JPH10132812A - Scanning-type optical measuring method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a scanning-type optical measuring method capable of judging multiple cells precisely and swiftly. SOLUTION: Multiple cells are judged using a plurality of image processing parameters about a cell region extracted in a strip (steps 901, 902). From a plurality of these judged results, an image processing parameter capable of obtaining a result nearest to a reference value based on the ratio of the number of the whole cells to that of multiple cells in the cell region stored beforehand is selected as an optimum one (step 903), and a cell data obtained from this optimum parameter is adopted (step 904).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a scanning optical measurement method in which a laser beam is scanned over a cell population and measurement is performed using an image formed from optical data from the cell population.

[0002]

2. Description of the Related Art Conventionally, a so-called scanning type in which a cell population on a slide glass is scanned with a spot in which a light beam (laser beam) is converged, and fluorescence or the like emitted from individual cells of the cell population is detected and data processed. As a cytometer, one disclosed in Japanese Patent Application Laid-Open No. 3-255365 is known. That is, such a scanning cytometer irradiates and excites a laser spot on each cell of a biological cell population biochemically labeled with a fluorescent dye, measures the fluorescence emitted by each cell, and converts the obtained data. The purpose is to analyze and present as statistical data representing the immune characteristics, genetic characteristics and cell proliferation of the cell population.

A scanning cytometer scans a cell population on a slide glass by moving an electric stage while deflecting a laser beam by a scanner driven according to a scanning waveform. Then, the fluorescence emitted from the cells excited by the laser spot by this scanning is converted into an electric signal, collected according to the logic of the data input signal output together with the scanning waveform, an image is further formed, and this image is subjected to image processing. Then, measurement data such as the area of each cell, the maximum fluorescence value, the sum of the fluorescence values, and the coordinates on the slide glass are extracted.

After such a measurement, individual cell data is displayed statistically, and the coordinates of data in a certain subset, such as abnormal peaks such as cancer on the statistical data, are reproduced under a microscope. Allows observation of the morphology of individual cells (recall function).

On the other hand, a flow cytometer having the same purpose as a scanning type cytometer is known. In this flow cytometer, a laser and a spot where the laser beam is converged are fixed, and the spot is focused on the spot. The cells in an isolated and suspended state flow out as a jet water stream, which differs from the scanning cytometer in the basic configuration of this scanning method. As described above, a scanning cytometer can observe individual cell morphology by reproducing the coordinates of a subset of data under a microscope, while a flow cytometer jets cells in an isolated suspension state. Because of the flow along with the water flow, it is impossible to find cells corresponding to the data in the subset at the abnormal peak and observe the morphology. As described above, the scanning cytometer and the flow cytometer are functionally different from each other.

[0006] The specimen used for the scanning cytometer is a cell population on a slide glass such as a smear of a floating cell liquid and a touch smear of a tissue cell. And, as a cytometer, it collects data of thousands to 10,000 cells, but the actual cells on the slide glass are not necessarily isolated individually, and when multiple cells are in contact There is. In such a case, cells isolated by image processing (hereinafter, single cells) or cells in which a plurality of cells are contacted and recognized as one (hereinafter, multiple cells)
Have been determined. The cell data thus identified can be later selected by the user as to whether or not to be used as statistical data.

However, in practice, a single cell may be erroneously recognized as a multiple cell, and conversely, a multiple cell may be erroneously recognized as a single cell. This is because the determination of multiple cells is performed by image processing, and the optimal image processing parameters vary depending on the cell diameter and state.

FIGS. 12 (a) and 12 (b) are plots showing the measurement results of individual cells when the X-axis is the sum of the fluorescence values of the cells and the Y-axis is the area of the cells. (A) and (b) in the figure are displayed based on the same data.
(B) specifies that data of cells determined to be multiple cells is not plotted. As a result, (b) has about 1/5 the data number of (a). This is due to the fact that many single cells are erroneously recognized as multiple cells.

Therefore, conventionally, in order to increase the recognition accuracy of a multiple cell, as shown in FIG.
In step 301, data is collected. In step 1302, if it is determined that misrecognition is high with reference to statistical data and individual cell morphology, the image processing parameters are reset in step 1303, and the process returns to step 1301 again to collect data. I try to collect. This is usually repeated several times without terminating once.

[0010]

However, if data collection is repeated several times rather than completed once as described above, it is troublesome for the user, and furthermore, the fading of the fluorescence of the cells during the repeated data collection may occur. In some cases, there is a problem that stable multiple cell determination cannot be performed.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a scanning optical measurement method capable of accurately and promptly determining a multiple cell.

[0012]

According to the first aspect of the present invention,
Scanning a laser beam over a cell population, forming an image by capturing optical data from the cell population, and in a scanning optical measurement method for performing measurement using the image, a cell region is obtained by image processing of the image. While extracting,
A plurality of cells are determined by using a plurality of image processing parameters set in advance for the cell region.From these determination results, a reference value based on the ratio of the total number of cells and the number of multiple cells in the cell region prepared in advance. The image processing parameter that gives the result closest to is selected as the optimal image processing parameter.

According to a second aspect of the present invention, there is provided a scanning optical measurement method in which a laser beam is scanned over a cell population, optical data from the cell population is taken in, an image is formed, and measurement is performed using the image. In the above, while extracting a cell region by image processing of the image, performing multiple cell determination with a plurality of different image processing parameters set in advance for the cell region, these determination results, the logical formula prepared in advance To select an optimal image processing parameter.

According to a third aspect of the present invention, there is provided a scanning optical measurement method in which a laser beam is scanned over a cell population, optical data from the cell population is captured, an image is formed, and measurement is performed using the image. In, while extracting a cell region by image processing of the image, performing multiple cell determination with a plurality of image processing parameters set in advance for the cell region, from the average value of the cell diameter obtained from these determination results An optimal image processing parameter is selected.

As a result, according to the first aspect of the present invention,
The complexity of parameter setting can be reduced, work efficiency can be dramatically improved, and multiple cell judgments are performed at once using multiple image processing parameters, preventing fluorescence fading and keeping measurement conditions constant. Can be

According to the second aspect of the present invention, the determination result of multiple cells based on a plurality of image processing parameters is applied to a logical expression to obtain a final determination result. By combining them, it is possible to set optimal conditions for the multiple cell determination.

According to the third aspect of the present invention, by applying a value calculated from the average diameter of the cells after data collection to image processing parameters, complicated parameter setting for multiple cell determination can be automated.

[0018]

Embodiments of the present invention will be described below with reference to the drawings. (First Embodiment) FIG. 1 shows a schematic configuration of a scanning optical measuring apparatus to which the scanning optical measuring method of the present invention is applied.

In this case, a laser beam emitted from the laser light source 1 is condensed by a spot projection lens 18, reflected by a dichroic mirror 2, and further rotated by a galvano mirror 3 about a rotation axis perpendicular to the plane of the drawing. Are reflected by the pupil projection lens 4 to form an image on the objective image plane, and thereafter, enter the optical path switching mirror 5. Accordingly, the laser beam is scanned in the vertical direction along the plane of the drawing at the position of the optical path switching mirror 5 by the presence of the rotating galvanometer mirror 3.

The laser beam is transmitted to an optical path switching mirror 5.
After being reflected by, the light is incident on the objective lens 6 and is imaged on the specimen 7. In this case, the laser spot formed on the specimen 7 is scanned in the left-right direction on the specimen 7 by rotating the galvanomirror 3 along the paper surface. In addition, the galvanomirror 3 scans the laser beam in the left-right direction along the plane of the paper on the surface of the sample 7 and at the same time, moves the scanning stage 17 in the direction orthogonal to the paper surface, thereby
The laser spot is two-dimensionally scanned.

In this case, the specimen 7 is composed of a cell population, and these cells are biochemically labeled with a fluorescent dye in advance, and emit fluorescence when excited by a laser spot. The fluorescence from the specimen 7 travels in the optical path described above in reverse, passes through the objective lens 6, the optical path switching mirror 5, the pupil projection lens 4, the galvanomirror 3, passes above the dichroic mirror 2, and further passes through the barrier filter 13. The light is condensed on a light receiving surface of a photomultiplier tube (PMT) 15 by a condenser lens 14 and detected. The scattered light from the sample 7 is detected by the photodiode 11 via the condenser lens 8 and the dichroic mirror 9.

On the other hand, the transmission illumination light source 12 and the epi-illumination illumination light source 1
By using No. 9, it can also be used as a normal microscope. In this case, the optical path switching mirror 5 is provided so as to be insertable into and removable from the optical path of the laser light, and by removing the optical path switching mirror 5 from the optical path, an observation image of the sample 7 is guided to the microscope observation optical system 16. . As a result, the observer
The transmission image and the fluorescence image of the specimen 7 can be observed with the naked eye under a microscope or can be photographed under a microscope with a television camera or a photographing device.

FIG. 2 shows an electric circuit for converting the fluorescence taken in from the photomultiplier tube 15 and the photodiode 11 into an image and processing the image, and a scanning control circuit for two-dimensionally scanning the specimen 7 with a laser spot. And so on.

In this case, the photomultiplier tube 15 includes three photomultiplier tubes 15a, 15b and 15c (PMTs 1, 2 and 2).
3), the photomultiplier tubes 15a, 15b, 1
5c is converted into image data by signal processing circuits 20a, 20b and 20c, and the electric signal corresponding to the scattered light intensity obtained from the photodiode 11 (PD11) is converted into a signal processing circuit. 2
0d is converted into image data. The image data obtained from the signal processing circuits 20a to 20d is processed by the computer 22 to create a scanned image and a processed image.

The two-dimensional scanning of the laser spot on the specimen 7 is controlled by the scanning control circuit 23, and the operation of the signal processing circuits 20 a to 20 d including the scanning control circuit 23 is controlled by the main body control unit 24. .

The CPU bus 32 of the main body control unit 24
Is connected to a signal processing circuit 20a, which is connected to a cathode of the photomultiplier tube (PMT1) 15a by the CPU 33 of the main body control unit 24 via the CPU bus 32 via a D / A converter inside the signal processing circuit 20a. A voltage is applied to control the doubling rate. In the CPU 33, a photomultiplier tube (P
MT1) The offset adjustment voltage of the photoelectric signal detected by 15a is set in the offset adjustment circuit inside the signal processing circuit 20a. The offset adjustment circuit converts the set offset adjustment voltage into a predetermined voltage by an internal D / A converter, and changes the offset voltage of the photoelectric signal detected by the photomultiplier tube (PMT1) 15a.

Other photomultiplier tubes (PMT2, PMT3)
The signal processing circuits 20b and 20c for 15b and 15c are the same as the signal processing circuit 20a for the photomultiplier tube (PMT1) 15a described above, and therefore description thereof is omitted. The signal processing circuit 2 for the photodiode 11
0d is substantially the same as the other signal processing circuits 20a to 20c, except that the D / A converter for applying the cathode voltage is not provided, and the description is omitted here.

The CPU bus 32 of the main body control unit 24 has a GPIB interface control circuit (GPI) for performing various communications between the CPU 33 and the computer 22.
A BI / F) 36, an RCU 37, and an input / output circuit 38 are connected, and a drive circuit 41 for two stepping motors 39 and 40 for moving the scanning stage 17 in the X-axis and Y-axis directions is connected to the CPU bus 32. 42, a scanning control circuit 23, which is connected to a waveform generating circuit 45 for forming a waveform for driving the galvanomirror 3, and a D / A converter 46 for applying the generated waveform to the galvanomirror 3.
By controlling the operations of the scanning stage 17 and the galvanomirror 3, the two-dimensional scanning of the laser spot on the sample 7 is enabled.

On the other hand, the computer 22 is provided with a GPIB board 47 for performing GPIB control.
Communication with the main body control unit 24 is enabled via the GPIB interface control circuit 36 on the fourth side.

In the computer 22, two memory boards 48a and 48b and one GPIB board 47 described above are mounted in an expansion slot. On these memory boards 48a and 48b, memory circuits for two channels are mounted. The transfer data from the signal processing circuit 20a is input to the channel 1 memory circuit of the memory board 48a, and the transfer data from the signal processing circuit 20b is input to the channel 2 memory circuit.
The signal processing circuit 20c is connected to the memory circuit of channel 3 of 8b.
, And the transfer data from the signal processing circuit 20 d is input to the channel 4 memory circuit. In this case, each channel is composed of two bank memories so that the computer 22 can access the other bank while data is being transferred to one bank.

Next, a description will be given of the scanning optical measuring apparatus thus configured. First, as shown in FIG. 3, a computer 22 sets a scanning area 51 set by a user in advance.
To create a plurality of strips 52 and then 1
GPIB for scanning strips and collecting data
The command is sent to the CPU 33 of the main body control unit 24.

In the CPU 33 of the main body control unit 24, the GPI
When the B command is received, the scanning control circuit 23 is driven to move the scanning stage 17 to the scanning start coordinates, and then the scanning stage 17 is moved while generating the scanning waveform to be applied to the galvanomirror 3 from the waveform generating circuit 45. Specimen 7
The upper part is scanned with laser light.

Then, in the signal processing circuit 20a, the CPU
After receiving a data collection command from the CPU 33 of the main body control unit 24 via the bus 32, 16-bit data is sequentially transferred to one bank memory of the memory board 48a in synchronization with a data input signal of a scanning waveform.

When the scanning of one scan area on the specimen 7 is completed, the signal processing circuit 20a sends a data end signal to the memory board 48a to notify the end of the data transfer. The memory board 48a that has received the data end signal switches one of the bank memories in which the scan data has been written to a state in which the computer 22 can access the bank memory.

Thereafter, the computer 22 scans the scanning area of the next one strip and collects data by the GPI.
The B command is sent to the CPU 33 of the main body control unit 24.
When the collected data can be accessed, the computer 22 accesses the transferred data, performs predetermined image processing, measures the coordinate position of the cell, the photometric data, and records and displays the data.

Next, the image processing in each strip 52 will be described. In this case, the transferred data is image data in which the fluorescence values are arranged two-dimensionally, and first, a cell region is extracted by threshold processing. Next, a feature amount such as a maximum fluorescence value, a total value, and an area is calculated for each extracted cell region. At this time, as one of the feature values, it is determined whether or not the target cell is a multiple cell.

FIG. 4 is a diagram for explaining a method of determining a multiple cell. FIG. 4 shows a state in which two cells in a scanned image are in contact with each other. That is, in this case, the cells 1 and 2 are extracted by the threshold processing, but are recognized as one cell because they are in contact with each other.

For such a cell region, first, coordinates a at which the fluorescence value shows the maximum value in the region are obtained, and then, in a rectangle surrounding the cell region, the coordinates a of the maximum value are set in eight directions from the point a of the maximum value. The image data is traced, and if there is at least one trace line having a peak at a coordinate other than the maximum value, it is determined as a multiple cell. In FIG. 4, the trace line (1)
(2) Since there are a plurality of peaks b and c of cell 1 and cell 2 on trace line (1) among (3) and (4), the cell is determined to be a multiple cell.

In this case, depending on the noise and the state of the cell, there may be a plurality of peaks even in a single cell. Therefore, the number of data reference steps when tracing is varied. The number of reference steps in this case is a value indicating an interval at which data of a scanned image is referred to when tracing a cell region, as shown in FIG. 5. If the number of reference steps is reduced, the detection sensitivity of multiple cells becomes more sensitive. Thus, the frequency of erroneously recognizing a single cell as a multiple cell increases. Conversely, when the number of reference steps is increased, the frequency of recognizing a multiple cell as a single cell increases.

FIGS. 6A, 6B, and 6C show plots in which data is collected by changing the number of steps to 4, 2, and 1, and data determined as multiple cells is not displayed. It can be seen from these figures that the smaller the number of steps is, the more data is determined to be a multiple cell.

In this embodiment, the multiple cells are determined in the following manner, and the cell data is determined from the result. The determination of multiple cells is performed according to the flowchart shown in FIG. First, image processing parameters to be used for multiple cell determination are prepared in advance. The parameter here is the number of reference steps, parameter 1 is the number of reference steps 1, parameter 2 is the number of reference steps 2, parameter 3 is the number of reference steps 3, and parameter i is the number of reference steps i ...
It corresponds as follows.

Then, in step 701, parameter 1, ie, i = 1, is set. In step 702, multiple cell determination based on parameter 1 is performed.
In step 3, the determination result is stored in result 1, and thereafter, in step 70
In step 4, until i <the number of parameters is determined,
At 05, the same operation is repeated while incrementing i, and the determination results up to the parameter number n are stored in the results 1 to n.

As described above, in order to determine the feature amount of each cell region extracted in one strip, a determination of a multiple cell based on a plurality of image processing parameters is performed. Further, such processing is performed on all the cells extracted in the strip, and the data collection ends when all the scanning ranges specified by the user have been processed.

In this case, each of the determination results 1 to n is
Using a table as shown in FIG. 8, the determination results for parameter 1 and the determination results for parameter 2 are stored for each cell data.

Then, in order to determine the cell data from these determination results, the flowchart shown in FIG. 9 is executed. First, in step 901, data is collected.
This data collection is performed according to the flowchart shown in FIG.

Next, the process proceeds to step 902, where the collected data according to each image processing parameter is referred to, and the process proceeds to step 90.
At 3, an optimal image processing parameter is selected. The selection criterion of the image processing parameter in this case is empirically determined by the cell population to be measured.For example, the ratio of the total number of cells and the number of multiple cells in a region considered to be appropriate by the cell population is a reference value. And memorize it in advance,
An image processing parameter that provides cell data closest to the reference value is selected from the above determination results 1 to n as an optimum one. Then, in step 904, the cell data obtained by the optimal image processing parameters are further subjected to image processing, the coordinate position of the cells, photometric data, and the like are measured, and recorded and displayed.

Therefore, according to this configuration, the cell region extracted in the strip is subjected to the multiple cell determination using the plurality of image processing parameters, and the cell region stored in advance is determined from the plurality of determination results. Since the image processing parameter that gives the result closest to the reference value based on the ratio of the total number of cells in the cell to the number of multiple cells was selected as the optimal one, and the cell data obtained from this optimal parameter was adopted, Compared with the case where the data collection is repeated while the image processing parameters are reset by the conventional user's judgment, the complexity of setting the parameters can be reduced and the work efficiency can be dramatically improved. In addition, since multiple cell determination is performed at once using a plurality of image processing parameters, the fading of fluorescence can be prevented, measurement conditions can be kept constant, and multiple cell determination with high accuracy can be performed.

In the above description, the number of reference steps is used as an image processing parameter by tracing in eight directions to determine a multiple cell, but it is needless to say that processing can be performed by substituting another parameter. For example, the degree of irregularity of the cell in the cell region (perimeter of the cell ＾ 2 / area) (where the outer periphery ＾
2 means the square of the outer circumference. ) Is determined by a threshold value, or the standard deviation of the fluorescence value of each cell in a cell region is determined and determined by a threshold value. There is a method of modeling with a distribution and dividing the data in the cell area into a plurality of two-dimensional normal distributions by deconvolution to determine a multiple cell. (Second Embodiment) In the above-described first embodiment, the number of reference steps is used as an image processing parameter. However, in the second embodiment, in addition to the number of reference steps, the number of reference steps in the cell region is different. The degree of heterogeneity (perimeter of the cell 細胞 2 / area) and the standard deviation of the fluorescence values in the cell area are used.

The optical configuration and the electrical configuration of the second embodiment are the same as those in FIGS. 1 and 2 described above, and these drawings are used. In this case, a threshold set as the parameter 1 based on the degree of irregularity of the cells in the cell region (perimeter of the cell ＾ 2 / area), a threshold set as the parameter 2 based on the standard deviation of the fluorescence value in the cell region, a parameter A predetermined reference step number is set as 3 respectively.

In this state, the flowchart shown in FIG. 10 is executed. First, in step 1001, regarding the cell region extracted in the strip at the time of data collection,
(1) Threshold processing with parameter 1 for cell irregularity, (2) Threshold processing for parameter 2 with respect to standard deviation of fluorescence value in the cell region, (3) Multiple cells with reference step number as parameter 3 The determination process is performed in order, and these determination results are stored as determination results 1 to 3, respectively.

Next, the process proceeds to step 1002, in which these determination results 1 to 3 are applied to a logical formula prepared in advance, and it is determined whether or not the multiple cell determination result can be adopted. The logical expression in this case is empirically set depending on the cell population to be measured. For example, as a logical expression appropriate for the cell population, (Result 1) AND (Result 2) AND
In the case of (Result 3), the determination result of the multiple cell at this time is adopted only when all the multiple cell determination conditions are satisfied, and (Result 1) OR (Result 2) OR
In the case of (Result 3), when any of the multiple cell determination conditions is satisfied, the determination result of the multiple cell at this time is adopted. Then, in step 1003, as the post-processing of the data, the cell data based on the determination result of the multiple cells adopted is further subjected to image processing, the coordinate position of the cells, photometric data, and the like are measured, and recorded and displayed.

Separately from this flow, the coordinate position of the extracted cells and photometric data are measured by image processing on the extracted cells, and a logical expression is applied to the determination results of a plurality of multiple cells at the time of analyzing these data to make a final decision. It is also possible to obtain a typical determination result and perform an analysis process.

Therefore, according to this configuration, the determination result of the multiple cells based on the plurality of image processing parameters is applied to the logical expression to obtain the final determination result. Therefore, the determination results of the plurality of multiple cells can be arbitrarily determined. By combining them, it is possible to set the optimum conditions for the multiple cell determination, and to perform the multiple cell determination with high accuracy.

In the second embodiment, the case where three parameters are used has been described. However, it goes without saying that the number of parameters may be three or more. Third Embodiment In the first embodiment, the number of reference steps is used as a basis for selecting an image processing parameter.
In the third embodiment, multiple cells are determined from the collected data using the average value of cell diameters.

Further, the optical configuration and the electrical configuration of the third embodiment are the same as those in FIGS. 1 and 2 described above, and these drawings are used. Then, the flowchart shown in FIG. 11 is executed. First,
In step 1101, as in the first embodiment, data is collected while performing a multiple cell determination on a cell population to be measured using a plurality of parameters.
Next, after processing the entire scanning range specified by the user, in step 1102, the average value of the cell diameter is obtained from the collected data. Then, in step 1103, data obtained by detecting a multiple cell with the number of reference steps closest to 1 / k of the average value is employed in the analysis processing.

In this case, 1 / k of the average value is empirically set depending on the cell population to be measured, and an appropriate k is prepared depending on the cell population. Therefore, in this way, complicated parameter setting for multiple cell determination can be automated, and labor saving of user operation can be realized.

[0057]

As described above, according to the present invention, the complexity of parameter setting can be reduced, work efficiency can be dramatically improved, and multiple cell processing can be performed using a plurality of image processing parameters at once. Since the determination is performed, the measurement condition can be kept constant by preventing the fading of the fluorescence, and the multiple cell can be determined with high accuracy.

Further, since the result of multiple cell determination based on a plurality of image processing parameters is applied to a logical expression to obtain the final result of determination, the multiple cell determination results are combined by combining the multiple cell determination results. Conditions can be set, and highly accurate multiple cell determination can be performed.

Further, by applying a value calculated from the average diameter of cells after data collection to image processing parameters, complicated parameter setting for multiple cell determination can be automated, and user operation can be saved.

[Brief description of the drawings]

FIG. 1 is a diagram illustrating a schematic configuration of a scanning optical measurement apparatus to which a scanning optical measurement method according to a first embodiment of the present invention is applied.

FIG. 2 is a diagram showing a schematic configuration of an electric circuit and a scanning control circuit of the scanning optical measurement device applied to the first embodiment.

FIG. 3 is a diagram showing a scanning area having a plurality of strips that are divided and set in advance by a user in the first embodiment.

FIG. 4 is an exemplary view for explaining the concept of multiple cell determination according to the first embodiment;

FIG. 5 is an exemplary view for explaining the concept of multiple cell determination according to the first embodiment;

FIG. 6 is a view for explaining a result when data is collected by changing the number of steps in the first embodiment.

FIG. 7 is a flowchart illustrating a method for determining a multiple cell according to the first embodiment;

FIG. 8 is a view showing a table for storing a determination result of a multiple cell according to the first embodiment;

FIG. 9 is a flowchart illustrating a multiple cell determination method according to the first embodiment;

FIG. 10 is a flowchart illustrating a second embodiment of the present invention.

FIG. 11 is a flowchart for explaining a third embodiment of the present invention.

FIG. 12 is a diagram for explaining a conventional multiple cell determination method.

FIG. 13 is a view for explaining a conventional multiple cell determination method.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 ... Laser light source, 2 ... Dichroic mirror, 3 ... Galvano mirror, 4 ... Pupil projection lens, 5 ... Optical path switching mirror, 6 ... Objective lens, 7 ... Sample, 8 ... Condenser lens, 9 ... Dichroic mirror, 11 ... Photodiode Reference numeral 12: transmission illumination light source, 13: barrier filter, 14: condenser lens, 15: photomultiplier tube (PMT), 16: microscope observation optical system, 17: scanning stage, 18: spot projection lens, 19: epi-illumination light source 20a to 20d: signal processing circuit, 22: computer, 23: scanning control circuit, 24: body control unit, 32: CPU bus, 33: CPU, 36: GPIB interface control circuit, 37: RCU, 38: input / output circuit , 39, 40 ... stepping motor, 41, 42 ... drive circuit, 45 ... waveform generation circuit, 4 ... D / A converter, 47 ... GPIB board, 48a, 48b ... memory board.

[Procedure amendment]

[Submission date] April 2, 1997

[Procedure amendment 1]

[Document name to be amended] Statement

[Correction target item name] Claim 2

[Correction method] Change

[Correction contents]

[Procedure amendment 2]

[Document name to be amended] Statement

[Correction target item name] 0021

[Correction method] Change

[Correction contents]

In this case, the specimen 7 is composed of a cell population, and these cells are biochemically labeled with a fluorescent dye in advance, and emit fluorescence when excited by a laser spot. The fluorescence from the specimen 7 travels in the optical path described above in reverse, passes through the objective lens 6, the optical path switching mirror 5, the pupil projection lens 4, the galvanomirror 3, passes above the dichroic mirror 2, and further passes through the barrier filter 13. The light is condensed on a light receiving surface of a photomultiplier tube (PMT) 15 by a condenser lens 14 and detected. The scattered light from the sample 7 is detected by the photodiode 11 via the condenser lens 8 and the beam splitter 9.

[Procedure amendment 3]

[Document name to be amended] Statement

[Correction target item name] 0028

[Correction method] Change

[Correction contents]

The CPU bus 32 of the main body control unit 24 has a GPIB interface control circuit (GPI) for performing various communications with the CPU 33 and the computer 22.
A BI / F) 36, an RCU 37, and an input / output circuit 38 are connected, and a drive circuit 41 for two stepping motors 39 and 40 for moving the scanning stage 17 in the X-axis and Y-axis directions is connected to the CPU bus 32. 42, a scanning control circuit 23, which is connected to a waveform generating circuit 45 for forming a waveform for driving the galvanomirror 3, and a D / A converter 46 for applying the generated waveform to the galvanomirror 3.
By controlling the operations of the scanning stage 17 and the galvanomirror 3, the two-dimensional scanning of the laser spot on the sample 7 is enabled.

[Procedure amendment 4]

[Document name to be amended] Statement

[Correction target item name] Explanation of sign

[Correction method] Change

[Correction contents]

[Description of Signs] 1 laser light source, 2 dichroic mirror, 3 galvano mirror, 4 pupil projection lens, 5 optical path switching mirror, 6 objective lens, 7 specimen, 8 condenser lens, 9 beam splitter Reference numeral 11: photodiode, 12: transmission illumination light source, 13: barrier filter, 14: condenser lens, 15: photomultiplier tube (PMT), 16: microscope observation optical system, 17: scanning stage, 18: spot projection lens, 19: epi-illumination light source, 20a to 20d: signal processing circuit, 22: computer, 23: scanning control circuit, 24: main body control unit, 32: CPU bus, 33: CPU, 36: GPIB interface control circuit, 37: RCU, 38 input / output circuit, 39, 40 stepping motor, 41, 42 drive circuit, 45 waveform Raw circuit, 46 ... D / A converter, 47 ... GPIB board, 48a, 48b ... memory board.

Continued on the front page (51) Int.Cl. ⁶ Identification code FI G02B 21/00 G02B 21/00 G06T 7/00 G06F 15/62 395

Claims (3)

[Claims] 1. A scanning optical measurement method that scans a cell population with a laser beam, takes in optical data from the cell population, forms an image, and performs measurement using the image. While extracting the cell region by the process, the multiple cell determination is performed with a plurality of image processing parameters set in advance for the cell region, and from these determination results, the total number of cells in the cell region prepared in advance and A scanning optical measurement method, wherein an image processing parameter that provides a result closest to a reference value based on a ratio of the number of multiple cells is selected as an optimal image processing parameter. 2. A scanning optical measurement method in which a laser beam is scanned over a cell population, optical data from the cell population is taken in, an image is formed, and measurement is performed using the image. Eye While extracting a cell region by image processing of the image, performing multiple cell determination with a plurality of different image processing parameters set in advance for the cell region, these determination results are converted into a logical formula prepared in advance. A scanning optical measurement method characterized by selecting an optimal image processing parameter to be applied. 3. A scanning optical measurement method in which a laser beam is scanned over a cell population, optical data from the cell population is captured to form an image, and measurement is performed using the image. A cell region is extracted by the processing, and multiple cell determination is performed with a plurality of image processing parameters set in advance for the cell region, and an optimal image processing parameter is determined from an average value of cell diameters obtained from these determination results. A scanning optical measurement method characterized by selecting.