data of each fundus image is stored in the storage unit 142. Then, at the time of evaluation, the analysis unit 143 reads the captured fundus image data into the main memory (step S41).
  • the analysis unit 143 extracts retinal blood vessels for each arterial and vein from the read fundus image data (step S42). Then, the analysis unit 143 identifies the tip of the retinal vein among the extracted retinal blood vessels in the fundus image data (step S43). Of the tip portions of the retinal veins thus identified, those that are expected to be the blackout region are identified for each fundus image taken before and after the medication by the medication means (step S44). ).
  • the number of blackout regions of the retinal vein is compared between fundus images taken before and after medication (step S45). Based on this comparison result, the effect of the administered drug can be evaluated (step S46). For example, if the number of blackout areas of the retinal vein has decreased after administration, it can be evaluated that the administered drug has the expected effect, and further how effective it is based on the degree of decrease. It can be evaluated (medication effect evaluation means).
  • steps S42 to S46 shown in FIG. 11 particularly show the case where the extracted retinal blood vessel is a vein, but it is naturally possible that it may be an artery. In the case where the extracted retinal blood vessel is an artery, the steps involved are exactly the same as S42 to S46 (not shown).
  • the “biological signal detection unit 11” is an example of the “biological signal detection unit” according to the present invention
  • the “imaging unit 13” is an example of the “imaging unit” according to the present invention
  • “Infarct detection unit 14" is an example of "infarct detection means” according to the present invention
  • the “storage unit 142” is an example of the “accumulating unit” according to the present invention.
  • “Analysis unit 143” is an example of "medication effect evaluation means” according to the present invention
  • the “analysis unit 143” is an example of “infarct risk estimation means” according to the present invention.
  • SYMBOLS 10 Retina information diagnostic system, 11 ... Living body signal detection part, 13 ... Imaging part, 14 ... Infarct detection part, 111 ... Electrode sensor, 112 ... Amplification part, 113 ... Output part, 131 ... Input part, 132 ... Waveform signal sensing Transmission unit 133 ... Shutter mechanism 134 ... Light receiving unit 135 ... Photoelectric conversion unit 136 ... Output unit 141 ... Input unit 142 ... Storage unit 143 ... Analysis unit

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Abstract

L'invention porte sur un système de diagnostic d'informations rétiniennes capable de détecter un infarctus vasculaire rétinien dans un sujet faisant l'objet d'un test, comprenant un moyen de photographie (13), qui photographie une image de fond d'œil du sujet testé et un moyen de détection d'infarctus (14) qui détecte un infarctus vasculaire rétinien en spécifiant l'emplacement, la présence ou l'absence, le degré, le nombre ou similaire de zones opaques dans lesquelles les composants de couleur des vaisseaux rétiniens se situent à l'extérieur de la plage de valeurs de l'état où le sang circule dans les vaisseaux rétiniens. Dans ce système de diagnostic, un infarctus vasculaire rétinien dans un sujet testé peut être détecté de façon simple et précise.
PCT/JP2009/060111 2008-06-04 2009-06-03 Système de diagnostic d'informations rétiniennes WO2009148067A1 (fr)

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