JP2003180641A - Blood flow velocity measuring apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a blood flow velocity measuring apparatus by which the same level measurement accuracy can be obtained as conventional apparatus using at least three images without requiring multiple images. <P>SOLUTION: The blood flow velocity measuring apparatus has a storage section storing in turn multiple images formed on a light-receiving part based on the reflecting signals from a body tissue by applying laser beam to the blood cells of the body tissue, and calculates the distribution condition of the blood cell velocity based on at least three images of the stored images. The calculation section detects the blood flow distribution condition in the body tissue by selecting a first pixel group comprising a plurality of pixels selected from the pixels of a predetermined address position and the pixels present adjacent to the above predetermined address position within one image, selecting a second and third pixel groups present respectively at the same address as the above first pixel group within other images, selecting predetermined two combined pixels from the above the first to third pixel groups, calculating the average of the total of the differences of the outputs of the selected two pixels or the inverse number, and carrying out the difference calculation on each predetermined address position pixel. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a blood flow velocity measuring device for irradiating a living tissue having blood cells with laser light and measuring a blood flow velocity based on a speckle signal reflected from the blood cells.

[0002]

2. Description of the Related Art Conventionally, a blood cell of a living tissue such as a fundus of an eye to be examined is irradiated with laser light and an image formed by reflected light from the blood cell is guided onto an image sensor such as a solid-state imaging device (CCD). , This image is continuously captured and stored at a predetermined time interval, a predetermined number of images are selected from the stored many images, and the time variation amount of output at each pixel of each image is integrated. There is known a blood flow velocity measuring device that calculates a value or its reciprocal value and calculates the blood cell velocity (blood flow velocity) from this value.

In this type of blood flow velocity measuring device, since the output fluctuation amount of each pixel corresponds to the blood cell moving speed, based on the calculated output fluctuation amount value of each pixel or its reciprocal value, The blood flow velocity distribution in living tissue is displayed as a two-dimensional image on the monitor screen.

Assuming that the value calculated by each pixel, that is, the calculated value indicating the blood flow velocity is the SBR value, the following formula is used, for example.

[0005]

[Equation 1]

In this equation 1, SBR _{n, m} is given by
As shown in, for example, the SBR value at the n-th and m-th pixels in a series of time-series images taken in one second is shown, and I _{n, m, t} is the n-th and m-th pixels. The time t _i (i
= 1, 2, ..., N), and <>
Indicates an average value.

The numerator of the equation (1) shows the square of the average value of the outputs of the nth and mth pixels which change with time within a predetermined time. The denominator of Equation 1 is the square of the average value of the absolute values of the differences between the pixel output of the nth and mth pixel at each time and the average output value of the nth and mth pixel within a predetermined time. This denominator means a value corresponding to the variance value of the output fluctuation at the n-th and m-th pixel positions.

In this way, the SBR values are n = 1 and m =
It is obtained from the pixel X at the address 1 to the pixel X at the address n = n, m = m, and the blood flow velocity is displayed on the screen 1 by coloring in accordance with the SBR value, as shown in FIG.

That is, the faster the speckle fluctuation is, the more the speckle fluctuation is integrated within the shutter time, and the fluctuation in the output fluctuation is reduced. Therefore, the denominator of the SBR value in Equation 1 decreases, and
The value increases. Coloring is performed according to the magnitude of this SBR value, and the change in blood flow velocity is displayed on the screen 1.

[0010]

As described above, in this type of blood flow velocity measuring apparatus, in order to see the temporal change in the blood flow velocity distribution, for example, an image is taken at a high-speed shutter interval of 500 frames per second. Captured, for example, a series of N = 64 time-series images is extracted from the image, and 64
The SBR value corresponding to the blood flow velocity is calculated by the equation 1 based on the images.

According to the calculation method of the equation (1), at least about 30 images are required to obtain a highly accurate blood flow velocity result, and the highly accurate blood flow velocity can be measured, and
To improve the measurement resolution of the temporal change in blood flow velocity,
There is a need for a high speed continuous image capture device with short shutter intervals.

An object of the present invention is to solve this conventional problem and does not require a large number of images for blood flow velocity calculation, and at least three images can be used for the conventional blood flow calculation. It is an object of the present invention to provide a blood flow velocity measuring device that can obtain the same level of measurement accuracy as the flow velocity measuring device.

[0013]

A blood flow velocity measuring apparatus according to a first aspect of the present invention includes a laser light irradiating section for irradiating blood cells of a living tissue with a laser light, and a large number of detecting a reflected light from the living tissue. A light-receiving unit formed of a light-receiving element, a storage unit that sequentially records a plurality of images formed on the light-receiving unit based on a signal from the light-receiving unit, and at least three of the stored images.
And a calculation unit that calculates the distribution state of blood cell velocities based on a single image, wherein the calculation unit selects from among pixels at one predetermined address position and pixels located near the predetermined address in one image. The first pixel group including a plurality of selected pixels and the second and third pixel groups located at the same address as the first pixel group in other images are selected, and the first pixel group is selected. Or, a predetermined two combination pixels are selected from the third pixel group, the average value of the sums of the differences between the outputs of the two selected pixels or the reciprocal thereof is calculated, and the difference calculation is performed for each pixel at each predetermined address. Thus, the state of blood flow distribution in the living tissue is detected.

A blood flow velocity measuring apparatus according to a second aspect of the invention sequentially captures an odd field image based on an odd scanning line based on a signal from the light receiving unit and an even field image based on a signal from an even scanning line as one set. , The even-numbered field image and the odd-numbered field image captured in the storage unit are combined and stored as a combined frame image, and the calculation unit calculates a blood cell based on at least three combined frame images in the stored image. It is characterized in that the velocity distribution state is calculated.

In the blood flow velocity measuring apparatus according to the third aspect, the image used for the calculation in the calculation unit is an image which has been subjected to coordinate conversion in order to correct the shift amount of the image on the light receiving element. Is characterized by.

In the blood flow velocity measuring apparatus according to the fourth aspect, the first to third pixel groups are further divided into two pixel groups having different pixel address positions, and each pixel of the two pixel groups is divided. It is characterized in that two predetermined combination pixels are selected from the group.

[0017]

DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 19 shows an outline of an optical system of a blood flow velocity measuring device, 1 is a laser beam irradiation system, 2 is a light receiving system, and E is an eye to be examined. The laser light of the laser light irradiation system 1 is applied to the fundus Er, which is a living tissue of the eye E to be inspected, through the half mirror 3, for example.

The light receiving system 2 has a light receiving lens 4, a CCD (solid-state image sensor) 5 as a light receiving portion, and a signal amplification circuit 6.
The laser reflected light from the fundus Er is C by the light receiving lens 4.
An image of a living tissue is formed on the CD5. The CCD 5 has a large number of pixels on its light-receiving surface, converts the biological tissue image formed by the light-receiving lens 4 into an electrical signal, reads out the signal charges by the frame accumulation method, and outputs it as a video signal. The video signal is amplified by the signal amplification circuit 6, and the video signal amplified by the signal amplification circuit 6 is output to the analog signal processing means 7 for performing gain control and the like, and converted into a digital signal by the A / D converter 8. It

Reference numeral 9 is a timing pulse generator, and 10
Is an electronic shutter control means, 11 is a solid-state image sensor driving means, and the timing pulse generator 9 outputs a timing pulse to the electronic shutter control means 10 and the signal selection means 12. The solid-state image pickup device driving means 11 is driven based on the timing pulse.

A digital signal as a video signal A / D converted by the A / D converter 8 is input to the signal selection means 12. The signal selecting means 12 is based on the timing pulse from the timing pulse generator 9 and is based on the A / D converter 8
Of the video signal from the first image recording means 13 is transmitted to the first image recording means 13, and the image of the odd field is transmitted to the second image recording means 13.
The image of the even-numbered field is stored in the first image recording means 13 and transmitted to the image recording means 14, and the second image recording means 1
An image of an odd field is recorded in 4. The signal selecting unit 12, the first image recording unit 13, and the second image recording unit 14 function as a part of an image capturing unit that captures a plurality of images at predetermined time intervals.

The image data of the odd field and the image data of the even field recorded in the first image recording means 13 and the second image recording means 14 are combined by the image combining means 15 and photographed at 1/30 second intervals. The image data of one frame is stored in the image recorder 16 as an image storage unit.

The image signal stored in the image recording unit 16 is input to the arithmetic processing unit 17, and the arithmetic processing unit 17 performs arithmetic processing described later. In addition, 18 is a TV monitor.

The arithmetic processing unit 17 takes three images, for example, taken at 1/30 second intervals from the image stored in the image recording device 16.
This is to take out a continuous image of one sheet and perform an operation based on the image signal.

The calculation processing section 17 first corrects the image shift amount of the three images before performing the calculation calculation of the fundus blood flow.
This correction is performed when there is a possibility that an image position shift will occur due to the influence of the involuntary eye movement of the subject's eye during the capture of the three images. The correction is performed by first detecting the correlation of images among the three images by the so-called template method, calculating the mutual positional deviation amount of each image based on the correlation, and based on this deviation amount, Coordinate conversion is performed in consideration of the image shift amount, and image information in which the shift between the three images is corrected is created (for the calculation of the image positional shift amount between these images, for example, Japanese Patent Application No. 2001-365419). No.). In addition, this coordinate transformation, if the deviation of the image can be ignored,
do not need.

The calculation method based on the three images in which the positional deviation of the image has been corrected will be described below.

FIG. 3 shows three images G1, G2, G3 as time series images stored in the image recorder 16. In FIG. 3, a 4 × 4 square represents a pixel group including a pixel group of interest, and A1, A2, and A3 represent output values of the pixel X at addresses n and m.

Here, assuming that the first row is a pixel group corresponding to the scanning lines O of the odd field, the second row is a pixel group corresponding to the scanning lines e of the even field, and the third row is an odd number. A pixel group corresponding to the scanning line O of the field,
The row is a pixel group corresponding to the scanning lines e of even fields.

Assuming that the SBR value based on the conventional equation 1 is calculated, the value of the denominator of the equation 1 is <│A1- <A>.
│ + │A2- <A> │ + │A3- <A>│> ² ,
The number of denominator differences is three. <A> is the average value,
<A> = (A1 + A2 + A3) / 3. Therefore, the numerator value is <A> ² .

Therefore, the SBR value in this case is SBR = <A> ² / <│A1- <A> │ + │A2- <A
> │ + │A3- <A>│> ² .

If the calculation is performed using only the three images shown in FIG. 3, the denominator sample number is 3
Since the number of samples is small, if the blood flow velocity is calculated using only three images, it is impossible to expect stable and highly accurate measurement.

Therefore, in the present invention, the calculation method described below is used. (Embodiment 1) In this embodiment, S of pixel X at addresses n and m
In order to obtain the BR value, the output value near the pixel X is incorporated in the calculation.

4 and 5 are enlarged views showing a part of a series of at least three images which are continuous in time series.

Here, each square represents a pixel, and here,
4x4 pixels are shown. When obtaining the calculated value corresponding to the SBR value of the pixel of address n, m (one predetermined address position in one image) X, as shown in FIG. Output value A of pixel X at address m
_i (i = 1, 2, 3) and the output values B _i (i = 1, 1) of the pixels at the addresses (n + 1) and (m + 1) at the lower right of the pixel X
2 and 3), and as shown in FIG.
For three time-series images, the pixel X of the address n, m
The output value D _i (i of the pixel at the address n, (m + 1) on the right of
= 1, 2, 3) and the output value C _i (i = 1, 2, 3) of the address (n + 1) and the pixel m immediately below the pixel X at the addresses n and m.
And a combination consisting of and.

Then, the difference is calculated from the output values in the combination of two pixels for the time series image shown in FIG. 4 and the output in the combination of two pixels for the time series image shown in FIG. Take the difference from the value.

That is, the first image G1 consisting of a plurality of pixels selected from the pixel X at one predetermined address position (n, m addresses) and the pixels located near the predetermined address position.
Pixel group and other images (second image G2, third image G
3) Select the second pixel group and the third pixel group located at the same address as the first pixel group. Then, two predetermined combination pixels are selected from the first pixel group to the third pixel group.

As a combination for obtaining the difference from the output value in the combination of the two pixels shown in FIG. 4, the number of pixels used for the calculation is two for each of the three time-series images. The total number of pixels used for the calculation is 6, and when the difference is calculated for all combinations of each pixel, ₆ C ₂ (15) difference values of the output values are obtained. In this case, the difference calculation results are (A1-B1), (A1-A2), (A1-B2),
(A1-A3), (A1-B3), (B1-A2),
(B1-B2), (B1-A3), (B1-B3),
(A2-B2), (A2-A3), (A2-B3),
(B2-A3), (B2-B3), and (A3-B3).

Similarly, as a combination for obtaining the difference from the output value in the combination of two pixels shown in FIG. 5, the number of pixels used for calculation is 2 for each of the three time-series images. Since the total number of pixels used in the calculation is 6, the difference between the output values of ₆ C ₂ (15) can be obtained by calculating the difference of all combinations of each pixel. become.

Therefore, the total number of pixels used in the calculation is 12, and the total sum S _{n, m} of the outputs is (A1 + A2
+ A3) + (B1 + B2 + B3) + ... + (D1 + D2 +
D3). This equation corresponds to the numerator of the pixel X at the address n, m, and the calculated sum _{Sn, m} 'is obtained by multiplying the average value of the sums by a factor of 2.5. No. 3 in the denominator
The average value of the sum of 0 differences is used. S _{n, m} '= (A1 + A2 + A3) + ... + (D1 + D2 +
D3) × 2.5 / 12 Here, the coefficient 2.5 times is the sum of the number of pixels of the denominator used for the calculation and the number of pixels of the numerator used for the calculation.

The above operation is performed from the address n = 1, m = 1 to the address n = n, m = m to obtain the operation value corresponding to the SBR value.

The reciprocal of the inverse of the denominator and the numerator is SB
It may be used as a calculated value based on the R value.

Here, the pixels corresponding to the odd fields and the pixels corresponding to the even fields are displaced by 1/60 seconds.

When such a calculation method is used, a large number of images for calculating the blood flow velocity are not required, and at least 3
S that shows blood flow velocity at the same speed as the conventional one using one image
A calculated value corresponding to the BR value can be obtained. (Embodiment 2) FIG. 7 shows S of the pixel X at the addresses n and m shown in FIG.
To obtain the calculated value corresponding to the BR value, the addresses n, (m + 1) pixel, address (n + 1), m pixel, address (n + 1), ( m + 1)
The output values A _{i to} D _i (i = 1, 2, 3) of these pixels are used for the calculation, and two of the twelve selected pixels are combined to obtain the difference. It was decided.

The number of pixels used for the calculation is 12,
Since two pixels are used to take the difference, the number of differences is
_{It is 12} C ₂ (= 66). The total output S _{n, m} is the same as that in the first embodiment.

In the second embodiment, the number of pixels used for calculating the numerator is 12, and the number used for obtaining the difference is 66. Therefore, the average value of the total sum S _{n, m} of the outputs is multiplied. The coefficient is 66/12 = 5.5.

In the case of the second embodiment, the same effect as that of the first embodiment can be obtained. (Embodiment 3) FIGS. 9 and 10 show the output value of the pixel at the address (n + 1), m shown in FIG. 9 for obtaining the calculated value corresponding to the SBR value of the pixel X at the address n, m shown in FIG. C _i (i = 1,
2 and 3) and output values B _i (i = 1, 2, 3) of the pixels at addresses (n + 1) and (m + 1), and FIG.
Output value B of the pixel at addresses (n + 1) and (m + 1) shown in 0
_{Using the combination of i} (i = 1, 2, 3) and the output value D _i (i = 1, 2, 3) of the pixel at address n, (m + 1), the difference between the output values and the sum S _{n , m} and are obtained.

The pixel shown in FIG. 9 is selected and the combination for obtaining the difference between the output values of the pixels is selected from two combinations of ₆ pixels. Therefore, ₆ C ₂ = 15 combinations, and the pixel shown in FIG. There are also ₆ C ₂ = 15 combinations for selecting the difference between the output values of the pixels by selecting, and therefore the number of pixels used for the denominator calculation is 30.

On the other hand, the number of pixels used for the sum S _{n, m} is 9
And the total sum S _{n, m} is S _{n, m} = C1 + B1 + C2 + B2 + C3 + B3 + D1 +
D2 + D3 The coefficient is 3.3.

Also in the case of the third embodiment, the same effect as that of the first embodiment is obtained. (Embodiment 4) FIGS. 12 and 13 show addresses n and m shown in FIG.
12 to obtain the value of the pixel X, the output values A _i (i = 1, 2, 3) and the addresses n, (n +
1) the output value C _i (i = 1, 2, 3) of the pixel and the output value D _i (i = 1, 2, 3) of the pixel of address n, (m + 1) shown in FIG. And address (n + 1),
The output value B _i (i = 1, 2, 3) of the (m + 1) pixel is divided into two combinations, and two of the six pixels shown in FIG. Along with taking
Two of the six pixels shown in FIG. 13 are selected and the difference between their output values is determined.

Also in this case, the number of pixels used for the calculation of the denominator is 30 as in the third embodiment, and the total sum S
The number of pixels used for the calculation of _{n and m} is 12, and the coefficient is 2.5.

Also in the case of the fourth embodiment, the same effect as that of the first embodiment can be obtained. (Embodiment 5) FIG. 15 shows the output values A _i (i = 1, 2, 3) and n of the pixels at addresses n and m for calculating the calculated value corresponding to the SBR value of the pixel X shown in FIG. , (M + 2) pixel output values F _i (i = 1, 2, 3), address (n + 1),
Output value B _i (i = 1, 2, 3) of pixel (m + 1), address (n + 2), output value E _i of pixel m (i = 1, 2,
3), output values G _i of pixels at addresses (n + 2) and (m + 2)
Two of the output values of the five pixels (i = 1, 2, 3) are selected, and the difference between them is determined.
The sum S _{n, m} is S _{n, m} = A1 + A2 + A3 + B1 + B2 + B3 + E1 +
E2 + E3 + F1 + F2 + F3 + G1 + G2 + G3 The number of the sum S _{n, m} used for the calculation is 15, and the combination of selecting 2 out of ₁₅ and taking the difference is ₁₅ C ₂
Therefore, there are 105 combinations of the numbers used for the difference of the denominator, and therefore, the coefficient by which the sum S _{n, m} is multiplied is 7.0. (Embodiment 6) FIG. 17 shows output values D _i (i = 1, 2, 3) of an address n and a pixel of (m + 1) for obtaining an operation value corresponding to the SBR value of the pixel X shown in FIG. (N + 1), m
Pixel output values C _i (i = 1, 2, 3), address (n +
1), output values B _i (i = 1, 2,
3), output values J _i of pixels at addresses (n + 1) and (m + 2)
Two of the output values H _i (i = 1, 2, 3) of the five pixels at (i = 1, 2, 3), the address (n + 2), and (m + 1) are selected. Then, the difference is determined. The total sum S _{n, m} is S _{n, m} = B1 + B2 + B3 + C1 + C2 + C3 + D1 +
D2 + D3 + H1 + H2 + H3 + J1 + J2 + J3 The number used to calculate the sum is 15, and the combination that selects two from 15 and takes the difference is ₁₅ C ₂ , so the combination of the number used for the difference of the denominator is 10
There are five ways, and therefore the coefficient by which the sum S _{n, m} is multiplied is
It is 7.0. (Embodiment 7) As shown in FIG. 18, three time-sequential images G ₁ , G ₂ , and G ₃ are taken out from a plurality of time-sequential images G _{1 to} G _N. The value of the pixel at the address n, m is calculated from n = 1, m = 1 to n = n, m = m using the calculation result of any of the first to sixth embodiments, and based on the calculation result. Obtain the blood flow velocity distribution.

Next, one image is shifted and three images G ₂ , G ₃ , and G ₄ which are continuous in time series are taken out, and the next blood flow velocity distribution is obtained. As described above, when the blood flow distribution velocity is calculated based on the three images while shifting the images used for calculating the blood flow velocity distribution one by one, the blood flow velocity distribution that changes with time is obtained.

With this, it is possible to obtain a temporal change of the blood flow velocity distribution and display the change of the blood flow velocity distribution on the screen 1 as a moving image.

[0053]

Since the present invention is configured as described above, it is not necessary to provide a large number of images for blood flow velocity calculation as in the conventional blood flow velocity measurement device, and at least three images can be displayed. If it can calculate the blood flow velocity with sufficient accuracy, it does not require a high-speed continuous image capturing device with a short shutter interval. For example, even a general image capturing device of 60 frames per second is sufficient. An effect that high measurement accuracy can be obtained is obtained.

[Brief description of drawings]

FIG. 1 is an explanatory diagram for explaining that an SBR value of pixels at addresses n and m in a series of N images is calculated based on output values of pixels at addresses n and m of each image. Is.

FIG. 2 is an S obtained using the series of images shown in FIG.
It is an explanatory view for explaining an example of a blood flow velocity distribution displayed on a screen based on a BR value.

FIG. 3 is a description of a neighboring pixel group used to obtain a calculated value corresponding to an SBR value of pixels at addresses n and m of three images that are consecutive in time series among a series of time series images. It is a figure.

FIG. 4 is an explanatory diagram of pixels which are divided into two groups and used for one of the groups to obtain an operation value corresponding to the SBR value shown in the first embodiment of the present invention. It is a figure which expands and shows the pixel of 4 rows 4 columns.

5 is an explanatory diagram of pixels that are used in the other group by dividing them into two groups in order to obtain a calculated value corresponding to the SBR value shown in Example 1 of the present invention. It is a figure which expands and shows the pixel of 4 rows 4 columns.

FIG. 6 is an explanatory diagram of a pixel X for obtaining a calculated value corresponding to an SBR value according to the second embodiment of the present invention, which is an enlarged view of a pixel in row 4, column 4 of the pixel group shown in FIG. 3; is there.

FIG. 7 is an explanatory diagram in the vicinity of a pixel X used for obtaining a calculated value corresponding to an SBR value shown in Example 2 of the present invention.

FIG. 8 is an explanatory diagram of a pixel X for obtaining a calculated value corresponding to an SBR value according to the third embodiment of the present invention, which is an enlarged view of a pixel in row 4 and column 4 of the pixel group shown in FIG. is there.

FIG. 9 is an explanatory diagram of pixels which are divided into two groups and used in one of the groups to obtain a calculated value corresponding to an SBR value shown in Example 3 of the present invention.

FIG. 10 is an explanatory diagram of pixels which are divided into two groups and are used in the other group in order to obtain a calculated value corresponding to the SBR value shown in Example 3 of the present invention.

FIG. 11 is an explanatory diagram of a pixel X for obtaining a calculated value corresponding to an SBR value according to the fourth embodiment of the present invention, which is an enlarged view of a pixel in row 4, column 4 of the pixel group shown in FIG. 3; is there.

FIG. 12 is an explanatory diagram of pixels which are divided into two groups and used in one of the groups to obtain a calculated value corresponding to an SBR value shown in Example 4 of the present invention.

FIG. 13 is an explanatory diagram of pixels which are divided into two groups and are used in the other group in order to obtain a calculated value corresponding to the SBR value shown in Example 4 of the present invention.

FIG. 14 is an explanatory diagram of a pixel X for obtaining a calculation value corresponding to an SBR value according to the fifth embodiment of the present invention, which is an enlarged view of a pixel in row 4 and column 4 of the pixel group shown in FIG. is there.

FIG. 15 is an explanatory diagram of the vicinity of a pixel X used to obtain a calculated value corresponding to an SBR value shown in Example 5 of the present invention.

FIG. 16 is an explanatory diagram of a pixel X for obtaining a calculated value corresponding to an SBR value according to the sixth embodiment of the present invention, which is an enlarged view of a pixel in row 4 and column 4 of the pixel group shown in FIG. is there.

FIG. 17 is an explanatory diagram in the vicinity of a pixel X used to obtain a calculated value corresponding to an SBR value shown in Example 6 of the present invention.

FIG. 18 is an explanatory diagram of a time-series image group according to the seventh embodiment of the present invention.

FIG. 19 is a diagram showing a main configuration of a blood flow velocity measuring device of the present invention.

[Explanation of symbols]

1 ... Laser light irradiation system (laser light irradiation part) 5 ... CCD (light receiving part) 16 ... Image recorder (storage unit) 17 ... Arithmetic processing unit

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁷ identification code FI theme code (reference) G06T 7/20 A61B 5/02 340D (72) Inventor Hitoshi Fujii 2-26, Hisato, Munakata-shi, Fukuoka 8 (72) Inventor Naoki Konishi, 232-15 F term, Niho, Shonai-cho, Kaho-gun, Fukuoka Prefecture (reference) 2G059 AA05 BB12 CC16 EE02 GG01 JJ22 JJ23 KK04 MM01 MM09 MM10 4C017 AA11 AC28 BC11 5B057 AA10 BA02 CA08 CA20 DB16 DB01 CD01 DA01 5L096 AA06 BA06 BA13 CA04 FA25

Claims (4)

[Claims] 1. A laser light irradiating section for irradiating blood cells of living tissue with laser light, a light receiving section composed of a plurality of light receiving elements for detecting reflected light from the living tissue, and light reception based on a signal from the light receiving section. A storage unit for sequentially recording a plurality of images formed on a set, and at least 3 of the stored images
Comprising a calculation unit for calculating the distribution state of the blood cell velocity based on a single image, the calculation unit, from the pixel at one predetermined address position in one image and the pixel located near the predetermined address The first pixel group including a plurality of selected pixels and the second and third pixel groups located at the same address as the first pixel group in other images are selected, and the first pixel group is selected. Or third
By selecting two predetermined combination pixels from the pixel group, calculating the average value of the sum of the differences between the outputs of the two selected pixels or the reciprocal thereof, and performing the difference calculation for each pixel at each predetermined address, A blood flow velocity measuring device characterized by detecting a blood flow distribution state in a biological tissue. 2. An even field image sequentially captured as a set of an odd field image based on an odd scanning line and an even field image based on a signal of an even scanning line based on a signal from the light receiving unit, and the even field image captured in a storage unit. 2. The odd-numbered field image is combined and stored as a combined frame image, and the calculation unit calculates the distribution state of blood cell velocities based on at least three combined frame images in the stored images. Blood flow velocity measuring device. 3. The blood flow according to claim 1, wherein the image used in the calculation by the calculation unit is an image that has been subjected to coordinate conversion in order to correct the image shift amount on the light receiving element. Speed measuring device. 4. The first to third pixel groups are further divided into two pixel groups having different pixel address positions, and two predetermined combination pixels are included in each of the two pixel groups. The blood flow velocity measuring device according to claim 1, which is selected.