JP2001272328A - Particle measurement apparatus by means of image - Google Patents

Abstract

PROBLEM TO BE SOLVED: To efficiently measure particles. SOLUTION: This device has a flow cell which enables a parallel flow of plural particles included in a liquid, first and second image pickup parts simultaneously picking up images of the plural particles flowing inside the flow cell from crossed two axial directions, and an analysis part analyzing the first and second images picked up by the first and second image pickup parts. The analysis part makes the particles in the first image correspond to the particles in the second image to specify the respective same particles, and calculates the characteristics of the respective specified same particles, on the basis of particle image data gotten from the first and second images.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a particle measuring device, and more particularly to a measuring device for measuring particles such as industrial powders, organic powders, and in vivo particles.

[0002]

2. Description of the Related Art Conventionally, a particle measuring apparatus and method for wrapping a particle-containing liquid in a sheath liquid and flowing the same in a flow cell and optically measuring the characteristics of each particle in two directions in a state where the particles are arranged in a line. (Flow cytometry) is known (for example, refer to JP-A-1-296136).

[0003]

However, in such a conventional particle measuring apparatus and method, there is a problem that the measurement efficiency is low because a plurality of particles cannot be flown in parallel. The present invention has been made in view of such circumstances, and it is possible to efficiently measure the characteristics of particles by flowing a plurality of particles in parallel in a flow cell and imaging them from two directions. A particle measuring device is provided.

[0004]

SUMMARY OF THE INVENTION The present invention is directed to a flow cell capable of flowing a plurality of particles contained in a liquid in parallel, and substantially simultaneously imaging a plurality of particles flowing through the flow cell from two axial directions crossing each other. First and second imaging units to perform
An analysis unit configured to analyze the first and second images captured by the first and second imaging units, wherein the analysis unit associates particles in the first image with particles in the second image and associates them with each other; It is an object of the present invention to provide a particle measuring apparatus characterized in that particles are specified, and characteristics of the specified same particles are calculated using particle image data obtained from first and second images.

[0005]

DETAILED DESCRIPTION OF THE INVENTION The flow cell used in the present invention is as follows.
It is possible to flow a plurality of particles of the order of 100 μm in parallel, and thus the flow path (orifice) is larger than before, for example, having a rectangular cross section of 1 mm × 1 mm.

[0006] A transparent liquid, for example, a particle-containing liquid in which target particles are dispersed in water is supplied to the flow cell. At this time, since the particle-containing liquid passes through the orifice as it is, there is no need to supply a sheath liquid. It is.

The target particles of the present invention include fine powders of inorganic substances such as fine ceramics, toners, pigments and powders for cosmetics, powders of organic substances such as food additives, microscopic organisms such as plankton, blood cells, In vivo particles such as cells are included.

[0008] The first and second of the particle measuring apparatus of the present invention
The imaging unit intersects a plurality of particles flowing through the flow cell.
Although provided so that imaging can be performed from the axial direction, it is preferable that these two intersecting axes are orthogonal to each other on a plane crossing the flow cell in order to clearly measure the characteristics of the particles from the two directions. The first and second imaging units include a light source that irradiates each imaging region of the flow cell, for example, a pulse laser, and an imaging device that images each imaging region, for example, a CCD.

The analysis unit of the present invention includes a CPU, a ROM,
A microcomputer or a personal computer having a RAM or the like can be used. The analysis unit preferably further includes an input unit for inputting analysis conditions and a display unit for outputting analysis results. The analysis unit performs a process of identifying the same particle by associating particles in the image captured by the first imaging unit with particles in the image captured by the second imaging unit.

That is, regarding the particles in the first image and the particles in the second image, (1) the position (for example, the position of the center of gravity) in the flow direction of the particles, (2) the size (vertical width) in the flow direction of the particles,
By comparing at least one item of (3) flatness of particles, the particles can be associated with each other and the same particle can be specified. By comparing a plurality of items, the accuracy of the association can be improved. For this purpose, for example, a value reflecting {(position in the flow direction of particles) ² + (size in the flow direction of particles) ² + (flatness of particles) ² } ^1/2 can be used.

The characteristics of each identical particle specified by the associating process are calculated using image data from two directions, that is, particle image data obtained from the first and second images. The characteristics of the particles include, for example, particle volume, average diameter,
For example, the number of particles.

It is preferable that each of the first and second image pickup units has two image pickup devices and constitutes a shadow picture image pickup unit and a contour emphasized image pickup unit. The shadow picture image capturing unit can be configured by forming light emitted from the imaging region of the flow cell on one of the imaging devices via a lens and a pinhole, and the contour-enhanced image capturing unit emits light emitted from the imaging region of the flow cell. It can be configured by forming an image on the other image sensor via a lens and a spatial filter. In addition,
As the spatial filter, for example, a light-shielding plate having a ring-shaped light-transmitting portion having a predetermined radius with respect to the optical axis can be used.

Each of the first and second image pickup sections includes the shadow picture image pickup section and the contour emphasized image pickup section as described above, so that the particle size (sub) of the following regions (a) to (c) can be obtained. (Microns to hundreds of microns).

That is, when the particle diameter is d and the wavelength of the irradiation light is λ, (a) those in the diffraction / scattering region. This is a region where d> λ × (2 to 10) and the light irradiated to the particle is diffracted and scattered at the periphery of the particle. The intensity of the diffracted and scattered light is affected by the complex refractive index of the particle surface. In addition, the radiation angle distribution becomes independent of the particle size. Therefore, there is no clear correlation between the particle size and the diffraction / scattered light in this region.

(B) Those in the Mie scattering region. This is a region of λ × (0.5 to 1) <d <λ × (2 to 10). According to Mie scattering theory, scattered light is generated as a combination of electromagnetic waves radiated from an electric field distribution formed on the surface. Occurs. In this case, the scattered light distribution and intensity are affected by the state of the electric field distribution formed on the surface.

(C) Those in the Rayleigh scattering region. This is a region of d <λ × (0.5 to 1). In this region, the particle is considered as a dipole oscillator, and the particle size and the scattered light intensity have linearity. This is the area where scattered light is concentrated.

In the present invention, by providing the shadow picture image pickup section, particles having a particle size in the diffraction / scattering area and the Mie scattering area are picked up by the image pickup element like a shadow picture.
Particles having a particle size in the Rayleigh scattering region are imaged as bright points (Rayleigh scattering image), and all particle images in the flow cell are imaged.

Further, by providing the contour-enhanced image pickup section, particles having a particle diameter in the diffraction / scattering region and the Mie scattering region are picked up with a bright outline and a dark center, so that a plurality of particles are partially captured. Each particle can be identified even if they overlap. Particles having a particle size in the Rayleigh scattering region are imaged as bright spots.

Therefore, if the images obtained by the two image pickup units are superimposed and integrated, submicron to several hundreds of
An image of particles having a micron size can be obtained, and an image that can identify partially overlapping particles can be obtained.

Hereinafter, the present invention will be described in detail with reference to embodiments shown in the drawings. This does not limit the present invention.

FIG. 1 is a structural explanatory view showing one embodiment of the particle measuring apparatus of the present invention. This particle measuring apparatus simultaneously captures a flow cell 11 capable of flowing a plurality of particles contained in a liquid in parallel from a plurality of particles flowing through the flow cell 11 from two axial directions (orthogonal directions in this embodiment). A first imaging unit Sa and a second imaging unit Sb, an analysis unit 20 that analyzes images captured by the first and second imaging units Sa and Sb, and a display unit 30 that displays an analysis result of the analysis unit 20. Input section 40 for setting analysis conditions and display conditions
Is provided.

The first imaging unit Sa includes a pulse light source 1a composed of a pulsed semiconductor laser that emits a laser beam having a wavelength of 780 nm, a lens 2a that converts light from the light source 1a into parallel light, and a light from the lens 2a. A light source unit including a lens 3a for guiding to the flow cell 11, and an imaging lens 6 for transmitting light from the flow cell 11 through a pinhole at the center of the mirror 5a.
a, and a shadow picture image pickup unit composed of an image pickup element 7a that receives light from the imaging lens 6a and picks up an image. The light reflected from the lens 4a by the mirror 5a and guided through the spatial filter 8a. Image sensor 1
A contour-enhanced image capturing unit including an imaging lens 9a for forming an image at 0a is provided.

The second imaging unit Sb includes a pulse light source 1b composed of a pulsed semiconductor laser that emits a laser beam having a wavelength of 780 nm, a lens 2b that converts light from the light source 1b into parallel light, and a light from the lens 2b. A light source unit including a lens 3b for guiding to the flow cell 11, and an imaging lens 6 for transmitting light from the flow cell 11 through a pinhole at the center of the mirror 5b.
b, and a shadow picture image pickup unit composed of an image pickup element 7b that picks up an image by receiving light from the imaging lens 6b, and light reflected from the lens 4b by the mirror 5b and guided through the spatial filter 8b. Image sensor 1
A contour-enhanced image pickup unit including an imaging lens 9b for forming an image at 0b is provided.

Here, in the shadow picture image pickup section, the image pickup element 7 is used.
a and 7b capture the silhouette of the particles flowing through the flow cell 11 as a particle image (shadow picture), and in the contour-enhanced image capturing section, the imaging elements 10a and 10b
The particle image (outline emphasized image) in which the outline of the particles flowing through the image is enhanced by the action of the spatial filter 8a can be captured.

The flow cell 11 is made of inorganic glass, has a flow channel 12 having a cross-sectional dimension of 1 mm × 1 mm, and has a rectangular cylindrical shape with four surfaces optically polished. The mirrors 5a and 5b are disc-shaped mirrors having a pinhole with a diameter of 10 to 100 μm at the center.

Each of the image sensors 7a, 7b, 10a, and 10b has a 1/3 inch CCD board camera, CCB
-37BE (manufactured by Sony Corporation) is used. Each of the spatial filters 8a and 8b is a light-shielding plate having a ring-shaped light-transmitting portion around the optical axis. The analysis unit 20 is constituted by a personal computer, and the display unit is constituted by a CRT.
The input unit 40 is composed of a keyboard and a mouse.

In such a configuration, as shown in FIG. 2, the particle-containing liquid (particle P1) flowing in the flow path 12 in the direction of arrow C is used.
To P6) from the directions of arrows A and B (directions orthogonal to each other) by the first and second imaging units Sa and Sb, respectively.

In FIG. 2, particles P1 and P3 have a particle size in the Mie scattering region, particles P2 and P5 have a particle size in the diffraction / scattering region, and particles P4 and P6 have a particle size in the Rayleigh scattering region. Have. The imaging devices 7a and 7b project images of all particles in the imaging region, and the imaging devices 10a and 10b combine a clear image of particles within the depth of focus and a blurred image of particles outside the depth of focus. You can get it.

FIGS. 3 and 4 show shadow picture images obtained by the image pickup devices 7a and 7b, respectively.
FIG. 5 and FIG. 6 show the edge-enhanced image obtained by 0b, respectively. When such an image is obtained, the analysis unit 20
Performs image processing based on the flowchart shown in FIG.

That is, the analyzing unit 20 fetches the shadow picture image shown in FIG. 3 and FIG.
In step 2, the contour emphasized images shown in FIGS. Then, the luminance of each pixel of the captured image is ternarized in step S3. When the process is completed (step S4), a process of integrating the shadow picture image and the contour enhanced image captured in the same direction is performed (step S5).

Then, clustering is performed on the integrated image (step S6), and features are extracted from the image (step S7). When the processing up to this point is completed (step S8), the correspondence between the particle images is performed based on the obtained characteristics (step S9), and the characteristic parameters of the associated particles are calculated (step S10).

Next, the processing contents of each processing step will be described in detail. Step S1 The images captured in this step are shown in FIGS.
As shown in (1), particles obtained in the imaging directions A and B, respectively, have a particle diameter of the diffraction / scattering region and the Mie scattering region in which the whole particle is uniformly darkly imaged, and a particle diameter of the Rayleigh scattering region. Particles appear as bright spots.

Step S2 The images captured in this step are shown in FIGS.
As shown in FIG. 8, particles obtained from the imaging directions A and B, respectively, and particles having a particle size larger than the Mie scattering region within the depth of focus have bright contours due to the action of the spatial filters 8a and 8b, The portion is imaged dark, and particles having a particle size in the Rayleigh scattering region appear as bright spots as in the image in Step 1.

Step S3 In this step, four obtained images (FIGS. 3 to 6)
In contrast, a particle image (black) of the background (gray) portion, the diffraction / scattering region and the Mie scattering region, and a contour portion (white) of the particles other than the Rayleigh scattering region in the Rayleigh scattering region particle image and the contour enhanced image ), A ternarization process for dividing into three color areas is performed. The procedure is shown in the flowchart of FIG.

First, in order to obtain two threshold values required for the ternarization processing, a frequency distribution (histogram) of luminance of all pixels is created for each image as shown in FIG. 8 (step S101). The luminance is calculated as M and N corresponding to the two valleys of the frequency distribution (step S102). Next, the luminance of each pixel is compared with threshold values M and N. At this time, an XY coordinate system orthogonal to the image is set, the coordinates of the upper left pixel of the image are P (0,0), and the coordinates of the lower right pixel are P (Xma
x, Ymax), and when the luminance is smaller than the threshold value M (step S103), a binary number 00 (black) is written as pixel information in the pixel P (X, Y) (step S104). Similarly, if the altitude is above the threshold M and the threshold N
If the pixel P (X,
A binary number 01 (gray) is written in Y) (step S106). Further, a pixel P whose luminance is equal to or higher than the threshold
A binary number 10 (white) is written in (X, Y). This process is repeated for all pixels (step S10)
8). Table 1 summarizes the ternary pixel data in this way, for example.

[0036]

[Table 1]

Step S5 In this step, the shadow picture image and the contour emphasis image existing in each of the imaging directions A and B are overlapped to form one integrated image. At this time, all the particle images in the flow cell 11 are projected on the shadow picture image, and only clear images of particles within the depth of focus are captured on the contour enhanced image.

That is, the presence of particles in the cell is superior to the shadow picture, and the contour emphasized image is superior to clearly showing the contour of the particles. Therefore, the particle image of the diffraction / scattering region and the Mie scattering region is black, the background is gray, the particle image of the Rayleigh scattering region is dark gray, and the contours of the particles in the diffraction / scattering region and the Mie scattering region are represented by four colors of white. And Table 2 below. Thus, the integrated images shown in FIGS. 10 and 11 are obtained.

Details of the processing in this step are shown in the flowchart of FIG. That is, for the shadow picture image and the contour enhanced image in the same direction, when the ternary pixel data of the coordinates P (X, Y) is not 01 for the shadow picture image and 00 for the contour enhanced image (step S201), the pixel P ( X,
Y (gray) is written into Y) as integrated pixel data (step S202).

Next, when the ternarized pixel data of the coordinates P (X, Y) is 01 for the shadow picture and 00 for the contour enhanced image (step S203), and 00 for the shadow picture and not 10 for the contour enhanced image. In this case (step S204), 00 (black) is written to the pixel P (X, Y) of the integrated image (step S204).
205).

In the case of 00 for the shadow picture image and 10 for the contour enhanced image (step S206), 10 (white) is written to the element P (X, Y) of the integrated image. Also, instead of 00 in the shadow picture,
If it is not 10 in the contour emphasized image, the pixel P of the integrated image
Write 11 (dark ash) to (X, Y). This process is repeated for all pixels (step S209). Table 2 summarizes the pixel data integrated in this way.

[0042]

[Table 2]

In Table 2, 00 (black) represents an image of the diffraction / scattering region and Mie scattering region particles, 01 (gray) represents the background, and 10 (white) the outline of the diffraction / scattering region and Mie scattering region particles. And 11 (dark ash) represents Rayleigh scattering region particles in the integrated image.

As described above, in detecting the presence or absence of particles, the shadow picture image is superior to the contour emphasis image. Therefore, in the integration processing, a small luminescent spot appears at the coordinates P (X, Y) of the shadow picture image, and when it does not appear in the contour emphasized image, the coordinates P (X, Y) are added to the Rayleigh scattering region in consideration of superiority. Considering that the particles included are present, the bright spot is written as an effective image in the integrated image.

Step S6 All particle images in each of the integrated images shown in FIGS. 10 and 11 are classified (clustered) based on the pixel data, and labels (1A, 2A,...)
(1B, 2B, ...).

After the clustering in step S7 , the maximum horizontal width (f [] [0]), the maximum vertical width (f [] [1]), The class center of gravity (f [] [2], f [] [3]) is calculated as a morphological parameter. All classes A1 to 6A in FIG.
Are shown in Table 3 and the form parameters for all classes 1B to 5B in FIG. 11 are shown in Table 4.

[0047]

[Table 3]

[0048]

[Table 4]

Step S9 In this step, a process is performed for associating which class (particle) of the integrated image in FIG. 10 and which class (particle) in the integrated image of FIG. 11 are the same particle. At this time, the class of the integrated image in FIG. 10 is focused on one by one, and the class vertical width (f [] in Table 3) centered on the Y coordinate (f [] [3] in Table 3) of the center of gravity of the focused class. Within the range (search range) of [1]), a class having the Y coordinate of the center of gravity (f [] [3] in Table 4) is selected from the classes of the integrated image in FIG.

Tables 3 and 4 of these two classes
Is substituted into the following evaluation function D to quantitatively calculate the strength of the correlation. Then, one class (potential class) in which D has the minimum value, that is, the correspondence is considered to be influential, is selected. Next, a class in which the Y coordinate of the center of gravity (f [] [3] in Table 3) falls within the search range is shown in FIG.
Select from 0.

Then, the morphological parameters of the class selected from FIG. 10 and the class selected from FIG. 11 described above are substituted into the evaluation function D, and the strength of the correlation is calculated as a quantitative value.
The combination having the smallest value among D obtained in this way is determined to be a class having a true correspondence. D = {(the center of gravity of the difference between the Y-coordinate) ² + (difference of the vertical width) (the difference in aspect ^{ratio) 2 + 2} 1/2 D =} [(f B [k B] [3] -f A [m ] [3]) ² + (f _B [k _B ] [1]-
f _A [m] [1]) ² + {(f _B [k _B ] [0] / f _B [k _B ] [1])-(f _A [m] [0] / f _A [m]
[1])} ² ] ^1/2 m: the number of the class of interest in FIG. 10 k _B : the class number in FIG.

This process will be described more specifically with reference to Table 5. First, the class 1A in Table 3 is changed to the class of interest Cp.
And The vertical width (f [] [1]) of the class 1A centered on the Y coordinate (f [] [3]) of the center of gravity of the class 1A is calculated as a search range.
1.5 to 112.5 (see Table 5).

Next, from FIG. 11, a candidate class Cr including the Y coordinate of the center of gravity of the class is selected within this search range. In this case, as shown in Table 5, only one class 2B is selected as the candidate class Cr. Therefore, 15.2 is obtained by substituting the morphological parameters of the classes 1A and 2B into the evaluation function D. Since there is only one candidate, 2B is set as a promising candidate.

Next, a class in which the Y coordinate of the center of gravity is included in the search range based on 1A is selected as a class Cq from FIG. Then, since the class 3A exists, the morphological parameters of the classes 3A and 2B are substituted into the evaluation function D. As a result, the value of 3.6 (Table 5), which is smaller than the value of 15.2 of the above D, indicates that classes 3A and 2B correspond rather than classes 1A and 2B. Therefore, it can be determined that the class corresponding to 1A does not exist.

Next, finding a class corresponding to the class 4A will be described as an example. At this time, the search range is 110 to
At 190 (Table 5), two classes 3B and 4B are obtained as candidates for the class in FIG. 11 included in the range. When the evaluation function D is applied to each of these two cases, the case of 3B is 7, 3, and the case of 4B is 63.6 (Table 5). Therefore, the corresponding probable candidate is 3B.

Next, there is a class 5A as a class in FIG. 10 included in the previous search range. Class 5
When the evaluation function D is applied to A and 3B, it becomes 61.1, and 4
Since the evaluation function values 7.3 of A and 3B are smaller than the evaluation function values 61.1 of 5A and 3B, it can be determined that the class 3B corresponds to the class 4A.

Further, a limit function L is provided as an upper limit of the evaluation function value when calculating a series of evaluation functions. When an evaluation function value exceeding this value is taken, it is determined that the association is inappropriate. The results of associating all the classes in FIG. 10 with the classes in FIG. 11 in this manner are shown in Table 5 by ○ and X (○ indicates a correspondence, X indicates no correspondence).

[0058]

[Table 5]

As described above, for one of the attention classes of the integrated image in FIG. 10, one influential candidate is selected from the candidates in the integrated image in FIG. 11, and the candidate is not immediately determined. Accurate association can be realized by reconfirming whether another class corresponding to the influential candidate exists in the integrated image of FIG.

In this evaluation function D, (1) f _B [k _B ] [3] -f _A [m] [3] is the Y coordinate of the center of gravity of the candidate class in the image of FIG. This is the difference from the barycenter Y coordinate of the class of interest in the image, and the condition when the candidate class is selected is within the range of the vertical width f _A [m] [1] of the class centered on the barycenter Y coordinate of the reference class. Because it is possible to enter
The maximum possible value of this term is (f _A [m] [1]) /
2

(2) f _B [k _B ] [1] -f _A [m] [1] is the difference between the height of the candidate class in FIG. 11 and the height of the class of interest in FIG. From the corresponding candidates, the difference is shown in FIG.
Since it is unlikely to take a value twice as large as the height of the class of interest in 0, the maximum value of this term is set to 2 × f _A [m] [1].

(3) (f _B [k _B ] [0] / f _B [k _B ] [1]) − (f _A [m]
[0] / f _A [m] [1]) is the aspect ratio of the candidate class in FIG.
The difference between the aspect ratio of the class of interest in FIG. 10 and the maximum value that this term can possibly have is MAX [max (f
_B [k _B ] [0] / f _B [k _B ] [1])-min (f _A [m] [0] / f _A [m] [1])
, Min (f _B [k _B ] [0] / f _B [k _B ] [1])-max (f _A [m] [0] / f
_A [m] [1])]. Therefore, the limit L value is L = [(f _A [m] [1]) / 2} ² + (2 × f _A [m] [1]) ² + (MAX [max (f _B [k _B ]
[0] / f _B [k _B ] [1])-min (f _A [m] [0] / f _A [m] [1]), min (f _B [k _B ]
[0] / f _B [k _B ] [1])-max (f _A [m] [0] / f _A [m] [1])] ² ] ^1/2 If this value L is exceeded, it is determined that there is no correspondence even if the possibility of correspondence is the highest among the candidate classes.

Step S10 : A coordinate position based on the real space is calculated from the optical system based on the coordinates on the image of the pair of classes for which the correspondence has been clarified, and a geometric calculation is performed based on the calculated position. Thus, the actual size of the particle and the position in the space can be calculated without performing the correction. Further, statistical processing is performed based on the value of each particle to calculate a particle size distribution.

[0064]

According to the present invention, since particles flowing in parallel in the flow cell are imaged and measured simultaneously, measurement efficiency is improved. Further, since a plurality of particles flowing in the flow cell are simultaneously imaged from two intersecting directions, image data of one particle is obtained from two directions, and the amount of information is larger than that of the image data from one direction. More detailed information can be grasped. In addition, the imaging unit is composed of a shadow picture image capturing unit and a contour enhanced image capturing unit, and by integrating the images obtained by them, it is possible to measure particles having a diameter of submicron to several hundreds of microns.

[Brief description of the drawings]

FIG. 1 is a configuration explanatory diagram of an embodiment of the present invention.

FIG. 2 is a perspective view showing particles flowing through a flow channel of the flow cell of the example.

FIG. 3 is a shadow picture image captured in the embodiment.

FIG. 4 is a shadow picture image captured in the embodiment.

FIG. 5 is an outline-enhanced image captured in the embodiment.

FIG. 6 is an outline-enhanced image captured in the embodiment.

FIG. 7 is a flowchart illustrating image processing in the embodiment.

FIG. 8 shows an example of a luminance distribution of an image in the embodiment.

FIG. 9 is a flowchart illustrating ternarization processing in the embodiment.

FIG. 10 is an integrated image in the embodiment.

FIG. 11 is an integrated image in the embodiment.

FIG. 12 is a flowchart illustrating an image integration process according to the embodiment.

[Explanation of symbols]

 Reference Signs List 11 flow cell 20 analyzing unit 30 display unit 40 input unit Sa first imaging unit Sb second imaging unit 1a light source 1b light source 2a lens 2b lens 3a lens 3b lens 4a lens 4b lens 5a mirror 5b mirror 6a imaging lens 6b imaging lens 7a Image sensor 7b Image sensor 8a Spatial filter 8b Spatial filter 9a Image forming lens 9b Image forming lens 10a Image sensor 10b Image sensor

Continued on the front page (72) Inventor Yasuyuki Ison 1-5-1, Wakihama Kaigandori, Chuo-ku, Kobe City Inside Sysmex Corporation (72) Inventor Masaki Ishizaka 1-5-1, Wakihamakaigandori, Chuo-ku, Kobe City Sysmex In-house F-term (reference) 2F065 AA04 AA26 AA51 BB07 BB15 DD06 FF04 JJ03 JJ05 JJ26 LL12 LL21 LL30 QQ03 QQ08 QQ21 QQ25 QQ29 QQ32 QQ43 SS13 2G059 AA05 BB04 CC19 DD12 EE02 GG01 GG01 GG01 GG03

Claims (6)

[Claims] 1. A flow cell capable of flowing a plurality of particles contained in a liquid in parallel, and a first and a second imaging unit for imaging the plurality of particles flowing through the flow cell substantially simultaneously from two axial directions intersecting each other. And an analysis unit that analyzes the first and second images captured by the first and second imaging units, wherein the analysis unit associates particles in the first image with particles in the second image. A particle measuring device for identifying the same particle by using the particle image data obtained from the first and second images. 2. The analysis unit according to claim 1, wherein the particle in the first image and the particle in the second image are: (1) a position in a flow direction of the particle;
(2) the size of the particles in the flow direction, (3) the flatness of the particles,
2. The particle measuring apparatus according to claim 1, wherein the same particles are specified by comparing at least one of the following items to identify the same particles. Wherein the analysis unit, for particles in the particles and the second image of the first in the image, {(difference in position in the flow direction of particles) ²
+ (Difference in size in the flow direction of particles) ² + (difference in flatness)
^2. The particle measuring device according to claim 1, wherein the correlation is performed based on a value reflecting ² ｝ ^1/2 . 4. The first and second imaging units each include a light source for illuminating the flow cell, a shadow image capturing unit, and a contour enhanced image capturing unit, and the shadow image capturing unit captures the illuminated flow cell. An image sensor, comprising a pinhole member inserted in an optical path from the flow cell to the first image sensor,
The contour-enhanced image capturing unit includes a second image sensor that captures an image of the illuminated flow cell, and a spatial filter that is inserted into an optical path from the flow cell to the second image sensor and that has a ring-shaped light transmitting unit having a predetermined radius from the optical axis. The particle measuring device according to claim 1 provided with. 5. The particle measuring device according to claim 4, wherein the spatial filter is a light shielding plate. 6. The particle measuring apparatus according to claim 5, wherein the first and second images are integrated images of images by a shadow picture image capturing unit and a contour enhanced image capturing unit, respectively.