WO2015068495A1

WO2015068495A1 - Organ image capturing device

Info

Publication number: WO2015068495A1
Application number: PCT/JP2014/075886
Authority: WO
Inventors: 松田　伸也
Original assignee: コニカミノルタ株式会社
Priority date: 2013-11-05
Filing date: 2014-09-29
Publication date: 2015-05-14

Abstract

This organ image capturing device (1) comprises a data distribution acquisition unit and a detection unit (18). The data distribution acquisition unit captures an image of an organ of a living body, and acquires a horizontal-direction data distribution indicating the degree of unevenness on the surface of the organ. The detection unit (18) detects the thickness of the organ on the basis of the unevenness of the data distribution as acquired by the data distribution acquisition unit.

Description

Organ imaging device

The present invention relates to an organ image photographing apparatus for photographing an organ of a living body and detecting the thickness (degree of thickness) of the organ.

In oriental medicine, a diagnostic method (tongue diagnosis) for diagnosing a health condition or medical condition by observing the state of the tongue is known. In the tongue examination, the physical condition and health level are judged based on the color and shape of the tongue (more precisely, tongue and moss).

One of the diagnostic items in tongue examination is the size (thickness) of the tongue. Poor water metabolism leads to a so-called swollen state, bulging and thickening of the tongue (referred to as enormous). Conversely, when the blood flow is insufficient or the water is insufficient, the tongue becomes thin and thin (this is called thinning). These states are called water stagnation or tuna in Oriental medicine, and when it becomes severe, it becomes edema or dehydration.

Currently, these diagnoses are carried out by specialized doctors, but because they rely on experience and intuition, there are individual differences and poor objectivity.

Therefore, a system has been proposed in which a subject is photographed using a digital camera, and the features of the photographed image are digitized and recorded and diagnosed. For example, in Patent Document 1, a tongue is photographed with a camera to extract a region of interest such as a tongue apex, a tongue, a tongue base, or a tongue base, and an individual's health condition can be easily diagnosed based on a state change of the region of interest. I have to. In Patent Document 2, an index for diagnosing the state of blood or blood vessels is obtained by photographing the tongue with a camera and detecting the color and gloss of the tongue separately. Further, in Patent Document 3, polar coordinates with the center of gravity of the tongue as the origin are set, the variance of the radius for each angle (the distance between the center of gravity of the tongue and the point on the contour line) is calculated, and the tongue is based on the value of this variance. The outer shape (circularity) is determined. Specifically, when the variance value is small, it is judged that the tongue is enlarged (in plan view) and close to a circle, and when the variance value is large, the tongue is thinned (in plan view). Judged to be close to a triangle.

Japanese Patent No. 3854966 (see claim 1, paragraphs [0004], [0009], etc.) JP 2011-239926 A (refer to claim 1, paragraph [0028] etc.) Japanese Patent Laying-Open No. 2005-137756 (refer to claim 3, paragraphs [0071] to [0074], FIG. 5, FIG. 6, etc.)

However, Patent Documents 1 and 2 do not mention detection of the thickness of the tongue at all.

Also, the method of Patent Document 3 cannot accurately detect (determine) the thickness of the tongue. That is, there are round and thin tongues and thick and thick tongues depending on individual differences and how force is applied (force input condition), but Patent Document 3 determines the tongue thickness based on the dispersion value of the radius (distance). In this method, it is determined that the circle = hypertrophy and the triangle = thinness. Therefore, in the case of a tongue that is circular or thin, or a tongue that is both thick and triangular, the thickness of the tongue is erroneously determined.

There are individual differences in the outer shape of the tongue, and the outer shape and thickness of the tongue do not necessarily correspond. In addition, there is a muscular tissue inside the tongue, and the outer shape differs depending on the developmental state and how to apply force. The state where the tongue is thick is a so-called “swelling state” in which the muscle tissue contains a large amount of water. In this way, the external shape of the tongue varies depending on individual differences and how the force is applied. Therefore, in the diagnosis of health based on the tongue thickness, the thickness of the tongue is accurately detected regardless of the external shape of the individual tongue. It is necessary.

The present invention has been made to solve the above-described problems, and an object thereof is to provide an organ imaging apparatus capable of accurately detecting the thickness of an organ regardless of the outer shape of each organ. There is to do.

An organ image capturing apparatus according to an aspect of the present invention includes a data distribution acquisition unit that captures an organ of a living body and acquires a horizontal data distribution indicating a degree of unevenness on the surface of the organ, and the data distribution acquisition unit And a detecting unit for detecting the thickness of the organ based on the unevenness of the data distribution acquired in (1).

According to the above configuration, even when the external shape of an organ varies depending on individual differences and how to apply force, the thickness of the organ can be accurately detected regardless of the external shape of the individual organ.

It is a perspective view which shows the external appearance of the organ imaging device which concerns on one Embodiment of this invention. It is a block diagram which shows the schematic structure of the said organ image imaging device. It is explanatory drawing which shows the positional relationship of the illumination part of the said organ imaging | photography apparatus with respect to imaging | photography object, a light projection part, and an imaging part. It is explanatory drawing which shows the picked-up image of the tongue by the said imaging part, the edge extraction filter, and the outline of the tongue extracted from the said picked-up image using the said edge extraction filter. It is a perspective view which shows the schematic structure of the said light projection part. It is explanatory drawing which shows the state which is projecting linear light on the surface of a tongue by the said light projection part. It is explanatory drawing which shows the picked-up image when the said light projection part image | photographs the linear light projected on the tongue surface by the said light projection part, and the cross-sectional shape of a tongue, when a tongue is thin and when it is thick . It is explanatory drawing which shows the relationship between the thickness of a tongue, and the movement by the muscle of a tongue, and the height distribution of the horizontal direction of a tongue surface. It is explanatory drawing which shows the one part area | region approximated with a polynomial with the said height distribution. Photographing the tongues of multiple people, acquiring the horizontal height distribution of the tongue surface, and approximating a partial area with a polynomial, the second-order coefficient of the above polynomial, and the Chinese medicine for each tongue It is explanatory drawing which shows the relationship with the finding of tongue thickness when actually performing a tongue examination. It is a flowchart which shows the flow of operation | movement in the said organ imaging device. It is explanatory drawing which shows typically the other setting method of the said area | region approximated with a polynomial in the said height distribution. It is explanatory drawing which shows distribution of the RGB image data of the picked-up image in the horizontal direction which passes along the approximate center of the up-down direction of the surface of a tongue, when a tongue is thin and is thick. It is explanatory drawing which shows typically the relationship between the planar shape and cross-sectional shape of a tongue.

An embodiment of the present invention will be described below with reference to the drawings. In this specification, when the numerical range is expressed as A to B, the numerical value range includes the values of the lower limit A and the upper limit B.

[Overall configuration of organ imaging system]
FIG. 1 is a perspective view showing an external appearance of an organ image photographing apparatus 1 of the present embodiment, and FIG. 2 is a block diagram showing a schematic configuration of the organ image photographing apparatus 1. The organ image capturing apparatus 1 captures an organ of a living body and extracts information necessary for diagnosis of health. Hereinafter, as an example, a case where the subject to be imaged is a tongue as an organ of a living body is shown.

The organ image photographing apparatus 1 includes an illumination unit 2, a light projecting unit 3, an imaging unit 4, a display unit 5, an operation unit 6, and a communication unit 7. The illumination unit 2 and the light projecting unit 3 are provided in the casing 21, and the other components (the imaging unit 4, the display unit 5, the operation unit 6, and the communication unit 7) are provided in the casing 22. Although the housing | casing 21 and the housing | casing 22 are connected so that relative rotation is possible, rotation is not necessarily required and one side may be completely fixed to the other. In addition, said illumination part 2 grade | etc., May be provided in the single housing | casing. Moreover, the organ image photographing device 1 may be composed of a multifunctional portable information terminal.

The illumination unit 2 is composed of an illuminator that illuminates a subject to be photographed from above. As the light source of the illuminating unit 2, in order to improve color reproducibility, a light source that emits a daylight color such as a xenon lamp is used. The brightness of the light source varies depending on the sensitivity of the imaging unit 4 and the distance to the shooting target. As an example, it is possible to consider the brightness at which the illuminance of the shooting target is 1000 to 10000 lx. The illumination unit 2 has a lighting circuit and a dimming circuit in addition to the light source.

The light projecting unit 3 is composed of a light projector that projects (irradiates) linear light in a horizontal direction onto the surface of the tongue, which is an organ to be imaged. Here, the horizontal direction refers to a direction perpendicular to a line connecting the tip of the tongue (the tip of the tongue) and the root (the base of the tongue) (the same applies hereinafter). Details of the light projecting unit 3 will be described later.

The imaging unit 4 captures an image of a living organ and acquires an image, and includes an imaging lens and an area sensor (imaging device). The aperture (brightness of the lens), shutter speed, and focal length of the imaging lens are set so that the entire range to be photographed is in focus. As an example, F number: 16, shutter speed: 1/120 seconds, focal length: 20 mm.

The area sensor is composed of image sensors such as CCD (Charge Coupled Device) and CMOS (Complementary Metal Oxide Semiconductor), and the sensitivity and resolution are set so that the color and shape of the subject can be detected sufficiently. Has been. As an example, sensitivity: 60 db, resolution: 10 million pixels.

In addition to the imaging lens and the area sensor, the imaging unit 4 includes a focus mechanism (not shown), a diaphragm mechanism, a drive circuit, an A / D conversion circuit, and the like. In the imaging unit 4, for example, data of 0 to 255 in 8 bits is acquired for each of red (R), green (G), and blue (B) as captured image data.

FIG. 3 is an explanatory diagram showing the positional relationship among the illumination unit 2, the light projecting unit 3, and the imaging unit 4 with respect to the subject to be photographed (tongue and face). As shown in the figure, the imaging unit 4 is arranged to face the subject to be photographed. The illuminating unit 2 is disposed so as to illuminate the imaging target at an angle A of, for example, 0 ° to 45 ° with respect to the imaging optical axis X of the imaging unit 4 passing through the imaging target. In addition, the light projecting unit 3 projects linear light onto the imaging target at an angle B that is, for example, in the range of 0 ° to 45 ° with respect to the imaging optical axis X and is larger than the angle A. Is arranged. The imaging optical axis X refers to the optical axis of the imaging lens that the imaging unit 4 has.

When the angle A during illumination is large, the range in which the tongue can be photographed becomes small due to the shadow of the upper lip. Conversely, when the angle A is small, the color jump due to regular reflection increases. Also, if the angle B at the time of projection is large, the amount of deformation when linear light deforms along the irregularities on the tongue surface increases, so the irregularities on the tongue surface can be accurately determined based on the shape of the projected light. Although it can be detected well, conversely, if the angle B is small, the detection accuracy of the unevenness decreases. Considering the above, the preferable range of the angle A is 15 ° to 30 °, and the preferable range of the angle B is 30 ° to 45 °. However, A <B.

The display unit 5 has a liquid crystal panel (not shown), a backlight, a lighting circuit, and a control circuit, and displays an image acquired by photographing with the imaging unit 4. The display unit 5 can also display information acquired from the outside via the communication unit 7 (for example, a result of diagnosis by transmitting information to an external medical institution).

The operation unit 6 is an input unit for instructing imaging by the imaging unit 4, and includes an OK button (imaging execution button) 6a and a CANCEL button 6b. In the present embodiment, the display unit 5 and the operation unit 6 are configured by a common touch panel display device 31, and the display area of the display unit 5 and the display area of the operation unit 6 in the touch panel display device 31 are separated. The operation unit 6 may be configured by an input unit other than the touch panel display device 31 (the operation unit 6 may be provided at a position outside the display area of the touch panel display device 31).

The communication unit 7 transmits the image data acquired by the imaging unit 4 and the data processed by the image processing unit 16 and the detection unit 18 described later to the outside via a communication line (including wired and wireless). And an interface for receiving information from the outside.

The organ imaging apparatus 1 further includes an illumination control unit 11, a light projection control unit 12, an imaging control unit 13, a display control unit 14, an operation control unit 15, an image processing unit 16, a storage unit 17, a detection unit 18, and communication control. A unit 19 and an overall control unit 20 for controlling these units are provided. The illumination control unit 11, the light projection control unit 12, the imaging control unit 13, the display control unit 14, the operation control unit 15, and the communication control unit 19 are the illumination unit 2, the light projection unit 3, the imaging unit 4, and the display unit 5. The operation unit 6 and the communication unit 7 are controlled. The overall control unit 20 is composed of, for example, a CPU (Central Processing Unit). The illumination control unit 11, the light projection control unit 12, the imaging control unit 13, the display control unit 14, the operation control unit 15, the communication control unit 19, and the overall control unit 20 are integrated (for example, with one CPU). ) May be configured.

The image processing unit 16 obtains a horizontal data distribution indicating the degree of unevenness on the surface of the organ from the image taken by the imaging unit 4, and the data distribution together with the illumination unit 2, the light projecting unit 3, and the imaging unit 4. The acquisition unit is configured. The horizontal data distribution may be (1) distribution of the height of the surface of the tongue, (2) distribution of image data of any of RGB colors included in the captured image of the tongue surface, or It may be a data distribution indicating the component ratio of any of the RGB colors. In the case of (1) above, the image processing unit 16 projects the height of the tongue surface from the curved shape of the linear light projected on the tongue surface by the light projecting unit 3 and photographed by the imaging unit 4. It functions as a height distribution acquisition unit that acquires. In the case of (2) above, the image processing unit 16 extracts image data of at least one of RGB colors from the photographed image of the tongue acquired by the imaging unit 4 under illumination by the illumination unit 2. Thus, it functions as a distribution creating unit that creates a distribution of image data of any of RGB colors or a distribution of data indicating a component ratio of any of RGB colors. Details of the data distribution will be described later.

The image processing unit 16 also has a function of extracting an organ outline from the image acquired by the imaging unit 4. Extraction of the outline of the organ can be performed by extracting the luminance edge of the captured image (the portion in which the brightness changes abruptly in the image). The luminance edge is extracted, for example, as shown in FIG. Such an edge extraction filter can be used. The edge extraction filter is a filter that weights pixels in the vicinity of the target pixel when performing first-order differentiation (when obtaining a difference in image data between adjacent pixels).

Using such an edge extraction filter, for example, for the G image data of each pixel of the captured image, the difference between the image data is calculated between the target pixel and the neighboring pixel, and the pixel whose difference value exceeds a predetermined threshold is extracted. Thus, a pixel that becomes a luminance edge can be extracted. Since there is a luminance difference due to the shadow around the tongue, the contour line of the tongue can be extracted by extracting pixels that become luminance edges as described above. Here, although G image data having the greatest influence on the luminance is used for the calculation, R or B image data may be used.

In Oriental medicine, the speckled white portion found in the center of the tongue is called moss, and its color is called moss. Moreover, the color of the red part other than the above in the tongue is called the tongue color.

The storage unit 17 stores image data acquired by the imaging unit 4, data processed by the image processing unit 16 and the detection unit 18, information received from the outside, and operates the various control units described above. This is a memory for storing a program for this purpose.

The detecting unit 18 detects the organ thickness (thickness degree) based on the unevenness of the data distribution acquired by the image processing unit 16. In particular, the detection unit 18 quantifies the thickness of the detected organ and determines the tongue thickness in the tongue examination. Details of the detection of the thickness of the organ (tongue) and the determination of the tongue thickness will be described later.

[Structure of projector and detection principle of tongue thickness]
FIG. 5 is a perspective view illustrating a schematic configuration of the light projecting unit 3. As shown in the figure, the light projecting unit 3 includes a point light source 41 and a columnar lens 42, and a drive circuit (not shown) that drives the point light source 41. The point light source 41 is configured by an LD (Laser Diode) or an LED (Light Emitting Diode). The columnar lens 42 is a columnar condensing lens in the horizontal direction that condenses the light emitted from the point light source 41 only in one direction (for example, the vertical direction). As the light emitted from the point light source 41 is condensed in one direction by the columnar lens 42, linear light that is long in the horizontal direction is projected onto the surface of the tongue as shown in FIG.

FIG. 7 shows a photographed image obtained by photographing linear light (shown by a thick solid line) projected on the tongue surface by the light projecting unit 3 with the imaging unit 4 when the tongue is thin and thick. The cross-sectional shape is shown. In the figure, the portion of the photographed image that is not the tongue surface is represented by a straight line indicating a height reference 0 (see FIGS. 8 and 9) described later. As shown in the figure, when the tongue is thin and its surface is almost flat, the projected linear light is slightly curved upward at the tongue portion. On the other hand, when the tongue is thick and the surface thereof is convex, the projected linear light is greatly curved upward at the tongue portion. Therefore, the thickness of the tongue (whether the tongue is thick or thin) can be detected by detecting the curved shape of the projected linear light. Note that the method of detecting the shape of the subject by irradiating the subject with linear light is also called a light cutting method.

When the organ to be imaged is the tongue, if a point light source that emits G or B light, which is a complementary color of the tongue color (R), is used as the point light source 41, the color of the projected light and the color of the tongue Therefore, it is easy to detect the curved shape of the projected light by photographing with the imaging unit 4. Even when the point light source 41 that emits the R light is used, the curved shape of the projected light can be detected by photographing with the imaging unit 4 by adjusting the amount of emitted light.

In addition, in this embodiment, although the light projection part 3 is comprised using the point light source 41 and the columnar lens 42, the structure of the light projection part 3 is not necessarily limited to this. For example, instead of the columnar lens 42, a slit having an elongated opening in the horizontal direction may be arranged, and linear light may be projected onto the tongue surface in the horizontal direction through the opening. Alternatively, a polygon mirror may be disposed in place of the columnar lens 42, and light may be projected in the horizontal direction by scanning the light from the light source at high speed in the horizontal direction with the polygon mirror.

[Relationship between tongue thickness and muscle movement, and horizontal data distribution]
There are two types of muscles of the tongue, the external tongue muscle and the internal tongue muscle. The former controls the large movement of the whole tongue, and the latter controls the fine movement of the tongue. Movements affecting the surface irregularities of the tongue are controlled by the internal tongue muscle. The internal tongue muscle includes an upper longitudinal tongue muscle that winds up the side of the tongue upward, a lateral tongue muscle that stretches the tongue thinly, and a vertical tongue muscle that spreads the tongue flatly. When photographing the tongue, it is instructed to spread the tongue sideways, but depending on the person, there may be unconscious power.

FIG. 8 shows the relationship between the thickness of the tongue and the movement of the tongue by the muscles. When the tongue is spread laterally by the action of the vertical tongue muscle (normal photographing state), the surface of the tongue becomes flat when the tongue is thin, and becomes convex when the tongue is thick. When the side of the tongue is raised by the action of the upper longitudinal tongue muscle, the surface of the tongue is concave when the tongue is thin, and is gently convex when the tongue is thick. When the tongue is stretched thinly by the action of the lateral tongue muscle, the surface of the tongue becomes convex when the center is thick, and when the tongue is thick, the surface of the tongue is raised as a whole.

When linear light is projected in the horizontal direction onto the surface of such a tongue by the light projecting unit 3 and the curved shape is photographed by the image capturing unit 4, the image processing unit 16 displays the curved shape from the curved shape. A data distribution as shown in FIG. This data distribution indicates the degree of unevenness on the tongue surface, and is a height distribution in which the height changes according to the unevenness on the tongue surface. Note that (a1) to (a3) show the height distribution in the horizontal direction when the tongue is thin, and (b1) to (b3) show the height distribution in the horizontal direction when the tongue is thick.

In the present embodiment, the linear light projected from the light projecting unit 3 is projected so as to pass through the substantially vertical center of the tongue surface as shown in FIG. Therefore, the height distribution shown in FIG. 8 is obtained as a horizontal height distribution that passes through a substantially vertical center of the tongue surface. Here, the vertical direction on the surface of the tongue refers to the direction connecting the tip of the tongue (the tongue tip) and the root (the tongue base) (the same applies hereinafter).

[Method for judging tongue thickness]
Next, a method for determining the tongue thickness from the above height distribution will be described. First, as illustrated in FIG. 9, the detection unit 18 sets a region A that is closer to the end than the center in the horizontal direction in the height distribution of the tongue surface acquired by the image processing unit 16. Here, the region A is a region determined by the dimensional relationship shown in FIG. 9 (with a width W / 4 at a distance of W / 8 from the end of the tongue, where W is the width of the tongue determined from the contour line of the tongue. Area). In addition, the said edge part may be an edge part on either side with respect to the center part of a tongue. Further, the height distributions of (a1) to (a3) and (b1) to (b3) in FIG. 9 correspond to those shown in FIG.

Next, the detection unit 18 approximates the shape of the region A in the height distribution with a polynomial, detects irregularities on the surface of the tongue (the degree of curvature of the shape) based on the coefficients of the approximated polynomial, and determines from the irregular shapes Detect the thickness of the tongue. The polynomial can be calculated using a general method (for example, the least square method). Although the order of the polynomial is not particularly limited, a quadratic polynomial (y = ax ² + bx + c) is used here as an example. a is a secondary coefficient described later.

When the tongue is thin (a1) to (a3), the shape of the region A is horizontal or has changed from horizontal to concave, so the second-order coefficient of the approximate polynomial is 0 or a positive value. On the other hand, when the tongue is thick (b1) to (b3), since the shape of the region A is a convex shape, the quadratic coefficient of the approximate polynomial is a negative value. Note that the thicker the tongue, the greater the negative value of the coefficient.

Thus, by looking at the coefficients of the approximate polynomial, the degree of unevenness of the shape (height distribution) of the region A can be obtained to determine whether the tongue is thin or thick.

FIG. 10 shows a quadratic coefficient of the approximate polynomial of region A when a plurality of people's tongues are photographed and the horizontal height distribution of the tongue surface is acquired, and the Chinese doctor actually Shows the relationship with the findings of tongue thickness when the tongue was examined. From the figure, it can be seen that there is a high correlation between the quadratic coefficient of the approximate polynomial and the findings of Chinese medicine. That is, it can be said that the tongue is thicker as the secondary coefficient is larger (the value is larger on the plus side), the tongue is thinner, and the secondary coefficient is smaller (the value is larger on the minus side). The correlation coefficient indicating the degree of correlation between the second-order coefficient and the findings of the Chinese medicine doctor was a high value of 0.88.

Therefore, the detection unit 18 can detect and determine the thickness of the tongue based on the second-order coefficient of the approximate polynomial. For example, when the secondary coefficient is 0.003 or more, it can be determined that the tongue is thin, and when the secondary coefficient is 0 or less, it can be determined that the tongue is thick, When the second-order coefficient is greater than 0 and less than 0.003, the tongue thickness can be determined to be medium. The correlation shown in FIG. 10 may be stored in the storage unit 17 as a table, and the detection unit 18 may determine the thickness of the tongue from the secondary coefficient with reference to the above table.

In the example of FIG. 10, the degree of the thickness of the tongue is quantified in three stages, “1” to “3”, corresponding to “tongue is thin”, “medium”, and “tongue is thick”. However, if the level of the thickness of the tongue is digitized in this way, the health level of the subject can be easily diagnosed based on the numeric value. *

[Control flow]
FIG. 11 is a flowchart showing an operation flow in the organ image capturing apparatus 1 of the present embodiment. When the organ image photographing apparatus 1 accepts a photographing instruction through the operation unit 6 or an input unit (not shown), the illumination control unit 11 turns on the illumination unit 2 (S1), and sets photographing conditions such as illuminance (S2). ). When the setting of the shooting conditions is completed, the imaging control unit 13 controls the imaging unit 4 to shoot the tongue that is the shooting target (S3).

When the photographing is completed, the image processing unit 16 extracts the contour line of the tongue from the photographed image of the tongue (S4). Then, the image processing unit 16 detects the upper and lower ends and left and right ends of the tongue from the extracted contour line Q, and detects the length and width of the tongue (length and width in the vertical direction of the tongue) (S5). Next, the light projecting control unit 12 controls the light projecting unit 3 to project linear light in the horizontal direction substantially at the center of the tongue surface in the vertical direction (S6).

The linear light projected on the tongue surface bends along the shape of the tongue surface. When the imaging unit 4 captures the curved shape of the linear light (S7), the image processing unit 16 determines the horizontal direction of the tongue surface from the curved shape of the captured light, as shown in FIGS. A height distribution is acquired (S8). Then, the detection unit 18 approximates the shape of a part of the region A of the height distribution with a second-order polynomial (S9), and refers to the table shown in FIG. In addition to detecting the thickness, the degree of the thickness of the tongue is digitized (S10). Thereby, the detection unit 18 can diagnose the health level of the subject based on the numerical value of the tongue thickness. The detection result of the tongue thickness and the diagnosis result of the health level of the subject are displayed on the display unit 5, but are output (recorded) to an output device (not shown) or transferred to the outside via the communication unit 7 as necessary. (S11). In addition, the detection result of the tongue thickness may be digitized and transmitted to the outside, and the health level of the subject may be diagnosed outside.

As described above, the image processing unit 16 acquires a horizontal data distribution (height distribution) indicating the degree of unevenness on the tongue surface from the captured image obtained by the imaging unit 4. Even when the outer shape of the tongue varies depending on individual differences and how the force is applied, the horizontal data distribution is obtained regardless of the individual outer shape of the tongue as indicating the degree of unevenness of the tongue surface. Therefore, the detection unit 18 can accurately detect the thickness of the tongue (thick or thin) regardless of the outer shape based on the unevenness of the data distribution.

In particular, when the organ is a tongue, the detection unit 18 detects the tongue thickness of the tongue diagnosis based on the unevenness of the data distribution, so that it is possible to determine the health level of the subject based on the tongue thickness. Become.

Also, since the data distribution is a distribution of the height of the tongue surface, it is possible to realize a data distribution that reliably reflects the degree of unevenness of the tongue surface.

In addition, the imaging unit 4 captures a shape of the linear light projected by the light projecting unit 3 and deformed according to the unevenness of the tongue surface, and the height distribution of the tongue surface is taken from the shape to the image processing unit 16. Have acquired. Thus, the height distribution of the tongue surface can be easily obtained by using the light cutting method.

Further, the detecting unit 18 approximates the shape of the height distribution with a polynomial, and detects the thickness of the tongue based on the coefficient. As described above, whether the shape of the tongue surface is concave or convex can be detected from the coefficient of the approximate polynomial (for example, positive or negative). If the tongue is concave, the tongue is thin, and if the tongue is convex, the tongue is It is considered thick. Therefore, the degree of the thickness of the tongue can be reliably detected from the coefficient of the approximate polynomial (= unevenness on the tongue surface).

Also, the detection unit 18 performs approximation by a polynomial only for a partial region A of the height distribution. By doing in this way, processing time can be shortened compared with the case where the whole shape of height distribution is approximated with a polynomial (over the whole width W).

In addition, the region A is a region corresponding to the end portion side of the horizontal portion of the tongue in the height distribution. Regardless of whether the tongue is thin or thick, the region corresponding to the central portion of the tongue in the height distribution is nearly flat, making it difficult to detect the tongue thickness based on the coefficients of the approximate polynomial. Therefore, as in this embodiment, by approximating the shape of the region A shifted from the center of the tongue toward the end in the height distribution with a polynomial, the concave or convex shape of the tongue surface can be reliably detected. The degree of tongue thickness can be reliably detected.

In this embodiment, a quadratic expression is used as the approximate polynomial. Based on the sign of the second-order coefficient, it can be easily determined whether the shape of the tongue surface is concave or convex, and therefore the degree of tongue thickness can be easily detected from the uneven shape.

Also, the above-mentioned height distribution is a horizontal data distribution that passes through almost the center in the vertical direction on the surface of the tongue. In the cross-section perpendicular to the vertical direction of the tongue, the horizontal uneven shape of the tongue surface is almost the same at any position in the vertical direction, so the thickness of the tongue is calculated from the uneven shape of the data distribution passing through the approximate center in the vertical direction. Can be sufficiently detected. That is, the thickness of the tongue can be detected without scanning the entire tongue surface in the vertical direction (without acquiring the horizontal data distribution over the entire vertical direction).

[Other setting methods for area A]
FIG. 12 is an explanatory diagram schematically showing another setting method of the region A in the horizontal data distribution (height distribution). As shown in the figure, the region A (a part of the height distribution) in which the detection unit 18 approximates the shape of the height distribution may include a data distribution of the end portion of the tongue.

In this case, when the circle is used as the approximate polynomial, and the detection unit 18 approximates the shape of the height distribution in the region A (curvature) with a circle and detects its radius, the following relationship is obtained. . That is, when the radius of the approximate circle when the tongue is thin is R1 (mm) and the radius of the approximate circle when the tongue is thick is R2 (mm), the radius R1 is significantly smaller than the radius R2. It was. Therefore, it is easy to determine whether the tongue is thick or thin based on the radius of the circle approximating the region A, and the detection accuracy of the tongue thickness can be further improved.

[Other examples of data distribution]
FIG. 13 is a distribution of image data obtained when the surface of the tongue is imaged by the imaging unit 4 under illumination by the illuminating unit 2, and the captured image in the horizontal direction passing through the substantially vertical center of the tongue surface. The distribution of RGB image data is shown. However, the upper distribution is for the case where the tongue is thin, and the lower distribution is for the case where the tongue is thick. The solid line indicates the distribution of R image data, the alternate long and short dash line indicates the distribution of G image data, and the broken line indicates the distribution of B image data.

When the tongue is thick, the tongue includes a portion that protrudes upward from the end to the center (see (b1) to (b3) of FIG. 8). Since such a convex portion on the tongue surface is brightly illuminated as it approaches the illumination unit 2, the value of the image data increases in the portion corresponding to the convex portion in the photographed image of the tongue. On the contrary, when the tongue is thin, the surface of the tongue includes a portion that is substantially flat from the end to the center, or includes a concave portion (see (a1) to (a3) in FIG. 8). Since the flat part and recessed part of the tongue surface move away from the illumination part 2 compared with said convex part, even if illuminated, it is darker than a convex part. For this reason, in the photographed image of the tongue, the value of the image data decreases in the portion corresponding to the flat portion or the concave portion on the surface compared to the portion corresponding to the convex portion. This tendency is the same for all RGB image data. The shape of the distribution of the image data shown in FIG. 13 corresponds to the shape of (a2) and (b2) in FIG.

Therefore, whether or not the tongue is thick or thin based on the unevenness of the distribution, even from the distribution of the image data of one of RGB colors (monochromatic distribution) in the photographed image of the tongue obtained under illumination of the illumination unit 2 Can be detected. In other words, it is possible to detect the tongue thickness with high accuracy (the tongue is detected by using the horizontal distribution of image data of one of RGB colors included in the photographed image of the tongue as a data distribution indicating the degree of unevenness of the tongue surface. Regardless of the outer shape). Also, with this method, the above-described light projecting unit 3 is not necessary, and thus it is possible to detect and diagnose the thickness of the tongue with a small and inexpensive configuration.

As a result of various experiments, it was found that when the component ratio of R, that is, the distribution of R / (R + G + B) was used as the data distribution, a distribution almost identical to the above-described height distribution was obtained. Therefore, the tongue thickness can be accurately detected by using the data distribution indicating the R component ratio in the photographed image of the tongue obtained under illumination of the illumination unit 2 as the data distribution indicating the degree of unevenness of the tongue surface. I can say that. Note that the tongue thickness can be accurately determined in the same manner as described above using the distribution of data indicating the G component ratio (G / (R + G + B)) and the B component ratio (B / (R + G + B)) in the photographed image of the tongue. Can be detected.

[Others]
In the above, the example in which the thickness of the tongue is detected from the horizontal data distribution indicating the degree of unevenness of the tongue surface has been described, but the tongue thickness can also be obtained by the following simple calculation.

FIG. 14 is an explanatory view schematically showing the relationship between the planar shape and the cross-sectional shape of the tongue. The surface area S (cm ² ) of the tongue in the standard state of the tongue muscle (the state where the tongue is not expanded or narrowed) is obtained by integrating the portion surrounded by the contour line (see FIG. 4) extracted from the photographed image of the tongue. Desired.

The surface area S is approximated as follows using an index W _S (cm) corresponding to the lateral width of the tongue in the standard state of the tongue muscle and an index W _L (cm) corresponding to the vertical width of the tongue. be able to.
S ≒ W _S × W _L

Here, the aspect ratio of the tongue in the standard state of the tongue muscle is length / width≈1.0 to 1.3, but if length / width = 1.2,
W _L = 1.2W _S
Can be considered. Therefore, the surface area S is
_{_{S = W S × (1.2W S}} )
= 1.2W _S ²
It becomes. From this formula:
W _S = √ (S / 1.2)
Is obtained.

On the other hand, the sectional area of the tongue in the standard state of the tongue muscle is simplified by twice the area of the height distribution shown in (a1) of FIG. 8 (the area of the portion surrounded by the horizontal axis and the distribution curve). Can be requested. That is, when the sectional area of the tongue is Sc (cm ² ),
Sc = 2 × ∫h × dw
It is represented by Here, h is the height from the horizontal axis of the height distribution curve, and dw is the minute width of the curve.

When the thickness of the tongue in the standard state of the tongue muscle is Hs (cm), the thickness Hs is
Hs = Sc / W _S
= Sc / (√ (S / 1.2))
It is represented by

When the tongue muscle is moved, the length and width of the tongue change, but the surface area S and the cross-sectional area Sc hardly change. Therefore, by determining the surface area S and the cross-sectional area Sc of the tongue, the tongue thickness Hs in the standard state of the tongue muscle can be easily obtained from the above equation regardless of the state of the tongue muscle at the time of photographing. And it becomes possible to diagnose a health degree based on the calculated | required tongue thickness.

In the above, the case where the subject to be photographed is a human tongue has been described. However, as long as it is a living body (living thing), it may not be a human but may be an animal other than a human. For example, even for the tongue of an animal such as a pet or a domestic animal, the tongue thickness can be detected by applying the method of the present embodiment, and a diagnosis can be performed based on the detection result. In this case, it is possible to quickly and accurately determine the poor physical condition of an animal that cannot communicate its intention.

Also, the organ of the living body to be imaged is not limited to the tongue. For example, if it is a site where swelling occurs due to the quality of water metabolism such as eyelids, it is possible to detect the thickness of the organ and make a diagnosis based on the thickness as in this embodiment.

The organ image capturing apparatus described above can be expressed as follows, and has the following effects.

The organ image capturing apparatus described above captures an organ of a living body and acquires a horizontal data distribution indicating the degree of unevenness on the surface of the organ, and the data distribution acquisition unit acquires the data distribution in the horizontal direction. And a detector for detecting the thickness of the organ based on the unevenness of the data distribution.

The horizontal data distribution indicating the degree of unevenness on the organ surface is acquired by the data distribution acquisition unit. Since this data distribution indicates the degree of unevenness on the organ surface and is acquired regardless of the external shape of each organ, the detection unit determines the thickness (thickness of the organ) based on the unevenness of the data distribution. By detecting the degree of thickness, the thickness of the organ can be accurately detected regardless of the outer shape of each organ, even if the outer shape of the organ varies depending on individual differences and how to apply force.

The organ may be a tongue, and the detection unit may detect a tongue thickness for tongue examination based on the unevenness of the data distribution. In this case, it is possible to determine the health level of the subject based on the tongue thickness.

The data distribution may be a distribution of the height of the tongue surface. The height distribution on the surface of the tongue is a distribution representing the degree of unevenness on the surface of the tongue itself. Therefore, by using the height distribution, the thickness of the tongue can be reliably detected with high accuracy.

The data distribution acquisition unit is configured to project a linear light in a horizontal direction on the surface of the tongue, and the unevenness of the surface of the tongue of the light projected by the light projecting unit. An imaging unit that captures a curved shape and a height distribution acquisition unit that acquires a height distribution of the surface of the tongue from the curved shape of the light captured by the imaging unit. Thus, by photographing the curved shape of the linear light projected on the tongue surface, the height distribution of the tongue surface can be easily obtained from the curved shape.

The data distribution may be a distribution of image data of any of red, green, and blue in a photographed image of the tongue surface, or a distribution of data indicating a component ratio of any of the colors. When the illumination condition is constant, the brightness changes between the concave and convex portions on the tongue surface, so the red (R), green (G), and blue (B) image data included in the captured image of the tongue is Both change according to the unevenness of the tongue surface. Therefore, by using the distribution of image data of any color of RGB of the photographed image or the distribution of data indicating the component ratio of any color as the data distribution indicating the degree of unevenness on the tongue surface, The thickness can be detected with high accuracy.

The data distribution acquisition unit includes an illumination unit that illuminates the surface of the tongue, an imaging unit that captures the tongue under illumination by the illumination unit, and a captured image of the tongue acquired by the imaging unit. A distribution creation unit that extracts image data of at least one of the colors of blue and creates a distribution of the image data of any of the colors or a distribution of data indicating a component ratio of any of the colors May be. In this case, a horizontal data distribution indicating the degree of unevenness on the tongue surface can be reliably acquired from the RGB image data included in the photographed image of the tongue.

The detecting unit may approximate the shape of the distribution with a polynomial and detect the thickness of the tongue based on a coefficient of the polynomial. Since the coefficient of the approximate polynomial indicates the degree of unevenness on the tongue surface, the thickness of the tongue (degree of thickness) can be reliably detected based on this coefficient.

The detection unit may perform approximation by the polynomial only for a part of the distribution. In this case, the processing time can be shortened compared to the case where the entire shape of the data distribution is approximated by a polynomial.

The part of the distribution may be a data distribution on the end side with respect to the central portion in the horizontal direction of the tongue. By approximating the shape of the portion of the data distribution that deviates from the center of the tongue with a polynomial, the concave or convex shape of the tongue surface can be reliably detected, and the degree of tongue thickness can be reliably detected. .

The part of the distribution may include a data distribution of the end of the tongue. When the data distribution at the end of the tongue is approximated by a polynomial (curve), the degree of curvature (radius, radius) of the approximate curve differs significantly depending on the degree of unevenness on the tongue surface (degree of tongue thickness). The curve of the approximate curve increases, and the curve of the approximate curve decreases when the tongue is thin. Therefore, the detection accuracy of the degree of tongue thickness is further improved.

The polynomial may be a quadratic expression, and the coefficient may be a quadratic coefficient of the polynomial. In this case, the detection unit can easily determine whether the shape of the tongue surface is a concave shape or a convex shape based on the sign of the quadratic coefficient of the approximate polynomial. The degree of thickness can be easily detected.

It is desirable that the data distribution is a horizontal data distribution passing through substantially the center of the direction connecting the tongue tip and the tongue base on the tongue surface. Since the uneven shape in the horizontal direction of the tongue surface is almost the same in any cross section as long as the cross section is perpendicular to the direction connecting the tongue tip and the base of the tongue, from the uneven shape of the above data distribution passing through the approximate center in the vertical direction, The thickness of the tongue can be detected sufficiently.

The present invention can be used for an apparatus for photographing a living organ and detecting the thickness of the organ.

DESCRIPTION OF SYMBOLS 1 Organ imaging device 2 Illumination part (data distribution acquisition part)
3. Projection unit (data distribution acquisition unit)
4 Imaging unit (data distribution acquisition unit)
16 Image processing unit (data distribution acquisition unit, height distribution acquisition unit, distribution creation unit)
18 Detector

Claims

A data distribution acquisition unit that images a living organ and acquires a horizontal data distribution indicating the degree of unevenness on the surface of the organ;
An organ imaging apparatus comprising: a detection unit that detects the thickness of the organ based on the unevenness of the data distribution acquired by the data distribution acquisition unit.
The organ is the tongue;
The organ image capturing apparatus according to claim 1, wherein the detection unit detects a tongue thickness of tongue examination based on the unevenness of the data distribution.
The organ image photographing apparatus according to claim 2, wherein the data distribution is a distribution of a height of a surface of the tongue.
The data distribution acquisition unit
A light projecting unit that projects linear light in a horizontal direction on the surface of the tongue;
An imaging unit that captures a curved shape of the light projected by the light projecting unit according to the unevenness of the surface of the tongue;
The organ image capturing device according to claim 3, further comprising: a height distribution acquisition unit that acquires a height distribution of the surface of the tongue from the curved shape of the light imaged by the imaging unit.
3. The data distribution according to claim 2, wherein the data distribution is a distribution of image data of any one of red, green, and blue in a photographed image of the tongue surface, or a distribution of data indicating a component ratio of any one of the colors. Organ imaging device.
The data distribution acquisition unit
An illumination unit that illuminates the surface of the tongue;
An imaging unit for photographing the tongue under illumination by the illumination unit;
The image data of at least one of red, green, and blue is extracted from the captured image of the tongue acquired by the imaging unit, and the distribution of the image data of any one of the colors, or any one of the colors The organ image photographing device according to claim 5, further comprising: a distribution creating unit that creates a distribution of data indicating the component ratio of the organ.
The organ imaging apparatus according to any one of claims 3 to 6, wherein the detection unit approximates the shape of the distribution with a polynomial and detects the thickness of the tongue based on a coefficient of the polynomial.
The organ imaging apparatus according to claim 7, wherein the detection unit performs approximation by the polynomial only for a part of the distribution.
The organ image capturing apparatus according to claim 8, wherein a part of the distribution is a data distribution closer to an end side than a central part in a horizontal direction of the tongue.
The organ imaging apparatus according to claim 9, wherein a part of the distribution includes a data distribution of an end portion of a tongue.
The polynomial is a quadratic equation,
The organ image photographing apparatus according to claim 7, wherein the coefficient is a second-order coefficient of the polynomial.
The organ image capturing apparatus according to any one of claims 2 to 11, wherein the data distribution is a horizontal data distribution passing through a substantially center of a direction connecting a tongue apex and a tongue base on a tongue surface.