JPH0961339A - Flow type particle image analyzing method and device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the measurement accuracy by collating particles detected by a particle detecting system with a detected particle static image in a particle image analyzer forming the static image of the particles suspended in a flowing liquid to analyze the particles. SOLUTION: A sample is fed to a flow cell 100, the transit of particles is detected by a laser beam 10, a pulse lamp 1 is lighted by the detection, a static image of particles is photographed by a TV camera 8 for image processing. By making the particles detected by a detecting means 103 and the particle sizes of each particle image processed by a particle analyzing means 102 correspond to each other in the classified result collection section of the particle analyzing means 102, the particles in the sample are classified, counted, and analyzed.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a flow-type particle image analysis method and apparatus, and more particularly, to a static image of particles suspended in a flowing liquid sample for particle analysis to analyze cells in blood or urine. The present invention relates to a flow-type particle image analysis method and apparatus suitable for particle analysis.

[0002]

2. Description of the Related Art In conventional particle image analysis, classification and analysis of cells in blood and cells and particles in urine have been performed by preparing a sample on a slide glass and observing with a microscope. In the case of urine, since the concentration of particles in the urine is low, the sample is observed after being centrifugally concentrated by a centrifuge in advance.

As a method or apparatus for automating these observation and inspection operations, a sample such as blood is smeared on a slide glass and set on a microscope, and the microscope stage is automatically scanned to detect the presence of particles. At this position, the microscope stage is stopped and a still particle image is captured, and the feature extraction and pattern recognition techniques of image processing technology are used to classify and analyze the particles in the sample.

However, in the above method, it takes a long time to prepare a specimen, and furthermore, it is necessary to find particles while mechanically moving the microscope stage and to move the particles to an appropriate image capturing area. Therefore, there are disadvantages that analysis takes time and the mechanical mechanism becomes complicated.

In a particle image analysis method or particle image analysis apparatus that does not form a smear as described above, a flow site in which a sample sample is suspended in a liquid and is flown into a flow cell for optical analysis. The meter method is known.
This method using a flow cytometer observes the fluorescence intensity and scattered light intensity from each particle in the sample, and has a processing capacity of several thousand per second. However, it is difficult to observe features that reflect the morphological characteristics of particles, and particles cannot be classified by morphological characteristics conventionally performed under a microscope.

As an attempt to capture static particle images in a continuously flowing sample sample and classify and analyze the particles from each static particle image, Japanese Patent Publication No. 57-50099.
Techniques described in Japanese Patent Laid-Open No. 5 and Japanese Patent Laid-Open No. 63-94156 are known.

In the technique disclosed in Japanese Patent Publication No. 57-500995, a sample sample is flowed through a channel having a special shape into a wide image pickup area, a static particle image is taken by a flash lamp, and the image is taken. Particle analysis is performed using. In this method, a magnified image of sample particles is C-imaged using a microscope.
When projecting on a CD camera, the flash lamp, which is a pulse light source, periodically emits light in synchronization with the operation of the CCD camera. Since the emission time of the pulsed light source is short, it is possible to obtain a still image even when particles are flowing continuously.
Moreover, the CCD camera can capture 30 still images per second.

In the technique disclosed in Japanese Patent Laid-Open No. 63-94156, a particle detection system is provided upstream of the particle image capturing area in the sample flow, in addition to the stationary particle image capturing system. This is to know the passage of particles by a particle detection system in advance and turn on a flash lamp which is a pulse light source at an appropriate timing when the particles reach the particle image capturing area. In this method, the light emission of the pulsed light source is not performed periodically, it is possible to detect the passage of particles and to capture a still particle image at the same time only, so the still particle images are efficiently collected, Even in the case of a sample having a low concentration, a meaningless image without particles is not captured and processed.

Further, in Japanese Patent Application Laid-Open No. 6-142086, as in the case of Japanese Patent Application Laid-Open No. 63-94156, there is provided a means for detecting particles in a sample flow in addition to a stationary particle image system, and in addition, detection is made. The actual number of particles in the sample particles from the total number of particles image-processed in the generated particle image,
It provides a means to obtain the number of particles for each classified type.

Further, in Japanese Patent Laid-Open No. 7-83817,
Japanese Unexamined Patent Publication No. 6-142086 discloses a one-to-one correspondence method between detected particles and detected particle images, which is a problem.

[0011]

In a conventional particle image analyzer, generally, a still image of a sample particle flowing continuously is analyzed to count or classify the number of plural kinds of particles in a sample. In order to efficiently perform the above, a particle detection system for detecting passing particles is required in the stationary particle image capturing area or upstream thereof, as is done in the above-mentioned known example. That is, the pulse light source is turned on only when the sample particles pass, and a still image of the sample particles is captured. Since this method can process a measurement sample having a low particle concentration very efficiently, it is possible to increase the amount of measurement sample, shorten the analysis time, and improve the analysis accuracy.

However, in such a flow type particle image analysis apparatus, a particle detection system for detecting passing particles in a stationary particle image capturing area or an upstream thereof, and a stationary particle image by turning on a pulse light source only when the particles have passed. Although an image pickup system for picking up the image is included, the particle detection system and the image pickup system generally have different measurement principles. As a particle detection system, a method is generally used in which a laser beam is focused on a measurement sample flowing in a flow cell and irradiated, and scattered light from particles that cross the laser beam is detected. The scattered light generally becomes an optical signal having an intensity proportional to the effective scattering cross section of the particle, and this optical signal is converted into an electric signal by a photodetector.

The magnitude of this optical signal is influenced by the optical refractive index of particles, absorption, size, internal state of particles, scattered light detection conditions, and the like, and is necessarily morphological information of particles used in image processing. It does not completely match the particle diameter, perimeter, color information, and texture information.

If the particle detection system is set to have a particle detection condition above a predetermined particle detection level, there are particles that are too small to reach the particle detection level due to light scattering in a static particle image obtained by an actual image pickup system. Doing is something that often happens. As a result, the number of particles counted by the particle detection system and the number of particles that have been image-processed do not match, even if the counting of particles due to dead time, which is unavoidable in image capture, is taken into consideration, and particle analysis accuracy and reproducibility deteriorate Cause to cause.

Japanese Unexamined Patent Publication No. 7-83817 provides a method for correctly addressing these problems. The method shown therein has a one-to-one correspondence relationship between particles imaged in one image and particles detected by the particle detection system. Therefore, from the particle detection signal, the number of particles corresponding to the detection particles among the particles reflected in the image when the pulse lamp light source is turned on is counted, and the count value and the detection particles among the particles in the image are counted. And to distinguish this from particles that are not considered detection particles.

In the above-mentioned method, a flow type particle image analysis method and a flow type particle image are provided, each having a particle detection system and an image pickup system, and the principle of the particle detection system and the principle of particle image discrimination of the image pickup system are different. In the analyzer, the detected particles and the particles in the static particle image are made to correspond to each other, and even if particles other than the detection particles of the particle detection system exist in the static particle image of the image capturing system, the number of particles of each type in the sample The present invention provides a flow type particle image analysis method and a flow type particle image analysis device that can accurately know the particle existence ratio, particle density, and concentration information, and have good analysis accuracy.

However, in the above-mentioned method, since the particles corresponding to the detection particles existing in one image are extracted from the particle detection signal and counted, complicated time timing is required,
When the circuit configuration of this part becomes complicated, it is not possible to deal with the case where the timing relationship changes due to the flow velocity change such as pulsation of the sample liquid, when there are a plurality of measurement modes where the sample flow velocity is different, There is a problem that a circuit configuration of multiple systems is required.

The object of the present invention is to make the detected particles correspond to the particles in the still particle image, and even if particles other than the detected particles are present in the still particle image, the number of particles of each kind in the sample,
It is an object of the present invention to provide a flow type particle image analysis method and a flow type particle image analysis device, which are suitable for making it possible to correctly know the particle abundance ratio, particle density, and concentration information and have good analysis accuracy.

[0019]

According to the invention, in a sample having a size equal to or greater than a predetermined value, the sample is flowed through a flow cell and passes through a predetermined position of the flow cell. The particles are detected as detection particles by the particle detection system. Particles passing through the imaging area of the flow cell are imaged by the particle imaging system and a still image thereof is obtained. Particles corresponding to the detected particles in the still image are extracted, and particle analysis is performed on the extracted particles.

In this way, the particles in the still image are associated with the detected particles. Therefore, even if particles other than the detected particles are present in the still particle image, the number of particles of each type in the sample, the particles A flow-type particle image analysis method and a flow-type particle image analysis device that are suitable for making it possible to correctly know the abundance ratio, particle density, and concentration information can be provided.

The predetermined value may be specifically determined based on the transit time of the particle when the particle passes through the predetermined position.

Particle detection may preferably be performed by illuminating a predetermined location on the flow cell with light and detecting the scattered light signal scattered by the particle as it passes by the light. Also, the transit time can be determined based on the width of the scattered light signal at a predetermined level. When a pulse having a time width corresponding to the width of the scattered light signal at a predetermined level is generated, the pulse width represents the particle size plus the focusing width in the flow direction of the sample of the irradiated light. Therefore, the transit time can be determined by the duration of the pulse.

The extraction of the particles corresponding to the detected particles in the still image can be performed in particular on the basis of the maximum size of the particles in the flow direction of the sample.

The particle analysis is performed by a plurality of predetermined measurement modes.
The analysis results may be integrated.

The particle analysis extracts the image feature amount of the extracted particles, and the image feature extraction amount may include morphological information, color information, fluorescence information of the extracted particles, or a combination thereof.

Particle detection may be performed in a plurality of measurement modes in which the particle detection conditions can be changed.

The particle analysis is performed by a plurality of predetermined measurement modes.
Mode, and the predetermined value is a plurality of modes.
It may be changed according to the mode.

In the particle analysis, either the number of particles per sample volume or the ratio may be calculated, and the number of particles per total sample volume may be calculated based on the calculation.

In the particle analysis, either the number of particles in the sample to be measured, the particle concentration per unit volume in the sample to be measured, or the number of particles in terms of a microscopic field may be determined.

In particle analysis, the
Particle analysis may be performed by using particles other than the detection particles as a separate frame.
Particles other than the detection particles are particles smaller than the detection particles, and among them, those that are particles for regular identification processing,
The particles that are not the object of the normal identification processing, but the existence of the particle doctor provides important information are included. Therefore, if the separate frame particle analysis process is performed, the abundance ratio of the processed particles can be calculated, or from the sample volume corresponding to all the static particle images subjected to the analysis process, the particle concentration per unit volume for the analysis processed particles, the microscope It is possible to know the number of particles in terms of visual field.

In the separate frame particle analysis, the measurement accuracy may be determined based on all the processed particles of the separate frame identification particles, and the fact may be reported. In this case, the total number of treated particles is compared with a preset numerical value, and when the measurement accuracy cannot be guaranteed, the fact is reported and the error due to the separate frame identification processing can be reduced.

Regarding the separate frame particle analysis, the classification result may be output as it is. At this time, when the presence of even one specific particle is more important information, the analysis result can be obtained for the exceptional particle.

If there is a normal identification processing particle in the particles analyzed in the separate frame, it may be incorporated into the result of the normal identification processing after calculating the particle concentration per unit volume. By doing so, the accuracy of particle analysis can be improved.
Also in this case, it is possible to judge the decrease of the analysis accuracy in the separate-frame particle analysis and incorporate it into the regular identification processing result. According to this, it is possible to prevent the measurement accuracy from deteriorating due to the incorporation of the results of the particle analysis processing in another frame.

These judgment criteria may be set in advance before the particle analysis, and the operator may be informed if the result of the separate frame particle analysis processing does not meet the judgment criteria. In this way, the analysis result can be judged with confidence.

It is not desirable to discard the information because the static particle image may contain particles important for sample analysis. In this case, by performing separate frame particle analysis, those particles can be reliably analyzed, and the overall analysis accuracy is not deteriorated.

The normal particle analysis processing and the separate frame particle analysis processing may be performed for each analysis mode even when there are analysis modes in which the range of particles to be analyzed is different.
For example, for a certain type of particle, if the first analysis mode is used to analyze particles in another frame and the second mode is used to analyze normal analysis target particles, individual analysis modes will be obtained after the analysis is completed.
It is possible to improve the analysis accuracy by integrating the analysis results of the above-mentioned ones as a particle analysis result of the entire analysis sample.

When there are a plurality of different measurement modes, such as when the measurement conditions are different or the range of particles to be analyzed is different, different particle detection conditions, that is, the particle detection level and the pulse width are different. The value of the predetermined width may be changed, and further, the value of the predetermined particle size may be changed in the particle analysis corresponding to different particle conditions. By doing so, the variety of measurement conditions is increased, and the accuracy of particle analysis can be improved.

A process may be defined when the number of still images is small and there is not enough sample volume to be processed to perform the separate-frame particle analysis.

Furthermore, when the number of still images is small and there is not enough sample volume to be processed for performing the separate-frame particle analysis, the evaluation procedure may be input and set in advance.

If the number of still images is small and there is not enough sample volume to be processed for performing the separate frame particle analysis, the separate frame particle analysis may be omitted or the separate frame particle analysis may be performed. May output that there is a problem.

[0041]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Prior to the detailed description with reference to the drawings, the concept of the embodiment will be described first.

Particles that have passed through the particle detection area in the flow cell are detected, and after a certain time, when the detected particles arrive at a predetermined position in the still image capturing area, the flash lamp is turned on to capture a still image of the particle. .

In general, it is often the case that small particles other than the particles detected by the particle detection system are also picked up in one picked-up still particle image. The higher the particle detection signal level, the greater this tendency. Therefore, it is necessary to distinguish which of the captured particle images is the detection target particle.

Here, as a detection principle of the particle detection system, for particles exceeding the signal level of the particle detection signal,
A signal whose pulse width exceeds a predetermined value is regarded as a particle detection signal. This pulse width corresponds to the time taken for the measurement particles to pass through the particle detection system, and is proportional to the size of the passing particles.

Since the size of the particle in the sample flow direction of the captured individual particle image and the pulse width due to passage of the particle correspond to each other, whether the particle is an image analysis target or not is distinguished based on the particle size determined by the pulse width. be able to.
Usually, the particle size in the flow direction is often used as one of the characteristic parameters necessary for classification and identification of particle images, so that it can be easily determined whether the particles are detected particles.

As the particle image identification feature amount, morphology information or color information of the measurement particles, fluorescence intensity information, or a feature amount obtained by combining a plurality of these items of information can be used. It is necessary to change the particle detection conditions of. Specifically, from the particle image, morphological information such as particle size, area, diameter, perimeter, and projection image, particle concentration, color information, particle internal structure, and fluorescence intensity are used.

Information such as the existence of nuclei, cytoplasm, intracellular granules, etc. as in biological cells can also be used. That is,
It is checked which particles are present in the image and which are the detected particles detected by the particle detection system, and the classification discrimination processing is executed. This is referred to as regular identification processing.

The remaining particles for which the detected particles and the particles in the image cannot be associated with each other are subjected to a different discrimination process from the corresponding particles. This process is referred to as a separate frame identification process.

Further, the count value of all detected particles which have passed the particle detection system and have a detection level or more and have a predetermined pulse width or more is measured regardless of still image capturing by particle detection.

In this case, it is necessary to prevent erroneous counting of particle detection signals due to flash lamp light.
To prevent this, the flashlamp light is prevented from reaching the particle detector or the flashlamp signal is not counted electrically.

It is also possible to prevent the erroneous counting by detecting the flash lamp light and subtracting the number of times of lamp light emission at the end of the measurement.

When processing a dense particle sample,
Due to the dead time associated with image reading, particle counts may be missed in the particle detection system.Therefore, the total number of particles in one image particle count value during a certain measurement time does not always pass through the particle detection system during the certain measurement time. It does not always match the total detected particle count value.

Further, since the particles to be subjected to the separate frame discrimination processing are particles below the detection level of the particle detection system, they are not included in the total particle detection count value.

When the detected particles and the particles in the still particle image are associated with each other, pattern recognition and identification processing is performed on the associated particle images to determine the type of particles. This operation is performed on all the images to determine the particle abundance ratio of each type in the sample. In order to determine this particle abundance ratio, the processing is performed only on the particles detected by the particle detection system, that is, on the corresponding particles. Particles that are present in the captured still particle image and that are lower than the particle detection level cannot be processed because they are not included in the total number of particles detected by the particle detection system.

When the particle existence ratio is determined, the total number of particles detected is separately measured by a particle detection counter, and the number of particles detected is multiplied by the particle existence ratio to calculate the number of particles of each type in the sample. . The particle concentration per unit volume is calculated from the number of particles of each type.

Next, a method of associating the number of particles in one image detected by the particle detection system with the particles existing in the still particle image will be described.

As a particle detecting means, a case will be described in which a laser beam is applied to a sample flow to detect light scattering from particles in the sample.

When the particles in the sample cross the wide and narrowly focused laser beam, the light is scattered and received by the photodetector. The size of the particle detection pulse signal converted into the electric signal includes the size information of the particle. In particular, the time it takes to pass the particle detection system corresponds to the particle detection pulse signal. This particle detection pulse signal actually corresponds to the particle size plus the spot size at the particle detection position of the laser beam. Therefore, when taking correspondence as a detection particle on a particle image, it is necessary to consider in consideration of the spot size of the laser beam.

When targeting the size of the detected particles in a specific size range, the range of the pulse width in the particle detection system and the size specification range of the corresponding particles in the particle image are correspondingly corresponding. Let

Next, the separate frame identification processing will be described. After associating the number of particles of one image particle of the particle detection system with the particles to be subjected to regular identification processing, classification and identification processing is performed on unprocessed particles remaining in the captured still particle image. These unprocessed particles are particles that are not detected by the particle detection system and are present in the captured still particle image. However, important particles may be contained in these unprocessed particles, and the information cannot be discarded. To determine the concentration and quantity of untreated particles in a sample,
The number of particles per unit volume, in fact, the number of particles per sample volume corresponding to all images after processing all images is calculated, and the number of particles occupies in the sample is recalculated for all measured samples. , Particle number ratio, etc. are determined. Thus, it is necessary to calculate the sample volume corresponding to the image processed sample.

At the end of the measurement, the results of the regular identification process and the separate frame process are combined to obtain the final result.

In the separate-frame identification result, there are particles that should be originally included in the regular identification result, and it is necessary to add them to the regular identification result. If particles that do not enter the regular identification process but are exceptionally important are included, the results are also reported.

When the particle size is small and the signal level is the same as the noise signal for detection by particle detection, or when the number of particles is very large and the analysis image becomes huge, the particle detection level is increased and analysis is performed. A method that reduces the number of static particle images is preferable.

By performing the above-described series of image processing on the measurement sample, the existence ratio and the number of particles for each particle type in the sample can be determined. From these values, the particle concentration per unit volume in the measurement sample, or the number of particles converted into a microscopic field is known. The number of particles in terms of the microscope field is the average number of particles present in the microscope field with an appropriate magnification, and it is necessary to set the sample volume corresponding to the microscope field in advance.

In order to maintain the measurement accuracy, when another frame identification processing is executed for the particles remaining in the still particle image after the correspondence between one image particle count value of the particle detection system and the particles for normal identification processing, An image processed sample volume is needed. However, when the number of particles detected by the particle detection system is small, it is not possible to secure a sufficient number of still particle images, and as a result, the volume of the sample subjected to image processing may not be sufficient.

In the separate frame identification process, the analysis process is performed based on the captured still particle image. Therefore, when the original regular identification process target particles are present in a small proportion in the sample, the image-processed sample is processed. Since the particle concentration in the separate frame identification process is calculated based on the volume, there is a risk that errors will increase. This is because there are few particles in the sample, and there is no problem in the analysis accuracy.

In order to perform separate frame identification when the volume of the sample to be image-processed in this way cannot be obtained sufficiently, the measurement accuracy cannot be obtained sufficiently.
Alternatively, it is necessary to notify the operator that the measurement accuracy is low even if the separate frame identification processing is performed and that the data is not reliable. However, among the particles that are subject to separate frame identification processing,
The presence of particularly important particles must be reported regardless of the measurement accuracy.

The total number of particles subjected to the separate frame identification processing is counted, and if the number of particles reaches a preset number or more, the result of the separate frame identification processing is judged to be valid. If the number of particles has not been reached, the validity of the measurement result is determined by judging that the measurement result is invalid or displaying the degree of measurement accuracy. in this case,
The reproducibility of the number of particles for each type may be used as a criterion, or the number of processed images may be used as a reference, or the sample volume of another frame identification processing may be used as a reference. It is necessary to set these criteria before measurement.

Furthermore, when the measurement result in the separate frame identification processing does not meet the above-mentioned criteria, it is necessary to provide means for notifying the operator. It is recommended to add a comment or a symbol after the measurement result.

Further, the classification result is output as it is for particles that provide important information to the operator due to the presence of even one specific particle rather than the risk in the separate frame identification processing. In this way, the problem that measurement results cannot be obtained for exceptional particles does not occur.

Further, when the particles to be subjected to the regular identification processing exist among the particles processed by the separate frame identification processing, the particle classification accuracy is calculated by incorporating the particles into the regular identification processing particles after calculating the particle concentration per unit volume. Improve. Also in this case, since the risk of the measurement accuracy in the separate frame identification processing is taken into consideration and incorporated into the regular identification result, the incorporation does not reduce the measurement accuracy.

From the images picked up by all the particle detections, the associated particles for normal identification processing are selected,
By executing the separate frame identification process, it is possible to know the number of classifications and classification ratios of all the particles detected.

In the above description, the analysis conditions were considered to be constant for the same analysis sample, but in actual sample analysis, the analysis mode may be changed.

Even when there are a plurality of such analysis modes, the above-described regular identification processing and separate frame identification processing are performed for each analysis mode. For example, for a certain type of particles, in the first analysis mode, separate frame identification target particles are
In the second analysis mode, if the analysis is performed so that the particles are the normal identification target particles, after the analysis is completed, the classification and identification results of the individual analysis modes are combined and arranged as the particle analysis results of one analysis sample as a whole. Improve accuracy.

Further, when there are a plurality of different measurement modes, such as when the measurement conditions are different or the range of particles to be analyzed is different, different particle detection conditions, that is, the pulse level of the particle detection signal, respectively. The predetermined value of pulse width can be changed, and as a result, the particle detection conditions can be optimized.

Further, in a plurality of different measurement modes, it is possible to have a plurality of values of a predetermined particle size corresponding to the particle analysis section corresponding to different particle detection conditions, and to have a means for changing the values. The variety of conditions increases, and the accuracy of particle analysis can be improved.

For the particle detection, information such as morphological information, color information, fluorescence information from the particles or a combination thereof may be used.

An embodiment of the present invention will be described with reference to FIGS.

FIG. 1 is a conceptual diagram of a flow type particle image analysis apparatus according to an embodiment of the present invention, FIG. 2 is a block diagram showing the configuration of a particle number analysis unit in the embodiment of FIG. 1, and FIG. It is a flow chart explaining a processing content of a particle analysis part.

In FIG. 1, 100 is a flow cell and 10 is a flow cell.
1 is an image pickup means, 102 is a particle detection means, 103 is a particle analysis means, 1 is a flash lamp, 1a is a flash lamp drive circuit, 2 is a field lens, 3 is a microscope condenser lens, 5 is a microscope objective lens, and 6 is a connection lens. Image position, 7 is a projection lens, 8 is a TV camera, 11 is a field stop, 12 is an aperture stop, 14 is a microreflector, 15 is a semiconductor laser, 17 is a collimator lens, 18 is a cylindrical lens, 19 is a reflector, 20 Is a beam splitter, 2
1 is an aperture, 22 is a light detection circuit, 23 is a flash lamp lighting control circuit, 24 is an AD converter, 25 is an image memory,
26 is an image processing control circuit, 27 is a feature extraction circuit, 28 is an identification circuit, 29 is a central control unit, 40 is a particle number analysis unit, 5
Reference numeral 0 is a display unit.

In FIG. 1, the flow-type particle image analyzer according to the present embodiment is a flow cell 100 to which a liquid sample in which particles are suspended is supplied, and an image pickup means for picking up an image of particles in the sample flowing in the flow cell 100. 101,
Particle detecting means 102 for detecting particles from the imaged image
And particle analysis means 103 for analyzing the detected particles.

The sheath liquid 111 is supplied to the flow cell 100 together with the sample 110, and the sample 110 forms a flow surrounded by the sheath liquid 111. The sample flow 110 is the optical axis 9 of the microscope of the image pickup means 101 (described later).
A stable steady flow having a flat cross-sectional shape in the direction perpendicular to (described later), that is, a so-called sheath flow, which flows down the center of the flow cell 100 from the upper side to the lower side of the paper surface. The flow velocity of the sample flow 110 is the central control unit 29.
(Described later).

The image pickup means 101 has a function as a microscope, and includes a flash lamp 1 which is a pulse light source, a flash lamp drive circuit 1a for causing the flash lamp 1 to emit light, and a field which makes a pulse light flux from the flash lamp 1 parallel. The lens 2 and the microscope condenser lens 3 for focusing the parallel pulsed light flux 10 from the field lens 2 on the sample liquid flow 110 in the flow cell 100.
A microscope objective lens 5 for condensing the pulsed light flux irradiated on the sample flow 110 in the flow cell 100 and forming an image at the image forming position 6, and a particle image at the image forming position 6 projected via the projection lens 7, A TV camera 8 for converting into an image data signal which is an electric signal captured by a so-called interlace system, and a field stop 11 for limiting the width of the pulse light flux 10.
And an aperture stop 12. As the TV camera 8, a CCD camera or the like with a small afterimage is generally used.

The particle detecting means 102 includes a semiconductor laser 15 which is a detection light source for emitting a laser beam as a detection beam, a collimator lens 16 for converting the laser beam from the semiconductor laser 15 into a parallel laser beam 14, and a collimator lens 16 A cylindrical lens 17 that focuses only one direction of the laser beam 14, a reflecting mirror 18 that reflects the laser beam 14 from the cylindrical lens 17, a microscope condenser lens 3 and a flow cell 100. The laser beam 14 of the sample liquid flow 1
And a micro-reflecting mirror 19 that guides the vicinity of the upstream side of the image capturing area on 10. Further, a microscope objective lens 5 for condensing scattered light of the laser light flux 14 by the particles (this microscope objective lens 5 is also used as the image forming microscope objective lens 5 of the image pickup means 101), and the microscope objective lens 5 The beam splitter 20 that reflects the scattered light condensed by the
A light detection circuit 22 that receives light via 1 and outputs an electric signal based on the intensity thereof, and a flash lamp emission control circuit 23 that operates the flash lamp drive circuit 1a based on the electric signal from the light detection circuit 22. It has.

The particle analysis means 103 is an AD for converting the image data signal transferred from the TV camera 8 into a digital signal.
From the converter 24, an image memory 25 that stores data based on a signal from the AD converter 24 at a predetermined address, an image processing control circuit 26 that controls writing and reading of data in the image memory, and an image memory 25. A feature extraction circuit 27 that performs image processing and classifies particles based on the signal, a discrimination circuit 28, a central control unit 29, and a particle number analysis unit 40 that determines the number of particles in the sample 110.
And a display unit 50 for displaying the number of particles and the classification as a result of image processing.

The central control unit 29 is connected with the photographing condition of the TV camera 8, the sample flow condition of the flow cell 100, the control of the image processing control circuit 26, the storage of the image processing result from the identification circuit 28, and the particle number analysis unit 40. It is configured to exchange data, display on the display unit 50, and the like.

Next, referring to FIG. 2, the particle number analysis unit 40
The configuration of will be described. In the figure, the same reference numerals as those in FIG. 1 denote the same parts, and a detailed description thereof will be omitted.

In FIG. 2, 41 is a pulse level detector, 42 is a pulse width detector, 43 is a total particle counting circuit, 5
0 is a display unit, 61 is a 1-particle image size data storage unit, 6
2 is a particle classification result storage unit, 63 is a total image number counting unit, and 64 is
Is an analysis condition setting unit, 65 is a size comparison unit, 66 is a predetermined size data storage unit, 67 is a particle classification result corresponding unit, 68 is a normal classification result processing unit, 69 is another frame classification result processing unit, 70
Is a classification result totaling unit.

The pulse level detection circuit 41 which constitutes the particle number analysis unit 40 detects the particle detection signal from the photodetection circuit 22 which is higher than a predetermined signal level.

Further, the pulse width detecting section 42 detects a particle detection signal having a predetermined pulse width or more among the output signals of the pulse level detecting section 41. The total particle counting circuit 43 counts the total number of detected particles during the entire analysis time when the signal level is equal to or higher than a predetermined value and the pulse width is equal to or higher than a predetermined value.

Furthermore, the particle analysis result storage unit 62 stores the sample analysis conditions in the analysis condition setting unit 64, the total image count amount in the total image counting unit 63, that is, the count amount incremented by 1 for each image processing. The central control unit 29 sets the particle classification result of the particle image subjected to the one-particle image processing, and the parameter data which is the particle size feature amount of each classified particle in the one-particle image size data storage unit 61. It is like this.

Further, the predetermined size value corresponding to the detected size of the detected particles is stored in the predetermined size data storage unit 66, and the size comparison unit 65 compares the value with the one particle image size data storage unit 61. is there. Based on the comparison result of the size comparison unit 65, the particle classification result correspondence unit 67 determines that the particle size is large and that the particle size is normal detection particle, and the small particle size is the separate frame classification particle.

On the basis of the result of the data correspondence unit 67, the particle classification result set in the particle classification result unit 62 is used by the particle classification result correspondence unit 67 as the target particle of the normal classification process and the target of the separate frame classification process. Particles are sorted and set in the regular classification result processing unit 68 or the separate frame classification result processing unit 69, respectively.

Finally, the total particle coefficient circuit 43 for counting the total number of particles, the total image number counting section 63 for counting the total number of processed images,
Based on the particle identification processing results of the analysis condition setting unit 64, the regular classification result unit 68, and the separate frame classification result unit 69, the classification result totaling unit 70 collects the final processing results. The result is transmitted to the central control unit 29 and is output and displayed on the display unit 50 as necessary.

The operation of the flow type particle image analysis device having the above configuration will be described. First, the operations of the image pickup means 101 and the particle detection means 102 will be described. The semiconductor laser 15 constantly oscillates continuously and always observes that particles in the sample 110 pass through the detection region. The laser light flux 14 from the semiconductor laser 15 is converted into a parallel laser light flux by the collimator lens 16 and is focused by the cylindrical lens 17 in only one direction of the light flux 14.

The laser beam 14 is reflected by the reflecting mirror 18 and the micro-reflecting mirror 19 and irradiated onto the sample flow 110 in the flow cell 100. This irradiation position is a particle detection position where the laser beam 14 is focused by the cylindrical lens 17, and is a position near the upstream side of the image capturing area on the sample flow 110.

Particles to be analyzed are the above laser beam 14
This laser light beam 14 is scattered when it crosses. The scattered light of the laser beam is reflected by the beam splitter 20,
The photodetector circuit 22 receives the light and converts it into an electric signal based on the intensity thereof.

Further, the output of the photodetection circuit 22 is sent to the particle number analysis section 40, and signals having a predetermined level and a predetermined pulse width or more are regarded as detected particles, and the result is sent to the flash lamp lighting control circuit 23. Tell.

When the particles are detected, it is assumed that the particles to be image-processed have passed, and the detection signal is transmitted to the flash lamp emission control circuit 23. The predetermined delay time depends on the distance between the particle detection position and the image capturing area and the sample 110.
It is determined by the flow rate of

When the flash light emission signal is transmitted to the flash lamp drive circuit 1a, the flash lamp drive circuit 1a causes the flash lamp 1 to emit light. The pulsed light emitted from the flash lamp 1 is the optical axis 9 of the microscope.
Going up, the field lens 2 collimates the light, and the microscope condenser lens 3 focuses the light into the flow cell 1.
The sample stream 110 in 00 is illuminated.

The width of the pulse beam 10 is limited by the field stop 11 and the aperture stop 12.

Sample flow 110 in flow cell 100
The pulsed light flux radiated on the laser beam is focused by the microscope objective lens 5 and an image is formed at the image forming position 6. The image at the image forming position 6 is projected onto the image pickup surface of the TV camera 8 by the projection lens 7 and converted into an image data signal by the interlace method. In this way, the static particle image of the particles in the sample 110 is captured. The imaging conditions of the TV camera 8 are preset in the central control unit 29,
The imaging operation of the TV camera 8 is controlled according to this imaging condition.

The particle analysis means 103 will be described. T
The image data signal captured by the V camera 8 and converted by the interlace method is converted into a digital signal by the AD converter 24, and the data based on this is controlled by the image processing control circuit 26 to a predetermined address of the image memory 25. Memorized in. The data stored in the image memory 25 is read out under the control of the image processing control circuit 26, input to the feature extraction circuit 27 and the identification circuit 28 to be subjected to image processing, and the result is stored in the central control unit 29. It
The contents stored in the central control unit 29 are the particle identification feature parameters used for particle classification and the particle classification result data.

The classification and identification processing of particles is automatically performed by the pattern recognition processing which is usually performed. The result of image processing, measurement conditions, and information on the number of images subjected to image processing are sent from the central control unit 29 to the particle number analysis unit 40. In the particle number analysis unit 40, the central control unit 29, the photodetection circuit 22
Based on the particle detection signal from the image processing control signal and the control signal from the image processing control circuit 26, the correspondence between the detected particles and the particle classification result is examined, and the final classification and classification result of the particle image is summarized.

Next, the particle number analysis unit 40 will be described with reference to FIG. The total particle counting circuit 43 counts particles of a predetermined size or more from the detected particle signal through the pulse level detecting section 41 and the pulse width detecting section 42 based on the particle detection signal from the light detecting circuit 22, and the measurement is completed. Sometimes the total number of detected particles is obtained.

The flow type particle image analysis will be described. The data of the sample analysis condition set in the analysis condition setting unit 64 is determined by the processing content in the classification result totaling unit 70. Basically, data such as analysis sample volume, analysis time, sample volume equivalent to one static particle image, sample volume equivalent to one field of view of the microscope, analysis mode, etc. is required. There are some items that may be omitted.

In the total image counting unit 63, the count amount is incremented by 1 every time one image is processed, and at the end of the analysis, the total number of images processed in the analysis time is stored. The particle classification result of the still particle image obtained by image-processing one particle is set in the particle classification result unit 62 via the identification circuit 28 and the central control unit 29. At the same time, of the feature amounts used for classification and identification of the classified particles, the feature amount closest to the detection principle of the particle detection system is set in the one-particle image size data 61. This is necessary to correspond to the particle detection conditions of the detection system.

Next, the particle size information set in the one-particle image size data 61, the value set in the predetermined particle size section 66 corresponding to the particle detection condition set in advance in the particle detection system, and the size comparison section 68 are set. , Compare sizes. The comparison result of the size comparison unit 68 is calculated by the particle classification result correspondence unit 67.
If the size is larger than the predetermined size, the normal classification particles are associated, and if the size is smaller, the separate frame classification particles are associated. The results are totaled by the regular classification result processing unit 68 and the separate frame classification result processing unit 69, respectively. Regular classification result part 68 and separate frame classification result part 6
In 9, the operation of adding to the results classified and classified up to that point is performed.

When the analysis of one sample is completed, the total number of particles above the particle detection level related to the analyzed sample is the total particle counting circuit 41, the total number of image-processed images is the total image number counting unit 63, and the normal identification processing target particles. The cumulative total number of classifications is stored in the regular classification result portion 68, and the cumulative total number of particles of another frame identification processing target is stored in the separate frame classification result portion 69.

Finally, the regular classification result processing unit 68 and the separate frame classification result processing unit 69 use
Using the analysis condition of the analysis condition setting unit 64 and the information about the total image number data of the total image number counting unit 63, the classification result totaling unit 70 calculates the number of particles classified, the particle concentration, the number of particles converted into a microscopic field, and the like. To do. The final result is sorted by the classification result totaling unit 70, the result is returned to the central control unit 29, and output and displayed on the display unit 50 as necessary.

The order of particle analysis will be described with reference to the flow chart shown in FIG.

In step 1, when the analysis of the particle sample is started, the analysis conditions are first set to the analysis condition setting unit 64.
Is set to The analysis conditions to be set include the division between the normal classification and the separate frame classification, the analysis time, the amount of analysis, the classification type, the analysis mode, and the like.

In step 2, whether a series of particle detection / image processing has been completed for the entire sample,
It is determined whether or not the processing has been completed, and the process proceeds to step 3.

In step 3, particle detection, particle image pickup, particle feature extraction and particle classification identification are executed for one particle image, and the operation proceeds to step 4.

In step 4, the characteristic parameter data regarding the particle size corresponding to the particle detection condition of one particle image is set and extracted. Go to step 5.

In step 5, the particle detail data on the image obtained in step 4 is compared with the preset predetermined particle size. If it is larger than the predetermined size, the process proceeds to step 6 for normal classification result processing, and if it is smaller than the predetermined size, the process proceeds to step 7 for separate frame classification result processing.

In step 6, the normal classification result processing section 68 performs addition / totalization processing of the analysis result of the particles for normal identification processing for each particle type, and the process returns to step 2.

In step 7, the analysis result of the particles to be subjected to the separate frame identification processing is analyzed by the separate frame classification result processing unit 6 for each particle type.
The addition / aggregation process is executed in 9 and the process returns to step 2.
Step 2 is repeated until the series of particle detection and image processing is completed. When all the samples have been analyzed, the process proceeds to step 8.

In step 8, the classification result totaling unit 7
At 0, the total particle counting circuit 41 sets the total number of particles equal to or higher than the particle detection level for the analysis sample, and the total number of images processed by the total image number counting unit 63, and the process proceeds to step 9.

In step 9, the total number of classifications of particles subject to normal identification processing is read in the regular classification result processing unit 68, and the total number of classifications of particles subject to separate frame identification processing is read in the separate frame classification result processing unit 69, respectively. However, the classification result totaling unit 70 performs totalization processing of regular identification processing / separate frame identification processing to determine the number of particles in the analysis sample, and
Proceed to.

In step 10, since it may be expected that the analysis error will increase depending on the number of particles subjected to the separate frame identification processing and the sample volume subjected to the image processing, the result of the separate frame identification processing is checked to determine the number of particles, Go to step 11.

In step 11, the abundance ratio of each particle is calculated from the number of particles in the result of the regular identification processing and the result of the separate frame identification processing. Next, with respect to the particles to be subjected to regular identification processing, the number of detected particles in the sample is determined by multiplying the total number of detected particles by the above-mentioned ratio.

Next, regarding the result of the separate frame identification processing, first, from the total number of processed images and one still particle image equivalent sample volume,
The total volume of the image-processed sample is calculated, and the number of particles in the total volume of the analysis sample is determined based on the abundance ratio of the particles to be subjected to identification processing in each frame.

Based on the results of the normal identification process and the separate frame identification process, the particles existing in duplicate are sorted into one particle type, and the particles not to be analyzed are discarded. Based on these analysis results, the particle concentration in the sample is calculated, and the field-of-view converted particle number is calculated.
Proceed to step 12.

At step 12, the analysis result is output and the process ends.

Whether data is valid or invalid is determined based on the number of particles subjected to separate frame identification processing and the number of sample volume particles subjected to image processing. These criteria need to be set in advance before the analysis, but may be performed, for example, by setting the analysis conditions at the start of the analysis.

In the particle classification result 69, after correlating the image particles of the particle detection system with the particles to be subjected to the regular discrimination processing, the classification discrimination processing is executed for the unprocessed particles remaining in the captured still particle image. These untreated particles are particles that have not been detected by the particle detection system, but are present in the captured still particle image. However, important particles may be contained in these unprocessed particles, and the information cannot be discarded.

To determine the concentration and quantity of untreated particles in a sample, the number of particles per unit volume, in fact, the number of particles per sample volume corresponding to all images after processing all images was calculated. Furthermore, the number of particles in the sample, the ratio of the number of particles, and the like are determined by reconverting the values for all the measurement samples. Thus, it is necessary to calculate the sample volume corresponding to the image processed sample.

At the end of the measurement, the classification result totaling section 70 combines the results of the regular identification processing and the separate frame processing to obtain the final result.

In the separate frame identification result, there are particles that should be originally included in the regular identification result, and it is necessary to add them to the regular identification result. If particles that do not enter the regular identification process but are exceptionally important are included, the results are also reported.

After the image particles of the particle detection system are associated with the normal identification target particles, when the separate frame identification processing is executed for the particles remaining in the still particle image, the image processing necessary for maintaining the measurement accuracy is performed. Sample volume is required.
However, when the number of particles detected by the particle detection system is small, it is not possible to secure a sufficient number of still particle images, and as a result, the volume of the sample subjected to image processing may not be sufficient.

Since the separate frame identification processing performs the analysis processing based on the captured still particle image, when the original normal identification processing target particles are present in a small proportion in the sample,
Since the particle concentration in the separate frame identification processing is calculated based on the sample volume subjected to the image processing, there is a risk that errors will increase. This is because there are not many particles in the sample, and there is no problem in analysis accuracy.

As described above, in order to perform the separate frame identification when the volume of the sample to be image-processed is not sufficient, the measurement accuracy cannot be sufficiently obtained. Therefore, the separate frame processing is stopped or the separate frame identification process is performed. Even if you do it, the measurement accuracy is poor.
It is necessary to inform the operator that the data is unreliable. However, if particles that are particularly important are included in the particles that are subject to the separate frame identification processing, they must be reported regardless of the measurement accuracy.

The total number of particles subjected to the separate frame identification processing is counted, and if the number of particles reaches a preset number or more, the result of the separate frame identification processing is judged to be valid. If the number of particles has not been reached, the validity of the measurement result is determined by determining that it is invalid or displaying the degree of measurement accuracy. in this case,
The reproducibility of the number of particles for each type may be used as a criterion, or the number of processed images may be simply used as a reference, or the sample volume of another frame identification processing may be used as a reference. It is necessary to set these criteria before measurement.

Further, when the measurement result in the separate frame identification processing does not meet the above-mentioned criteria, it is necessary to provide means for notifying the operator. It is recommended to add a comment or a symbol after the measurement result.

Further, the classification result is output as it is for particles which provide the operator with important information due to the presence of even one specific particle rather than the risk in the above-mentioned separate frame identification processing. In this way, the problem that measurement results cannot be obtained for exceptional particles does not occur.

If the particles to be subjected to the regular identification processing are present among the particles processed by the above-mentioned separate frame identification processing, the particle concentration is calculated after calculating the particle concentration per unit volume, and then the particles are classified into the regular identification processing particles. The accuracy can be improved. Even in this case, since the risk of the measurement accuracy in the above-described separate frame identification processing is taken into consideration and incorporated into the regular identification result, the incorporation does not reduce the measurement accuracy.

The associated normal identification processing target particles are selected from the images picked up by all the particle detections, and the separate frame identification processing is executed to know the number of classifications and classification ratios of all the particles detected. be able to.

The case where a plurality of measurement modes exist will be described below. In the above description, the case where the number of particle analysis measurement modes is one has been described. In actual particle measurement, multiple measurement modes are used for the same measurement sample.
Measurement may be performed. At this time, each measurement mode can be analyzed, and after the analysis of all measurement modes is completed, all data can be integrated.

For example, the following measurement modes can be set.

Measurement mode 1: The particles to be measured are all particles in the sample.

Measurement mode 2: The particles to be measured are particles larger than a certain size in the sample.

The following measurement mode may be used.

Measurement mode 1: Targets particles having a small particle size.

Measurement mode 2: For those having a large particle size.

Further, a plurality of measurement modes in which the particles to be measured are limited, the size is limited, and differences in staining conditions and fluorescence emission intensity are emphasized are also conceivable.

In such a plurality of measurement modes, the particle detection condition, the corresponding particle feature amount from the particle image, the sample flow rate condition, the measurement time, and the image magnification of the optical system are first included in each measurement mode. It is necessary to switch the configuration conditions to be used.

In the analysis condition setting section 64, measurement conditions such as measurement volume, flow velocity condition in the sample, volume corresponding to one image, and measurement time are set. Further, it is necessary to reset the conditions of the level and the pulse width of the pulse level detector 41 and the pulse width detector 42 for each measurement mode. Further, in the predetermined particle size data storage unit 66, the size of the parameter of the feature-extracted particle image corresponding to the particle detection condition is stored.
It is reset for each measurement mode.

In the case of a mode in which the flow velocity of the sample changes, the flash lamp lighting control circuit 23
It is also necessary to change the time from particle detection to lamp lighting. As described above, in a plurality of different measurement modes, corresponding to different particle detection conditions, having a plurality of values of a predetermined size corresponding to the particle analysis unit, and since it is possible to have a means for changing, Increased variety of measurement conditions
It is possible to improve the accuracy of particle analysis.

When a sample is analyzed in a plurality of analysis modes, the operation is executed in each analysis mode, and the analysis data of each mode is integrated at the final stage to obtain the final result.

In this case, when there are a plurality of different measurement modes, such as when the measurement conditions are different or the range of particles to be analyzed is different, different particle detection conditions, that is, pulse of the particle detection signal, respectively. Change the predetermined value of level and pulse width.

Furthermore, in a plurality of different measurement modes, a plurality of predetermined particle size values corresponding to the particle analysis unit are provided corresponding to different particle detection conditions, and a means for changing the values is provided so that the measurement conditions can be improved. And the accuracy of particle analysis can be improved.

There is a need for a means for preventing erroneous counting of particle detection signals due to flash lamp light for capturing a still particle image. For this purpose, there is a means for removing the influence of flash lamp emission. As a method, an optical system is considered so that the flash lamp light does not reach the particle detector, or the flash lamp signal is not electrically counted. On the contrary, it is possible to correct the erroneous count by a method of detecting the flash lamp light and subtracting the number of times of lamp light emission at the end of the analysis. This is performed on the counting results of the number of one image particle and the total number of particles.

A flow-type particle image analysis method and a flow-type particle image analysis apparatus according to an embodiment of the present invention include a biological sample or cells suspended in a liquid, blood cell components such as red blood cells and white blood cells in blood, or urine. It is effective in classifying and analyzing the urinary sediment components present in it. In particular, when counting the number of particles of urinary sediment components in urine and classifying the particles, the number of particles existing in each sample may differ by several digits or more, so image processing should be performed on the particles detected by the particle detection means. Is
This is effective in obtaining information on the number of particles in the sample liquid.

However, in the urinary sediment component, the types and sizes of particles are very diverse, and it is not possible to accurately correspond the detected particles of the particle detection system and the particles in the still particle image. Accurate particle counting, particle classification,
Particle concentration can be analyzed.

In the above embodiment, the case where the still image of the particles contained in the sample continuously flowing in the flow cell is picked up and the image is analyzed is described. It can also be applied to particle image analysis of moving slide specimens.

In addition, as the particle detection of the particle detection system, the case where the laser light flux from the semiconductor laser is used as the detection light and the laser light flux scattered by the particles is used has been described, but the present invention is not limited to this. It is possible to use transmitted light, a method of detecting particles by a one-dimensional image sensor, or a method of detecting particles by a change in electric resistance due to passage of particles.

Further, in the case of using the time for the sample particles to pass through the particle detection system, that is, the pulse width of the detection pulse signal converted into an electric signal, as the particle detection, the size information in the flow direction of the particles should be reflected. You can

When considering the particle transit time that crosses the laser beam as a reference for particle detection, the particle detection size must be determined in consideration of the spread of the laser beam. It is necessary to determine the value obtained by subtracting the spread of the laser beam as the particle detection pulse width, or to re-subtract the value of the image-processed particle size and perform size comparison. However, when associating the particle detection of the particle detection system with the captured still particle image, the particle diameter information or the projection information is appropriate.

Light scattering information is usually used as the particle detecting means. In this case, a light scattering signal from particles by the laser focused light is used, and a particle detection signal having a pulse width of a predetermined value or more is used as the particle detection signal.

As the value of the predetermined pulse width, a pulse width obtained by adding the size of the laser focusing size to the particle size corresponding to the particle image processing is used. As the size of the particle image corresponding to the detected particle, the maximum size of the particle image in the sample flow direction is used.

For particle detection, in addition to the light scattering information,
Morphological information from particles, color information, fluorescence information, or combination information thereof may be used.

Further, as the particle image feature amount used for extracting and using the particle parameter from the particle image at the extraction stage, particle shape information, color information, fluorescence information, or combination information thereof may be used.

When there are a plurality of different measurement modes, such as when the measurement conditions are different or the range of particles to be analyzed is different, different particle conditions, that is,
It may be possible to change a predetermined value of the pulse level or pulse width of the particle detection signal.

Further, in a plurality of different measurement modes, there may be provided means for changing and having a plurality of values of a predetermined particle size corresponding to the size of the particle analysis stage, corresponding to different particle detection conditions. .

As the particle image identification feature quantity, morphological information, color information, fluorescence information or combination information of the measured particles can be used, and the particle detection conditions of the particle detection system can be changed accordingly. Good. Specifically, from the particle image, morphological information such as particle size, area, diameter, perimeter, and projection image, particle concentration, color information, particle internal structure, and fluorescence intensity may be used.

Information such as the existence of cell nuclei, intracellular granules and the like can be used as in biological cells.

It should be noted that, up to now, in image capture
Although the interlaced scanning has been described as the V camera imaging method, the operation and effect of the invention are the same even in the non-interlaced scanning method.

From the above description, the flow-type particle image analysis method and the flow-type particle image, each of which is equipped with a particle detection system and an image pickup system, are different in the principle of the particle detection system and the principle of particle image discrimination of the image pickup system. In the analyzer, the detected particles and the particles in the static particle image are made to correspond to each other, and even if particles other than the detection particles of the particle detection system exist in the static particle image of the image pickup system, each type of particle in the sample It is understood that the flow-type particle image analysis method and the flow-type particle image analysis device which can accurately know the information on the number, the particle existence ratio, the particle density, and the concentration, and have good analysis accuracy can be provided.

[Brief description of drawings]

FIG. 1 is a conceptual diagram of a flow-type particle image analysis device according to an embodiment of the present invention.

FIG. 2 is a block diagram showing a configuration of a particle number analysis unit in the embodiment of FIG.

FIG. 3 is a flowchart for explaining the processing contents of a particle number analysis unit in FIG.

[Explanation of symbols]

1: Flash lamp, 1a: Flash lamp drive circuit, 2: Field lens, 3: Microscope condenser lens, 5: Microscope objective lens, 6: Imaging position, 7: Projection lens, 8: TV camera, 11: Field stop, 12: Aperture stop, 14: Micro reflecting mirror, 15: Semiconductor laser, 17: Collimator lens, 18: Cylindrical lens, 19:
Reflector, 20: Beam splitter, 21: Aperture, 22:
Light detection circuit, 23: Flash lamp lighting control circuit, 2
4: AD converter, 25: image memory, 26: image processing control circuit, 27: feature extraction circuit, 28: identification circuit, 29:
Central control unit, 40: particle number analysis unit, 41: pulse level detection unit, 42: pulse width detection unit, 43: total particle counting unit,
50: display unit, 61: 1 particle image size data storage unit, 62: particle classification result storage unit, 63: total image number counting unit, 64: analysis condition setting unit, 65: size comparison unit, 6
6: predetermined size data, 67: particle classification result corresponding part, 6
8: Regular classification result processing unit, 69: Separate frame classification result processing unit,
70: Classification result totaling unit, 100: Flow cell, 101:
Image capturing means, 102: particle analyzing means, 103: particle detecting means, 110: sample flow, 111: sheath liquid.

Claims (32)

[Claims] 1. A sample is poured into a flow cell, and the flow cell is flowed.
Passing through a predetermined position of the cell, detecting particles in the sample having a size equal to or more than a predetermined value as a detection particle by a particle detection system, and particles passing through an imaging region of the flow cell. Image with a particle imaging system,
A flow-type particle image analysis method comprising: a step of obtaining the still image; and a step of extracting particles corresponding to the detected particles in the still image and performing a particle analysis on the extracted particles. 2. The flow according to claim 1, wherein the predetermined value is determined based on a transit time of the particle when the particle passes through the predetermined position. Particle image analysis method. 3. The particle detecting step includes the step of irradiating the predetermined position with light and detecting a scattered light signal scattered by the particle when the light crosses the light. Is determined on the basis of the width of the scattered light signal at a predetermined level. 4. The particle detecting step includes the step of generating a pulse having a time width corresponding to a width at a predetermined level of the scattered light signal, the transit time being determined by the time width of the pulse. The flow-type particle image analysis method according to claim 3, wherein 5. The extraction of particles corresponding to the detected particles in the still image is performed based on the maximum size of the particles in the flow direction of the sample. The flow-type particle image analysis method described in 1. 6. The flow-type particle image according to claim 1, wherein the particle analysis is performed in a plurality of predetermined measurement modes and the analysis results are integrated. analysis method. 7. The particle analyzing step includes a step of extracting an image feature amount of the extracted particles, and the image feature extraction amount is the morphological information, color information of the extracted particles,
The flow-type particle image analysis method according to any one of claims 1 to 6, which comprises fluorescence information or a combination thereof. 8. The flow-type particle image analysis method according to claim 1, wherein the particle detection is performed in a plurality of measurement modes in which the particle detection conditions can be changed. 9. The particle analysis is performed in a plurality of predetermined measurement modes, and the predetermined value can be changed corresponding to the plurality of modes. The flow-type particle image analysis method according to any one of 1 to 5. 10. The method according to claim 1, wherein the step of analyzing particles includes the step of calculating either the number of particles per sample volume or the ratio and obtaining the number of particles per total sample volume based on the calculation. The flow type particle image analysis method described in any one of the above. 11. The particle analysis step includes a step of determining either the number of particles in a sample to be measured, the particle concentration per unit volume in the sample to be measured, or the number of particles in terms of a microscopic field. The flow-type particle image analysis method according to any one of claims 1 to 9. 12. The flow-type particle according to claim 1, wherein the particle analysis step includes a step of particle analysis in which particles other than the detected particles in the still image are separately framed. Image analysis method. 13. The flow-type particle according to claim 12, wherein the processing is defined when the number of still images is small and there is not enough sample volume to be processed for performing the separate-frame particle analysis. Image analysis method. 14. The evaluation procedure according to claim 12, wherein when the number of still images is small and there is not enough sample volume to be processed for performing the separate-frame particle analysis, the evaluation procedure is set in advance. Flow type particle image analysis method. 15. The flow expression according to claim 12, wherein when the number of still images is small and there is not a sufficient sample volume to be processed for performing the separate-frame particle analysis, the separate-frame particle analysis is not performed. Particle image analysis method. 16. If the number of still images is small and there is not a sufficient sample volume to be processed for performing the separate-frame particle analysis, the separate-frame particle analysis is performed and the problem in the analysis is output. The flow-type particle image analysis method according to claim 12. 17. A means for flowing a sample into a flow cell and a particle in the sample passing through a predetermined position of the flow cell and having a size equal to or larger than a predetermined value is detected as a detection particle. A particle detection system and a particle imaging system that images a particle passing through an imaging region of the flow cell to obtain a still image of the particle, and a particle corresponding to the detected particle in the still image is extracted and extracted. Flow type particle image analysis device including a particle analysis unit that performs particle analysis on the particles. 18. The flow according to claim 17, wherein the predetermined value is determined based on a transit time of the particle when the particle passes through the predetermined position. Particle image analyzer. 19. The particle detection system includes means for irradiating the predetermined position with light, and detecting a scattered light signal scattered by the particle when the light crosses the light, the transit time The flow particle image analyzer according to claim 18, wherein is determined based on a width of the scattered light signal at a predetermined level. 20. The particle detection system includes means for generating a pulse having a time width corresponding to the width of the scattered light signal at a predetermined level, the transit time being determined by the time width of the pulse. 20. The flow-type particle image analysis device according to claim 19, wherein. 21. The extraction of the particles corresponding to the detected particles in the still image is performed based on the maximum size of the particles in the flow direction of the sample. The flow-type particle image analysis method described in 1. 22. The flow-type particle image according to claim 17, wherein the particle analysis is carried out in a plurality of predetermined measurement modes and the analysis results are integrated. analysis method. 23. The particle analysis unit extracts an image feature amount of the extracted particles, and the image feature amount includes morphological information, color information, fluorescence information of the extracted particles, or a combination thereof. The flow-type particle image analysis device according to any one of claims 17 to 22, which is characterized. 24. The flow type particle image analyzer according to claim 17, wherein said particle detection is carried out in a plurality of measurement modes in which the particle detection conditions can be changed. 25. The particle analysis is performed in a plurality of predetermined measurement modes, and the predetermined value can be changed corresponding to the plurality of modes. 21. The flow-type particle image analysis method according to any one of 21 to 21. 26. The particle analyzing unit calculates either the number of particles per sample volume or the ratio and obtains the number of particles per total sample volume based on the calculation. The described flow-type particle image analyzer. 27. The particle analysis unit obtains either the number of particles in a sample to be measured, the particle concentration per unit volume in the sample to be measured, or the number of particles converted into a microscopic field. 25. The flow-type particle image analyzer according to any one of 25 to 25. 28. The particle analysis unit, in the still image,
29. The flow-type particle image analysis device according to claim 17, wherein particles other than the detection particles are analyzed as a separate frame. 29. The flow-type particle according to claim 28, wherein the processing is defined when the number of still images is small and there is not enough sample volume to be processed for performing the separate-frame particle analysis. Image analysis device. 30. The evaluation procedure according to claim 28, wherein when the number of still images is small and there is not enough sample volume to be processed for performing the separate-frame particle analysis, the evaluation procedure is set in advance. Flow type particle image analyzer. 31. The flow expression according to claim 28, wherein when the number of still images is small and there is not enough sample volume to be processed for performing the separate-frame particle analysis, the separate-frame particle analysis is not performed. Particle image analyzer. 32. If the number of still images is small and there is not enough sample volume to be processed to perform the separate-frame particle analysis, the separate-frame particle analysis is performed and the problem in the analysis is output. The flow-type particle image analysis device according to claim 28.