Patent Publication Number: US-2021182530-A1

Title: Measurement device and measurement method

Description:
CROSS-REFERENCE 
     This application claims priority to Japanese Patent Application No. 2019-227645, filed on Dec. 17, 2019, and Japanese Patent Application No. 2020-205362, filed on Dec. 10, 2020, the entire contents of which are incorporated herein by reference. 
     FIELD 
     The present disclosure relates to a measurement device and a measurement method. 
     BACKGROUND 
     As one type of urine test methods, a method is known which image-captures a urine specimen flowing through a flow path provided in a flow cell and analyzes an captured image to sort sediments (tangible (solid) components in the urine such as blood cells, epithelial cells, casts, bacteria, and crystals) in urine into different types of components (see, e.g., Patent Document 1 and Patent Document 2). 
     DOCUMENT OF RELATED ART 
     Patent Document 
     
         
         [Patent Document 1] Japanese Laid-Open Patent Publication No. H06-288895 
         [Patent Document 2] Japanese Laid-Open Patent Publication No. H11-94727 
       
    
     SUMMARY 
     An aspect of a technique according to the disclosure is shown by way of example by a measurement device as described below. A measurement device includes an acquisition unit and a calculation unit. The acquisition unit acquires a first image obtained by image-capturing liquid containing tangible components flowing through a flow path and a second image image-captured simultaneously with the first image and having an image-capturing magnification higher than that of the first image. The calculation unit sorts, by using clipped images obtained by clipping the tangible components included in the first image and the second image, the tangible components into different types, and that calculates, by using a total number of the tangible components clipped out of the first image and included in a specified category as well as a ratio of a number of each of the tangible components of the different types clipped out of the second image and included in the specified category relative to a total number of the tangible components in the specified category, the number of the tangible components included in the specified category. 
     The technique according to the disclosure sorts the tangible components contained in the liquid and can increase the accuracy of calculating the numbers of the sorted tangible components. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram illustrating a schematic configuration of a measurement device according to an embodiment; 
         FIG. 2  is a diagram illustrating a schematic configuration of a flow cell; 
         FIG. 3  is a diagram illustrating a schematic configuration of the vicinity of each of a confluent portion and a tapered portion; 
         FIG. 4  is a diagram illustrating distributions of a sheath fluid and a specimen each flowing through a fourth path; 
         FIG. 5  is a diagram illustrating an example of respective images captured by a first image capturing unit and a second image capturing unit; 
         FIG. 6  is a flow chart illustrating a flow of sorting of tangible components in the embodiment; 
         FIG. 7  is a flow chart illustrating a flow of the sorting of the tangible components and calculation of the numbers of the tangible components in the embodiment; 
         FIG. 8  is a diagram illustrating an example of results of the sorting of the tangible components and the calculation of the number of the tangible components each based on a first image; 
         FIG. 9  is a diagram illustrating an example of results of the sorting of the tangible components and calculation of ratios of the numbers of the tangible components each based on a second image; 
         FIG. 10  is a diagram illustrating a correction result obtained by performing correction processing in the embodiment; 
         FIG. 11  is a flow chart illustrating a flow of the sorting of the tangible components and the calculation of the numbers of the tangible components in a first modification; 
         FIG. 12  is a diagram illustrating an example of the results of the sorting of the tangible components and the ratios of the numbers of the tangible components each based on the second image; 
         FIG. 13  is a diagram illustrating an example of the correction result obtained by performing the correction processing in the first modification; 
         FIG. 14  is a flow chart illustrating a flow of the sorting of the tangible components and the calculation of the numbers of the tangible components in a second modification; 
         FIG. 15  is a diagram illustrating an example of the results of the sorting of the tangible components and the ratios of the numbers of the tangible components each based on the second image; 
         FIG. 16  is a diagram illustrating an example of the correction result obtained by performing the correction processing in a second modification; 
         FIG. 17  is a flow chart illustrating a flow of the sorting of the tangible components and the calculation of the numbers of the tangible components in a third modification; 
         FIG. 18  is a diagram illustrating an example of the results of the sorting of the tangible components and the calculation of the number of the tangible components each based on the first image in the third modification; 
         FIG. 19  is a diagram illustrating an example of the results of the sorting of the tangible components and the calculation of the ratios of the numbers of the tangible components each based on the second image in the third modification; and 
         FIG. 20  is a diagram illustrating the correction result obtained by performing the correction processing in the third modification. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     The analysis of the sediments in the urine includes determination processing of determining types of the sediments in the urine and calculation processing of calculating the number of the sediments. By image-capturing the urine specimen with a high magnification, it is possible to recognize in detail shapes of the sediments and therefore increase accuracy of the determination processing. Meanwhile, when the urine specimen is image-captured with a high magnification, an image-capturing range is narrowed, thereby increasing the number of the sediments passing through a range outside the image-capturing range and degrading a capture rate in a captured image. 
     When the image-capturing range is widened to reduce the number of the sediments passing through the range outside the image-capturing range in order to increase accuracy of the calculation processing, the urine specimen is consequently image-captured with a low magnification. When the urine specimen is image-captured with the low magnification, the detailed shapes and structures of the sediments can no longer be recognized to result in degraded accuracy of the determination processing. Such a problem is not limited to the image-capturing of the urine specimen, and may arise also when tangible components contained in liquid other than urine, such as blood, a bodily fluid, or artificial blood, are determined, and the number of the tangible components is counted. In Japanese Laid-Open Patent Publication No. H 06-288895, scattered light scattered by particles flowing in a flow cell is detected using a detector, and an image is captured in accordance with a detection signal. In Japanese Laid-Open Patent Publication No. H 11-94727, before sample measurement, an image effective factor is acquired using a known standard sample, the number of image processing particles is calculated from the number of all the particles passing through an image-capturing region of the flow cell, and the number of the image processing particles is multiplied by the particles image effective factor, whereby the number of the particles is calculated. However, in the particle detection using the scattered light, the particles cannot be sorted on a per component basis. As a result, there has been a demand for a further improvement in measurement accuracy. 
     A task of the disclosure is to increase accuracy of measurement in which tangible components contained in liquid are sorted and the number of each of the sorted tangible components is calculated. 
     Embodiments 
     A further description will be given below of an embodiment. A configuration of the embodiment shown below is exemplary, and a technique according to the disclosure is not limited to the configuration of the embodiment. For example, a measurement device according to the embodiment includes the following configuration. The measurement device according to the embodiment includes an acquisition unit and a calculation unit. The acquisition unit acquires a first image obtained by image-capturing liquid containing tangible components flowing through a flow path and a second image image-captured simultaneously with the first image and having an image-capturing magnification higher than that of the first image. The calculation unit sorts, by using clipped images obtained by clipping the tangible components included in the first image and the second image, the tangible components into different types, and that calculates, by using a total number of the tangible components clipped out of the first image and included in a specified category as well as a ratio of a number of each of the tangible components of the different types clipped out of the second image and included in the specified category relative to a total number of the tangible components in the specified category, the number of the tangible components included in the specified category. 
     The measurement device determines the types of the tangible components contained in the liquid and calculates the numbers of the tangible components of the different types. In the measurement device, the liquid may be liquid derived from a living body such as, e.g., urine, blood, or a bodily fluid or may also be liquid not derived from a living body such as artificial blood or a chemical. When the specimen is urine, as the tangible components, blood cells, epithelial cells, casts, bacteria, crystals, and the like can be listed. 
     Preferably, the flow path is formed such that the tangible components contained in the liquid do not stay in one place, but are uniformly distributed in the liquid to flow. The tangible components thinly spread in the liquid to inhibit degradation of accuracy of calculating the numbers of the tangible components due to the plurality of overlapping tangible components observed in the first image or the second image. For example, the flow path is formed in the flow cell. 
     The acquisition unit acquires the first image and the second image. The acquisition unit may also acquire the first image and the second image from an image capturing unit that has captured the first image and the second image. Alternatively, the acquisition unit may also acquire, from a storage unit, the first image and the second image each stored in advance in the storage unit. Still alternatively, the acquisition unit may also receive the first image and the second image from another device via a communication line or the like. 
     For example, the image capturing unit is a digital camera including an image capturing element such as a charge coupled device (CCD) image sensor or a complementary metal oxide semiconductor (CMOS) image sensor. 
     The first image is lower in magnification than the second image, and accordingly a wider range is captured in the first image. Consequently, the number of the tangible components captured by the captured first image is large, and therefore the first image is appropriate for counting of the number of the tangible components. Meanwhile, the second image captured with a magnification higher than that with which the first image is captured can show detailed shapes and structures of the tangible components. Accordingly, the second image is appropriate for sorting of the tangible components. The measurement device calculates the number of at least one type of the tangible components by using the number of the tangible components included in the first image and the numbers of the tangible components of the different types included in the second image to be able to increase the accuracy of calculating the numbers of the tangible components. 
     The measurement device may also have the following characteristic feature. The calculation unit mentioned above multiplies the total number of the tangible components clipped out of the first image described above and included in a specified category by a ratio of the number of each of the tangible components of the different types clipped out of the second image and included in the specified category relative to a total number of the tangible components in the specified category, thereby calculating the number of the tangible components included in the specified category. The specified category (type) mentioned herein may be, e.g., all the categories, the category (type) specified by a person in charge of the measurement, or the category (type) prone to erroneous sorting. By having such a characteristic feature, it is possible to increase the accuracy of calculating the number of the tangible components in the specified category (of the specified type), while reducing an arithmetic load placed on the measurement device. 
     The measurement device may also have the following characteristic feature. The calculation unit outputs a complete component image in which clipped images representing the tangible components of the different types are disposed based on a result of calculating the numbers of the tangible components of the different types. By having such a characteristic feature, the measurement device can facilitate visual recognition of the types of the tangible components and the number of the tangible components. 
     The measurement device may also have the following characteristic feature. The measurement device further includes a first image capturing unit that image-captures the first image and a second image capturing unit that image-captures the second image, and the first image capturing unit and the second image capturing unit have the same focal positions on optical axes thereof. By having such a characteristic feature, it is possible to increase the accuracy of calculating the number of the tangible components, since the image-capturing range of the second image is included in the image-capturing range of the first image in an in-focus state. The technique according to the embodiment described above can also be recognized from the aspect of a measurement method. 
     Referring to the drawings, a further description will be given below of the measurement device according to the embodiment.  FIG. 1  is a diagram illustrating a schematic configuration of the measurement device according to the embodiment. A measurement device  20  includes an image-capturing device  1 . The measurement device  20  uses the image-capturing device  1  to imager-capture, e.g., urine as a specimen and analyzes a captured image to measure, e.g., tangible components in the urine. However, the measurement device  20  is also applicable to measurement of tangible components in liquid specimen other than urine such as, e.g., blood or a bodily fluid. The urine is an example of a “liquid containing tangible components”. 
     The image-capturing device  1  includes an image capturing unit  10  that image-captures the specimen, a light source  12  for the image-capturing, and a flow cell unit  13 . The flow cell unit  13  includes a stage (the illustration thereof is omitted) on which a flow cell  13 A through which the specimen flows is fixedly disposed. The flow cell  13 A is detachable from the stage. 
     The image capturing unit  10  includes an objective lens  101 , a branching portion  102 , a first lens set  103 A, a second lens set  103 B, an aperture  104 , a first camera  105 A, and a second camera  105 B. Each of the first camera  105 A and the second camera  105 B uses an image capturing element such as, e.g., a CCD image sensor or a CMOS image sensor to perform the image-capturing. A combination of the objective lens  101 , the branching portion  102 , the first lens set  103 A, the aperture  104 , and the first camera  105 A is hereinafter referred to as a first image capturing unit  100 A. Meanwhile, a combination of the objective lens  101 , the branching portion  102 , the second lens set  103 B, and the second camera  105 B is referred to as a second image capturing unit  100 B. Each of the first lens set  103 A and the second lens set  103 B includes an ocular lens and may also have an imaging lens. The flow cell  13 A is disposed between the light source  12  and the objective lens  101 . The light source  12  and the objective lens  101  are shared by the first image capturing unit  100 A and the second image capturing unit  100 B. The objective lens  101  may be of either a finite-corrected optical system or an infinity-corrected optical system but, by using the objective lens  101  of the finite-corrected optical system, it is possible to compactify the image-capturing device  1 . The first image capturing unit  100 A is an example of a “first image capturing unit”. The second image capturing unit  100 B is an example of a “second image capturing unit”. 
     For example, the branching portion  102  is a beam splitter such as a half mirror. The branching portion  102  allows a portion of light that has passed through the flow cell  13 A and the objective lens  101  to pass therethrough and reflects a remaining portion of the light to branch the light in two directions. Light resulting from the branching and transmitted by the branching portion  102  is incident on an image-capturing surface of an image capturing element of the first camera  105 A through the first lens set  103 A. In other words, the light transmitted by the branching portion  102  is subjected to image-capturing in the first image capturing unit  100 A. Meanwhile, the light reflected by the branching portion  102  is incident on an image capturing surface of an image capturing element of the second camera  105 B through the second lens set  103 B. In other words, the light reflected by the branching portion  102  is subjected to image-capturing in the second image capturing unit  100 B. An optical path for the light between the branching portion  102  and the first camera  105 A is referred to as a first optical path, while an optical path for the light between the branching portion  102  and the second camera  105 B is referred to as a second optical path. As illustrated in  FIG. 1 , the branching portion  102  is disposed on an optical axis  11 B of the objective lens  101 . In  FIG. 1 , an optical axis of the first optical path is denoted by  111 A, while an optical axis of the second optical path is denoted by  111 B. 
     The aperture  104  is disposed between the branching portion  102  and the first lens set  103 A. In other words, the aperture  104  is inserted in the first optical path. The aperture  104  is formed by opening a circular hole in a plate. The aperture  104  is disposed at a position to be perpendicular to the optical axis  111 A of the first optical path such that an optical axis  111 A of the first lens set  103 A passes through a center axis of the hole of the aperture  104 . The aperture  104  is a diaphragm which blocks, in the first optical path, light from a peripheral portion to reduce an optical aperture of light traveling toward the first camera  105 A. The aperture  104  increases a depth of field of the first camera  105 A. 
     In the measurement device  20 , a controller  14  is provided to serve as a control unit. The controller  14  includes a central processing unit (CPU)  14 A, a read only memory (ROM)  14 B, a random access memory (RAM)  14 C, an electrically erasable programmable read only memory (EEPROM)  14 D, and an interface circuit  14 E. The CPU  14 A, the ROM  14 B, the RAM  14 C, the EEPROM  14 D, and the interface circuit  14 E are connected to each other by a bus line  14 F. 
     The CPU  14 A controls the entire measurement device  20  based on a program stored in the ROM  14 B and read into the RAM  14 C. In the ROM  14 B, programs and data for operating the CPU  14 A are stored. The RAM  14 C provides a work area for the CPU  14 A and temporarily stores various data and programs. The EEPROM  14 D stores various setting data and the like. The interface circuit  14 E controls communication between the CPU  14 A and the various circuits. 
     To the interface circuit  14 E, control lines for the first image capturing unit  100 A, the second image capturing unit  100 B, the light source  12 , a first pump  15 A, and a second pump  15 B are connected. The first image capturing unit  100 A, the second image capturing unit  100 B, the light source  12 , the first pump  15 A, and the second pump  15 B are controlled by a control signal from the CPU  14 A. The first pump  15 A is a pump that supplies a sheath fluid to the flow cell  13 A via a first supply pipe  132 A. The second pump  15 B is a pump that supplies the specimen to the flow cell  13 A via a second supply pipe  133 A. The sheath fluid is liquid that controls a flow of the specimen in the flow cell  13 A. As an example of the sheath fluid when the specimen is, e.g., urine, normal saline can be used. However, a solution other than the normal saline may also be used as the sheath fluid. 
       FIG. 2  is a diagram illustrating a schematic configuration of the flow cell  13 A. The flow cell  13 A is formed by joining together a first plate  130  and a second plate  131  (by, e.g., thermocompression).  FIG. 2  is a diagram obtained by viewing the flow cell  13 A from the first plate  130  side. It is assumed that a width direction of the flow cell  13 A illustrated in  FIG. 2  is an X-axis direction in a rectangular coordinate system, a longitudinal direction of the flow cell  13 A is a Y-axis direction in the rectangular coordinate system, and a thickness direction of the flow cell  13 A is a Z-axis direction in the rectangular coordinate system. The specimen to be image-captured flows in the Y-axis direction in the flow cell  13 A. The optical axis  11 B of the objective lens  101  is disposed to extend in the Z-axis direction. 
     As a material of the flow cell  13 A, a material having a visible light transmissivity of, e.g., 90% or more, such as acrylic resin (PMMA), cycloolefin polymer (COP), polydimethylsiloxane (PDMS), polypropylene (PP), or quartz glass, can be used. 
     In the first plate  130 , a first supply hole  132  for supplying the sheath fluid, a second supply hole  133  for supplying the specimen, and an exhaust hole  134  for exhausting the sheath fluid and the specimen are provided. Each of the first supply hole  132 , the second supply hole  133 , and the exhaust hole  134  extends through the first plate  130  in a thickness direction thereof. The first supply hole  132  is provided closer to one end of the first plate  130  in a longitudinal direction thereof. The second supply hole  133  is provided closer to the other end of the first plate  130  in the longitudinal direction thereof. The exhaust hole  134  is provided between the first supply hole  132  and the second supply hole  133  in the first plate  130  in the longitudinal direction thereof. 
     The first supply hole  132 , the second supply hole  133 , and the exhaust hole  134  communicate with each other via paths  135 A,  135 B,  136 , and  138 . Each of the paths  135 A,  135 B,  136 , and  138  is formed of a junction-plane surface of the first plate  130  which is recessed to have a rectangular cross section. Each of the paths  135 A,  135 B,  136 , and  138  is also formed to have the cross section which is longer in a width direction thereof (the X-axis direction in  FIG. 2 ) than in a depth direction thereof (the Z-axis direction in  FIG. 2 ). When the first plate  130  and the second plate  131  are joined together, the second plate  131  serves as a wall material in which the paths  135 A,  135 B,  136 , and  138  are to be formed. 
     To the first supply hole  132 , the first path  135 A and the second path  135 B are connected. The first path  135 A and the second path  135 B extend in opposite directions along an outer edge of the first plate  130  toward the second supply hole  133  to be joined together in a confluent portion  137 . To the second supply hole  133 , the third path  136  is connected. The third path  136  is joined with the first path  135 A and the second path  135 B in the confluent portion  137 . The confluent portion  137  is connected to the exhaust hole  134  via the fourth path  138 . In the fourth path  138 , a tapered portion  138 A is formed in a tapered shape in which a depth of the fourth path  138  (a length of the first plate  130  in the plate thickness direction (the Z-axis direction)) gradually decreases with distance from the confluent portion  137  toward the exhaust hole  134 . The tapered portion  138 A is provided with an inclination of, e.g., 2° to 8°. 
     To the first supply hole  132 , the first supply pipe  132 A illustrated in  FIG. 1  is connected. To the second supply hole  133 , the second supply pipe  133 A illustrated in  FIG. 1  is connected. To the exhaust hole  134 , an exhaust pipe (the illustration thereof is omitted) is connected. The sheath fluid supplied from the first supply pipe  132 A to the first supply hole  132  flows through the first path  135 A and the second path  135 B. The specimen supplied from the second supply pipe  133 A to the second supply hole  133  flows through the third path  136 . The sheath fluid and the specimen join together in the confluent portion  137  to flow through the fourth path  138  to be exhausted from the exhaust hole  134  into the exhaust pipe. 
       FIG. 3  is a diagram illustrating a schematic configuration of the vicinity of each of the confluent portion  137  and the tapered portion  138 A. In the confluent portion  137 , the third path  136  is unevenly disposed to be closer to the second plate  131 . In the confluent portion  137 , the specimen flows along the second plate  131 . 
       FIG. 4  is a diagram illustrating distributions of the sheath fluid and the specimen each flowing through the fourth path  138 . After the sheath fluid and the specimen are separately supplied from an upper side in  FIG. 4 , the sheath fluid and the specimen join together in the confluent portion  137 . Immediately after the joining together of the sheath fluid and the specimen in the confluent portion  137 , the specimen in the sheath fluid is localized to a relatively narrow range closer to a wall surface of the second plate  131  (position along a line A-A). Then, when the specimen flows through the tapered portion  138 A, the specimen is pressed by the sheath fluid to spread into a flat shape along and near the wall surface of the second plate  131  (position along a line B-B). When the specimen further flows, the specimen moves away from the wall surface of the second plate  131  under a tubular-pinch effect to be raised to a center direction of the fourth path  138  (position along a line C-C). 
     A distribution of the tangible components is affected by a distribution of the specimen in the sheath fluid. The measurement device  20  performs image-capturing using the first image capturing unit  100 A and the second image capturing unit  100 B at a position at which a larger number of the tangible components can be image-captured to be able to increase the accuracy of measuring the tangible components. In the flow cell  13 A, a flow of the specimen varies depending on a position thereof in the Y-axis direction. At the position along the line C-C in  FIG. 4 , a width of the specimen in the Z-axis direction is larger than at the position along the line B-B. At the position along the line C-C in  FIG. 4 , the tangible components in the specimen are distributed to spread in the Z-axis direction, and therefore the position along the line C-C is inappropriate for the image-capturing of the tangible components. 
     Meanwhile, at the position along the line B-B in  FIG. 4 , the sheath fluid flows from above so as to press the specimen against the second plate  131 , and the specimen is crushed under the pressure of the sheath fluid to thinly spread in the optical axis direction. Consequently, at the position along the line B-B in  FIG. 4 , the tangible components in the specimen are present without spreading in the Z-axis direction. Note that the sheath fluid and the specimen form respective laminar flows and are scarcely mixed with each other. Such a position along the line B-B is a position in the Y-axis direction appropriate for the image-capturing of the tangible components, and therefore the measurement device  20  image-captures the specimen at this position in the Y-axis direction. This position is referred to as an image-capturing position, and the optical axis  11 B of the objective lens  101  is aligned with the image-capturing position. In other words, the flow cell  13 A is formed such that the tangible components thinly spread in the specimen at the image-capturing position. At the image-capturing position, the tangible components are uniformly distributed in the specimen. 
     Note that the description has been given by way of example of a mode in which the specimen after passing through the tapered portion  138 A of the flow cell  13 A is in contact with a wall surface of the flow cell  13 A. However, a structure of the flow cell and the flow of the specimen are not limited to those in this mode. In the measurement device  20 , e.g., a flow cell having a structure in which, after the passage of the specimen through the tapered portion  138 A of the flow cell  13 A, the sheath fluid surrounds the specimen, and the specimen is thinly stretched out in a center portion of the sheath fluid may also be used. 
     Returning back to  FIG. 1 , in the first image capturing unit  100 A, the aperture  104  is inserted in the first optical path to reduce an amount of the light travelling toward the first camera  105 A (reduce a numerical aperture). Meanwhile, in the second optical path, a diaphragm equivalent to the aperture  104  is not provided. In the first camera  105 A, the numerical aperture of the aperture  104 , respective magnifications of individual lenses included in the first lens set  103 A, a distance between the objective lens  101  and the first lens set  103 A, and the like are adjusted to set an image-capturing magnification at the image-capturing position to a first magnification. In the second camera  105 B, respective magnifications of individual lenses included in the second lens set  103 B, a distance between the objective lens  101  and the second lens set  103 B, and the like are adjusted to set the image-capturing magnification at the image-capturing position to a second magnification higher than the first magnification. For example, the first magnification and the second magnification may also be 10 times and 40 times, respectively. Focal positions of the first camera  105 A and the second camera  105 B on the respective optical axes thereof are adjusted to coincide with the same position in the specimen in the image-capturing at the image-capturing position. In other words, the first camera  105 A and the second camera  105 B have the same focal positions. 
     The CPU  14 A causes the first camera  105 A and the second camera  105 B to simultaneously capture still images of the tangible components in the specimen flowing through the flow cell  13 A. The still images are enlarged images of the specimen. An ON period of the light source  12  and respective image-capturing periods (exposure periods) of the first camera  105 A and the second camera  105 B are synchronized by the CPU  14 A. From the light source  12 , parallel beams are incident on the flow cell  13 A. In image-capturing the still images, the CPU  14 A turns ON the light source  12  once or a plurality of times. The ON period of the light source  12  depends on a flow rate of the specimen and is set to, e.g., 0.1 to 10 psec to allow motion blur to fall within an allowable range. It may also be possible to turn ON the light source  12  a plurality of times for one exposure shot and thus increase the number of the tangible components included in one image. By image-capturing a larger number of the tangible components, the measurement device  20  can further increase the accuracy of measuring the tangible components. In this case, timing of blinking the light source  12  may be determined appropriately in consideration of a relationship between the flow rate of the specimen and the ON period of the light source  12 . In measurement for one specimen, e.g., 100 to 1000 images are captured. As the light source  12 , e.g., a xenon lamp or a white LED can be used, but the light source  12  is not limited thereto, and another light source can also be used. 
     When an image of the light from the light source  12  transmitted by the flow cell  13 A is image-captured by the first image capturing unit  100 A and the second image capturing unit  1008 , two images having different image-capturing magnifications are acquired.  FIG. 5  is a diagram illustrating an example of the respective images captured by the first image capturing unit  100 A and the second image capturing unit  100 B. In  FIG. 5 , a first image P 1  is an example of an image captured by the first image capturing unit  100 A with the first magnification at the image-capturing position. Meanwhile, a second image P 2  is an example of an image captured by the second image capturing unit  100 B with the second magnification at the image-capturing position. As illustrated in  FIG. 5 , the second image P 2  corresponds to an image obtained by enlarging a local region of the first image P 1 . In addition, the first camera  105 A and the second camera  105 B have the same focal positions on the respective optical axes thereof. The first image P 1  and the second image P 2  have respective center positions in an XY plane which are coincident with each other, and an image-capturing range of the second image P 2  may appropriately be included in an image-capturing range of the first image P 1 . In other words, an image-captured region image-captured by the second image capturing unit  100 B is included in an image-captured region image-captured by the first image capturing unit  100 A. The respective image-captured regions image-captured by the two image capturing units are associated with each other. For example, the CPU  14 A acquires, from the first image capturing unit  100 A and the second image capturing unit  100 B, the first image P 1  and the second image P 2  simultaneously captured thereby and stores the acquired first and second images P 1  and P 2  in association with each other in the RAM  14 C. The first image P 1  is an example of a “first image”. The second image P 2  is an example of a “second image”. 
     The first image P 1 , which is wider in image-capturing range than the second image P 2 , is appropriate for determination of the number of the tangible components. Meanwhile, the second image P 2 , which is higher in image-capturing magnification than the first image P 1 , is appropriate for observation of shapes of cell nuclei or the like or sorting of the tangible components. For example, the CPU  14 A can calculate the number of the tangible components in the specimen based on the first image P 1 , sort the tangible components in the specimen into different types based on the second image P 2 , and calculate the number of each of the tangible components sorted into the different types. 
     The CPU  14 A recognizes positions and sizes of the tangible components and the number of the tangible components in the images captured by the first image capturing unit  100 A and the second image capturing unit  100 B, determines sizes of images to be clipped based on the recognized sizes of the tangible components, and generates clipped images. The clipped images are images obtained by comparing the captured images to a background image, encircling portions with differences, and clipping images in the encircled portions. 
     Prior to generation of the clipped images, the CPU  14 A uses data on the stored images to produce, for each of the images, an average of respective pixel values of individual pixels as the background image. The pixel values may be either luminances or RGB values of the individual pixels. The clipped images are generated through execution of the program (clipping processing) stored in the ROM  14 B by the CPU  14 A. The clipped images are stored together with positions at which the images are clipped and the sizes of the clipped images in the RAM  14 C. For example, the CPU  14 A determines that portions of each of the first image P 1  and the second image P 2  that have differences with the background image include the tangible components and generates the clipped images for all the tangible components included in the image. The CPU  14 A sorts the clipped images clipped out of the first image P 1  according to each of the tangible components and counts the number of each of the clipped images sorted into different category items. The CPU  14 A may also calculate only the total number of the tangible components in the specimen without sorting the clipped images clipped out of the first image P 1  according to each of the tangible components. The CPU  14 A also observes shapes of the tangible components in each of the clipped images clipped out of the second image P 2 , sorts the tangible components into the different types, and calculates the numbers of the tangible components sorted into the different types. 
       FIG. 6  is a flow chart illustrating a flow of the sorting of the tangible components in the embodiment. The flow chart illustrated in  FIG. 6  is executed by the CPU  14 A. 
     In S 101 , the CPU  14 A acquires the first image P 1  captured by the first image capturing unit  100 A. The CPU  14 A also acquires the second image P 2  captured by the second image capturing unit  100 B. The CPU  14 A stores the first image P 1  and the second image P 2  in the RAM  14 C. The CPU  14 A that performs the processing in S 101  is an example of the “acquisition unit”. The processing in S 101  is an example of an “acquisition step”. 
     In S 102 , the CPU  14 A clips the tangible components out of the first image P 1  to generate first clipped images. The CPU  14 A stores the generated first clipped images in the RAM  14 C. 
     In S 103 , the CPU  14 A acquires positional information and feature values of the first clipped images stored in the RAM  14 C in S 102 . The CPU  14 A stores the first clipped images and the positional information and the feature values of the first clipped images in association with each other in the RAM  14 C. Examples of the feature values include colors, shapes, and sizes. To acquire the feature values, the program stored in advance in the ROM  14 B is used. 
     In S 104 , the CPU  14 A clips the tangible components out of the second image P 2  to generate second clipped images. The CPU  14 A stores the generated second clipped images in the RAM  14 C. 
     In S 105 , the CPU  14 A acquires feature values of the second clipped images stored in the RAM  14 C in S 104 . The CPU  14 A stores the second clipped images and the feature values of the second clipped images in association with each other in the RAM  14 C. 
     In S 106 , the CPU  14 A performs the sorting of the tangible components and the calculation of the numbers of the tangible components based on the feature values acquired in S 103  and S 105 . For the sorting, the program stored in advance in the ROM  14 B is used.  FIG. 7  is a flow chart illustrating a flow of the sorting of the tangible components and the calculation of the numbers of the tangible components in the embodiment. In other words,  FIG. 7  illustrates a detailed flow of the processing in S 106  in  FIG. 6 . 
     In S 1061 , the CPU  14 A sorts the tangible components into the different types based on the clipped image clipped out of the first image P 1 , and calculates the number of each of the tangible components sorted into the different types. Specifically, the CPU  14 A performs the sorting of the tangible components and the calculation of the numbers of the tangible components based on the feature values acquired in S 103  in  FIG. 6 .  FIG. 8  is a diagram illustrating an example of results of the sorting of the tangible components and the calculation of the number of the tangible components each based on the first image P 1 . In  FIG. 8 , the tangible components are sorted into large categories and into smaller category items into which the large categories are more finely sorted. For example, the tangible components are sorted into eight items “1” to “8” as the large categories. For example, in  FIG. 8 , epithelia in the large category “3” is more finely divided into the category items “FLAT EPITHELIUM” and “OTHER EPITHELIA”. Casts in the large category “4” is more finely divided and sorted into the category items “HYALINE CAST” and “OTHER CASTS”. All the large categories need not necessarily have smaller category items. As illustrated in  FIG. 8 , the CPU  14 A calculates the number of each of the tangible components of the different types and the total number of the tangible components. It may also be possible that, in S 1061 , the CPU  14 A calculates only the total number of the tangible components without calculating the number of each of the tangible components of the different types. 
     In S 1062 , the CPU  14 A, on the basis of the second image P 2 , sorts the tangible components into the different types and calculates the ratio of the number of each of the tangible components sorted into the different types to the total number of the tangible components. In other words, the CPU  14 A performs the sorting of the tangible components and the calculation of the ratios of the numbers of the tangible components based on the feature values acquired in S 105  in  FIG. 6 .  FIG. 9  is a diagram illustrating an example of results of the sorting of the tangible components and calculation of ratios of the numbers of the tangible components each based on the second image P 2 . In  FIG. 9 , in the same manner as in  FIG. 8 , the tangible components are sorted into types such as a red blood cell and a white blood cell, and the number of each of the tangible components sorted into different categories are calculated. Also, in  FIG. 9 , in the same manner as in  FIG. 8 , the tangible components are sorted into the large categories “1” to “8”. As illustrated in  FIG. 9 , the CPU  14 A calculates the number of each of the tangible components of the different types. As illustrated in  FIG. 9 , the CPU  14 A also calculates the respective ratios of the numbers of the tangible components of the different types to the total number of the tangible components. The CPU  14 A sorts the tangible component into the different types based on the second image P 2  captured with a magnification higher than that with which the first image P 1  is captured to be able to sort the tangible components with higher accuracy. Note that, in  FIGS. 8 and 9 , the tangible components are sorted into different types “RED BLOOD CELL”, “WHITE BLOOD CELL”, “FLAT EPITHELIUM”, “OTHER EPITHELIA”, “HYALINE CAST”, “OTHER CASTS”, “BACTERIA”, “CRYSTAL”, “OTHERS”, AND “DUST/CELL FRAGMENT”, but the sorting of the tangible components is not limited thereto. 
     In S 1063 , the CPU  14 A performs correction processing. The CPU  14 A corrects the numbers of the tangible components of the different types based on the total number of the tangible components acquired from the images clipped out of the first image P 1 , which is calculated in S 1061 , and the respective ratios of the numbers of the tangible components of the different types acquired from the images clipped out of the second image P 2 , which are calculated in S 1062 .  FIG. 10  is a diagram illustrating a correction result obtained by performing the correction processing in the embodiment. For example, since the ratio of “RED BLOOD CELLS” calculated in S 1062  is “15.2%” and the “TOTAL NUMBER” calculated in S 1061  is “82”, the CPU  14 A uses the total number of the individual tangible components based on the first image P 1  and respective abundance ratios of the individual tangible components acquired from the second image P 2  to calculate the numbers of the tangible components. By way of example, “82” as the total number of the tangible components obtained using the first image P 1  is multiplied by “15.2%” as the ratio of the red blood cells sorted using the second image P 2  to calculate that the number of the red blood cells after the correction is “12”. The total number of the tangible components after the correction is equal to the total number of the tangible components obtained using the first image P 1 , and the ratio of the number of each of the tangible components in the different categories after the correction are equal to the ratios acquired from the second image P 2 . The CPU  14 A performs such correction processing on the individual tangible components to be able to obtain the correction result illustrated in  FIG. 10 . 
     Returning back to  FIG. 6 , in S 107  the CPU  14 A outputs the correction result obtained by performing the correction processing in S 106 . The CPU  14 A may also, e.g., output a list of the correction result illustrated in  FIG. 10  as a calculation result to a monitor or to a printer to cause the printer to print the list. The CPU  14 A may also output, as a calculation result, a complete component image which is produced for overall observation by randomly disposing, on a screen, the clipped images of the individual components on the basis of the number of each of the tangible components of the different types calculated in S 106 , an amount of the specimen used for the measurement, and magnifications and image sizes of the images displayed as the complete component image. The CPU  14 A that performs the processing in S 102  to S 107  is an example of the “calculation unit”. The processing in S 102  to S 107  is an example of a “calculation step”. 
     The CPU  14 A produces the complete component image in which, e.g., the first clipped images or the second clipped images the number of which is equal to the number calculated in S 106  are randomly disposed in no-overlapping relation. The CPU  14 A may also enlarge a portion of the complete component image and output an enlarged image which allows the shapes of the individual tangible components to be easily visually recognized. The complete component image is obtained by changing the numbers of the tangible components of the different types in the first image P 1  or the second image P 2  illustrated in  FIG. 5  based on a result of the calculation performed in S 106 . 
     In the embodiment, the CPU  14 A corrects the numbers of the tangible components of the different types based on the total number of the tangible components calculated based on the first image P 1  in S 1061  and on the respective ratios of the numbers of the tangible components of the different types calculated based on the second image P 2  in S 1062 . By combining a result of a high-magnification image appropriate for counting of the numbers of the tangible components and a result of a low-magnification image appropriate for sorting of the types of the tangible components, the measurement device  20  can increase the accuracy of calculating the numbers of the tangible components of the different types. In addition, when the first image and the second image, which are different in image-capturing magnification, are acquired, only one light source  12  and only one objective lens  101  are required. This allows the sorting of the tangible components in the specimen and the calculation of the numbers of the tangible components to be accomplished with lower cost. 
     In the embodiment, the CPU  14 A outputs the complete component image in which the first clipped images or the second clipped images the number of which corresponds to the number calculated in S 106  are randomly disposed in no-overlapping relation. In the embodiment, the CPU  14 A may also enlarge a portion of the complete component image and output an enlarged image which allows the respective shapes of the tangible components to be easily visually recognized. Thus, the embodiment allows easy visual recognition of the types of the tangible components in the urine and the number of the tangible components in the urine. 
     In the embodiment, the first camera  105 A and the second camera  105 B have the same focal positions on the respective optical axes thereof. Accordingly, the first image P 1  and the second image P 2  are different in magnification. The first image P 1  can be captured to cover a wide range, but is lower in the accuracy of sorting the tangible components than the second image P 2 . In the embodiment, the numbers of the individual tangible components are calculated using the number of the tangible components calculated using the first image P 1  and the abundance ratios of the tangible components in the different categories calculated using the second image P 2  to allow the accuracy of counting the numbers of the tangible components of the different types to be increased. 
     First Modification 
     In the embodiment, based on the total number of the tangible components calculated based on the first image P 1  and on the respective ratios of the numbers of the tangible components of the different types calculated based on the second image P 2 , the numbers of the tangible components of the different types are corrected for all the large categories. In a first modification, a description will be given of processing of correcting the numbers of the tangible components in the specified large category. In the first modification, the processing illustrating in  FIG. 7  of the embodiment is modified. Information representing the large category to be specified may be, e.g., stored in advance in the ROM  14 B or the large category to be specified may be selected by an operation by a user. Components common to the embodiment are denoted by the same reference numerals, and a description thereof is omitted. Referring to the drawings, a description will be given below of the first modification. 
       FIG. 11  is a flow chart illustrating a flow of the sorting of the tangible components and the calculation of the numbers of the tangible components in the first modification. The epithelia as the large category “3” are specified herein. In S 1061   a , the CPU  14 A calculates, based on the first image P 1 , the total number of the tangible components sorted into the epithelia as the specified large category “3”. It is assumed herein that results of the sorting of the tangible components and the calculation of the number of the tangible components each based on the first image P 1  are in a state illustrated in  FIG. 8  and the specified large category is the epithelia “3”. The CPU  14 A adds up “12” as the number of the tangible components in “FLAT EPITHELIUM” sorted into the epithelia as the large category “3” and “1” as the number of the tangible components in “OTHER EPITHELIA” to calculate the total number “13”. The CPU  14 A that performs the processing in S 1061   a  is an example of a “first calculation unit”. 
     In S 1062   a , the CPU  14 A, on the basis of the second image P 2 , calculates the ratio of the number of each of the individual tangible components sorted into the epithelia as the specified large category “3”.  FIG. 12  is a diagram illustrating an example of the results of the sorting of the tangible components and the calculation of the ratios of the numbers of the tangible components each based on the second image P 2 . The CPU  14 A adds up “8” as the number of the tangible components in “FLAT EPITHELIUM” sorted into the epithelia as the large category “3” and “2” as the number of the tangible components in “OTHER EPITHELIA” to calculate that the total number of the tangible components sorted into the large category “3” is “10”. The CPU  14 A calculates, based on the total number of the tangible components sorted into the large category “3” which is calculated based on the second image P 2  and on the number of each of the tangible components in “FLAT EPITHELIUM” and “OTHER EPITHELIA”, “80.0%” as a ratio of “FLAT EPITHELIUM” and “20.0%” as a ratio of “OTHER EPITHELIA” in the large category “3”. The CPU  14 A that performs the processing in S 1062   a  is an example of a “second calculation unit”. 
     In S 1063   a , the CPU  14 A corrects the number of each of the tangible components in “FLAT EPITHELIUM” and “OTHER EPITHELIA” based on the total number of the tangible components sorted into the epithelia as the large category “3”, which is calculated based on the first image P 1  in S 1061   a , and on the respective ratios of “FLAT EPITHELIUM” and “OTHER EPITHELIA” as category items, which are calculated based on the second image P 2  in S 1062   a . The CPU  14 A multiplies “13” as the total number of the tangible components sorted into the large category “3”, which is calculated based on the first image P 1 , by “80%” as the ratio of “FLAT EPITHELIUM”, which is calculated based on the second image P 2 , to calculate that a corrected value of the number of the tangible components in “FLAT EPITHELIUM” is “10”. The CPU  14 A also multiplies “13” as the total number of the tangible components sorted into the large category “3”, which is calculated based on the first image P 1 , by “20%” as the ratio of “OTHER EPITHELIA”, which is calculated based on the second image P 2 , to calculate that “3” is a corrected value of the number of the tangible components in “OTHER EPITHELIA”. The total number of the tangible components after the correction is equal to the total number of the tangible components obtained using the first image P 1 . It may also be possible to subtract, from the total number of the tangible components included in the specified large category, the number of the tangible components included in another category item after the correction and thus calculate the number of the tangible components in the category item after the correction. In the example described above, it may also be possible to subtract, from the total number 13 of the tangible components included in the epithelia, 10 as the number of the tangible components in “FLAT EPITHELIUM” after the correction to calculate that the number of the tangible components in “OTHER EPITHELIA” after the correction is “3”, and vice versa. The CPU  14 A performs such correction processing on each of the tangible components sorted into the specified large category to be able to obtain a correction result illustrated in  FIG. 13 . 
     According to the first modification, it is possible to accurately calculate the number of the tangible components in the specified large category and also reduce the processing load on the CPU  14 A compared to that in the embodiment in which the correction processing is performed for all the large categories. Note that, in the first modification, a case where all the categories are specified corresponds to the embodiment described above. 
     Second Modification 
     In a second modification, in the sorting of the tangible components based on the first image P 1 , the large category prone to erroneous sorting is specified, and correction is performed for the specified category. In the second modification, the processing illustrated in  FIG. 7  of the embodiment is modified. Information specifying the large category prone to erroneous sorting may be, e.g., stored in advance in the ROM  14 B or, alternatively, the large category to be specified may be selected by an operation by the user. Components common to the embodiment are denoted by the same reference numerals, and a description thereof is omitted. Referring to the drawings, a description will be given below of the second modification. 
       FIG. 14  is a flow chart illustrating a flow of the sorting of the tangible components and the calculation of the number of the tangible components in the second modification. In S 1061   b , the CPU  14 A calculates, from the result of the sorting of the tangible components based on the first image P 1 , the total number of the tangible components sorted into the large categories prone to erroneous sorting. It is assumed herein that the results of the sorting of the tangible components and the calculation of the number of the tangible components each based on the first image P 1  are in a state illustrated in  FIG. 8 , and the large categories specified as the large categories prone to erroneous sorting are “1”, “5”, “6”, and “8”. The CPU  14 A calculates that the total number of the tangible components sorted into “RED BLOOD CELL”, “BACTERIA”, “CRYSTAL”, and “DUST/CELL FRAGMENT” serving as the tangible components sorted into the large categories “1”, “5”, “6”, and “8” by using the first image P 1  is “64”. The CPU  14 A that performs the processing in S 1061   b  is an example of the “first calculation unit”. 
     In S 1062   b , the CPU  14 A calculates, from the result of the sorting of the tangible components based on the second image P 2 , respective ratios of the numbers of the tangible components in the large categories prone to erroneous sorting.  FIG. 15  is a diagram illustrating an example of the results of the sorting of the tangible components and the ratios of the numbers of the tangible components each based on the second image P 2 . The CPU  14 A clips the tangible components out of the second image P 2  and calculates the total number of the category items (tangible components) sorted into the large categories “1”, “5”, “6”, and “8”. The CPU  14 A calculates herein that the total number of the tangible components in “RED BLOOD CELL”, “BACTERIA”, “CRYSTAL”, and “DUST/CELL FRAGMENT” is “49”. The CPU  14 A calculates the respective ratios of the numbers of the tangible components in “RED BLOOD CELL”, “BACTERIA”, “CRYSTAL”, and “DUST/CELL FRAGMENT” to the calculated total number. For example, the CPU  14 A divides “10” as the number of the tangible components in “RED BLOOD CELL” by “49” as the total number of the tangible components included in the specified categories to calculate that the ratio of the number of the tangible components in “RED BLOOD CELL” is “20.4%”. The CPU  14 A that performs the processing in S 1062   b  is an example of the “second calculation unit”. 
     In S 1063   b , the CPU  14 A corrects the number of each of the tangible components sorted into the large categories prone to erroneous sorting based on the total number calculated using the first image P 1  in S 1061   b  and on the respective ratios of the numbers of the tangible components calculated from the second image P 2  in S 1062   b .  FIG. 16  is a diagram illustrating an example of a correction result obtained by performing correction processing in the second modification. For example, the CPU  14 A multiplies “20.4%” as the ratio of the number of the tangible components in “RED BLOOD CELL” calculated from the second image P 2  by “64” as the total number of the tangible components sorted into “1”, “5”, “6”, and “8” as the large categories prone to erroneous sorting in the first image P 1  to calculate that the number of the red blood cells after the correction is “13”. The CPU  14 A performs such correction processing on the individual tangible components classified into the large categories prone to erroneous sorting to be able to obtain the correction result illustrated in  FIG. 16 . The total number of the tangible components after the correction is equal to the total number of the tangible components obtained using the first image P 1 . 
     According to the second modification, it is possible to accurately calculate the number of the tangible components in the large categories prone to erroneous sorting and also reduce the processing load on the CPU  14 A compared to that in the embodiment in which the correction processing is performed for all the large categories. 
     Third Modification 
     By being based on the second image P 2  that is captured with a high image-capturing magnification, it is possible to more particularly and accurately sort the tangible components than by being based on the first image P 1 . In a third modification, a description will be given of processing which allows sorting of the tangible components in more detail by using the second image P 2  than sorting of the tangible components by using the first image P 1  is used. In the third modification, the processing illustrated in  FIG. 7  of the embodiment is modified. Components common to the embodiment are denoted by the same reference numerals, and a description thereof is omitted. Referring to the drawings, a description will be given below of the third modification. 
       FIG. 17  is a flow chart illustrating a flow of the sorting of the tangible components and the calculation of the number of the tangible components in the third modification. In S 1061   c , the CPU  14 A performs the sorting of the tangible components and the calculation of the total number of the tangible components based on the first image P 1 .  FIG. 18  is a diagram illustrating an example of the results of the sorting of the tangible components and the calculation of the number of the tangible components each based on the first image P 1  in the third modification. It is assumed that, in S 1061   c , as illustrated in  FIG. 18 , the tangible components are sorted into eight types “RED BLOOD CELL”, “WHITE BLOOD CELL”, “EPITHELIUM”, “CAST”, “BACTERIA”, “CRYSTAL”, “OTHERS”, and “DUST/CELL FRAGMENT”. It is also assumed that, as the “TOTAL NUMBER” of the tangible components, “101” is obtained. The CPU  14 A that performs the processing in S 1061   c  is an example of the “first calculation unit”. 
     In S 1062   c , the CPU  14 A performs the sorting of the tangible components and the calculation of the respective ratios of the numbers of the tangible components based on the second image P 2 .  FIG. 19  is a diagram illustrating an example of the results of the sorting of the tangible components and the calculation of the ratios of the numbers of the tangible components each based on the second image P 2  in the third modification. In the third modification, by taking advantage of the high magnification of the second image P 2 , the tangible components are more particularly and finely sorted than are sorted based on the first image P 1  in S 1061   c . For example, the tangible components sorted into “RED BLOOD CELL” in the sorting in S 1061   c  are sorted into two types of category items “ISOMORPHIC RED BLOOD CELL” and “DYSMORPHIC RED BLOOD CELL” in the sorting in S 1062   c . The CPU  14 A also calculates a ratio of the number of each of the sorted tangible components. For example, since the “TOTAL NUMBER” of the tangible components detected based on the second image P 2  is “80” and the “NUMBER” of the tangible components in “ISOMORPHIC RED BLOOD CELL” is “8”, the CPU  14 A calculates that the “RATIO” of the number of the tangible components in “ISOMORPHIC RED BLOOD CELL” is “10.0%”. The CPU  14 A that performs the processing in S 1062   c  is an example of the “second calculation unit”. 
     In S 1063   c , the CPU  14 A calculates the number of each of the individual tangible components based on the total number of the tangible components calculated based on the first image P 1  in S 1061   c  and on the respective ratios of the numbers of the tangible components particularly sorted based on the second image P 2  in S 1062   c .  FIG. 20  is a diagram illustrating a correction result obtained by performing the correction processing in the third modification. For example, the CPU  14 A calculates that the number of the tangible components in “ISOMORPHIC RED BLOOD CELL” after the correction is “10” based on “10.0%” as the ratio of the number of the tangible components in “ISOMORPHIC RED BLOOD CELLS” calculated in S 1062   c  to “101” as the total number calculated in S 1061   c . The CPU  14 A performs such correction processing on the individual tangible components to be able to obtain the correction result illustrated in  FIG. 20 . 
     In the third modification, even the tangible components of the types hard to sort using the first image P 1  are sorted based on the second image P 2 , and the number of each of the tangible components of the different types sorted based on the second image P 2  are corrected based on the total number calculated based on the first image P 1 . According to the third modification, it is possible to accurately calculate the numbers of even the tangible components of the types hard to sort using the first image P 1 . Note that, in the third modification, all the categories are specified, and correction is performed in all the categories. 
     Other Modifications 
     In each of the embodiment and the modifications described above, the image-capturing range of the second image P 2  is a portion of the image-capturing range of the first image P 1 . However, the image-capturing range of the second image P 2  might not be included in the image-capturing range of the first image P 1 . For example, the image-capturing range of the first image P 1  may be disposed upstream or downstream of the image-capturing range of the second image P 2 . Even when the image-capturing range of the second image P 2  is not included in the image-capturing range of the first image P 1 , the number of the tangible components included in the specified category can be calculated by using the same method as that described above. 
     In each of the embodiment and the modifications described above, the image-capturing device  1  performs image-capturing in a bright field, but the image-capturing device  1  may also perform image-capturing in a dark field or with a phase difference, differential interference, polarization, fluorescence, or the like. For example, when image-capturing is performed in the dark field, it is appropriate to illuminate the flow cell  13 A with the light from the light source  12  and cause reflected light from the flow cell  13 A to be incident on the objective lens  101 . 
     In each of the embodiment and the modifications described above, the image-capturing device  1  includes the second image capturing unit  100 B that performs image-capturing with the second magnification higher than the first magnification. However, the image-capturing device  1  may also include two or more image capturing units that perform image-capturing with a magnification higher than the first magnification. In this case, the image-capturing ranges of the image capturing units that perform image-capturing with the magnifications higher than the first magnification are preferably included in the image-capturing range in which the first image capturing unit  100 A performs image-capturing. In other words, the image capturing units that perform image-capturing with the magnifications higher than the first magnification preferably image-captures an enlarged image of a local region of the image captured by the first image capturing unit  100 A. 
     The embodiment and the modifications each disclosed above can be combined with each other.