Imaging system and imaging range adjustment method

Abstract

This imaging system, which images a plurality of measurement targets disposed on a plane, includes: a light source that irradiates the plurality of measurement targets with light; a light detector that detects light from the plurality of measurement targets; one or more lenses; an adjustment mechanism that focuses imaging on the plurality of measurement targets; and a drive mechanism that changes a relative position of the light detector and the plurality of measurement targets. The plurality of measurement targets have the same shape and the same size, and are aligned at an equal pitch on the plane in the vertical direction and the horizontal direction. A value obtained by multiplying the imaging magnification with the pitch of the plurality of measurement targets is an integer multiple that is at least twice the pixel pitch of the light detector, and the adjustment unit of the imaging range is less than or equal to the pixel pitch when using the drive mechanism to change the relative position.

Description

[Technical Field]

[0001] The present invention relates to an imaging system and an imaging range adjustment method. [Background technology]

[0002] In fields such as biochemistry and molecular biology, measurements are performed by adding a minute amount of sample to a microplate containing numerous small, independent reaction sites, allowing the reaction to occur, and then photographing and digitally counting the color change in the reaction sites. When photographing a measurement device with multiple wells, such as a microplate, the relationship between the well size in the plate and the pixel size of the CCD or CMOS camera used as the photodetector is important. When the well size is sufficiently larger than the pixel size, the number of pixels (number of data points) covering each well increases. On the other hand, as the well size decreases, the number of data points corresponding to each well decreases, reducing the reliability of signal intensity in data analysis. Therefore, it is necessary to increase the number of data points per well.

[0003] Patent document 1 describes that a sample holder configured with multiple wells has at least 20,000 independent reaction sites, and that an optical sensor has a predetermined number of pixels, which is at least 20 times the number of independent reaction sites. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Special Publication No. 2015-515267 Summary of the Invention [Problem to be solved by the invention]

[0005] When imaging multi-wells, the number of data points decreases depending on the well size, which leads to a decrease in the reliability of signal intensity.

[0006] To prevent a decrease in the number of data points and achieve reliable measurements, the number of data points can be increased by increasing the number of pixels in the camera or by enlarging the measurement device with multiple wells and taking multiple images. However, this leads to higher camera costs and longer measurement times.

[0007] Patent Document 1 describes the importance of maintaining a large number of pixels at each reaction site for accurate calculations during signal analysis. It also describes the possibility of slightly increasing the number of data points by changing the well shape from circular to hexagonal. However, this means that changing from circular to hexagonal increases the well area, which in turn increases the number of data points. With such a well shape, for example, if a well the size of a hexagon inscribed in a circle is used, the well area is smaller than that of a circle, which may result in a decrease in the number of data points. Furthermore, the document does not mention guidelines, methods, or effects regarding increasing the number of data points by adjusting the optical system.

[0008] The present invention has been made in view of the above circumstances, and provides a technique for increasing the number of data points per well using a camera with a smaller number of pixels, thereby improving measurement accuracy. [Means for solving the problem]

[0009] An example of an imaging system according to the present invention includes: An imaging system for imaging a plurality of measurement targets arranged on a plane, The imaging system includes: a light source that irradiates the plurality of measurement targets with light; a photodetector that detects light from the plurality of measurement objects; one or more lenses; an adjustment mechanism for focusing an image onto the plurality of measurement targets; a drive mechanism for changing the relative positions of the photodetector and the plurality of measurement targets; and The plurality of measurement targets have the same shape and size, The plurality of measurement targets are arranged at equal pitches in the vertical and horizontal directions on the plane, a value obtained by multiplying the pitch of the plurality of measurement targets by an imaging magnification is an integer multiple of two or more times the pixel pitch of the photodetector, In changing the relative position by the driving mechanism, the adjustment unit of the imaging range is equal to or smaller than the pixel pitch.

[0010] An example of an imaging range adjustment method according to the present invention includes: 1. A method for adjusting an imaging range for imaging a plurality of measurement targets arranged on a plane, comprising: the imaging range adjustment method is performed by an imaging system, The imaging system includes: a light source that irradiates the plurality of measurement targets with light; a photodetector that detects light from the plurality of measurement objects; one or more lenses; an adjustment mechanism for focusing an image onto the plurality of measurement targets; a drive mechanism for changing the relative positions of the photodetector and the plurality of measurement targets; and The plurality of measurement targets have the same shape and size, The plurality of measurement targets are arranged at equal pitches in the vertical and horizontal directions on the plane, The imaging range adjustment method includes: the driving mechanism performs focusing on the plurality of measurement targets; capturing images of the plurality of measurement targets using the photodetector; The driving mechanism rotates at least one of the plurality of measurement objects and the photodetector so that the plurality of measurement objects are arranged in a horizontal axis direction or a vertical axis direction in the image; the driving mechanism changes the relative position of the photodetector and the plurality of measurement targets in a first axis direction based on the shape of at least one of the maximum and minimum peaks in a histogram of pixel intensities in the image; the driving mechanism changes the relative position in a second axis direction perpendicular to the first axis direction based on a shape of at least one of a maximum peak and a minimum peak among peaks in a histogram of pixel intensities in the image; Equipped with.

[0011] An example of an imaging range adjustment method according to the present invention includes: 1. A method for adjusting an imaging range for imaging a plurality of measurement targets arranged on a plane, comprising: the imaging range adjustment method is performed by an imaging system, The imaging system includes: a light source that irradiates the plurality of measurement targets with light; a photodetector that detects light from the plurality of measurement objects; one or more lenses; an adjustment mechanism for focusing an image onto the plurality of measurement targets; a drive mechanism for changing the relative positions of the photodetector and the plurality of measurement targets; and The plurality of measurement targets have the same shape and size, The plurality of measurement targets are arranged at equal pitches in the vertical and horizontal directions on the plane, The imaging range adjustment method includes: the driving mechanism performs focusing on the plurality of measurement targets; capturing images of the plurality of measurement targets using the photodetector; The driving mechanism rotates at least one of the plurality of measurement objects and the photodetector so that the plurality of measurement objects are arranged in a horizontal axis direction or a vertical axis direction in the image; the drive mechanism varying the relative position in a first axis direction based on a standard deviation of pixel intensities in the image; the driving mechanism changing the relative position in a second axis direction perpendicular to the first axis direction based on a standard deviation of pixel intensities in the image; Equipped with. [Effects of the Invention]

[0012] According to the present invention, a camera with fewer pixels can be used to provide more data points per well, thereby increasing measurement accuracy.

[0013] Furthermore, since the number of effective pixels of the photodetector can be utilized to the maximum extent, the number of measurable wells per measurement can be increased.

[0014] Further features related to the present invention will become apparent from the description of the present specification and the accompanying drawings. Furthermore, problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a configuration diagram of an imaging system for adjusting an imaging range according to a first embodiment of the present invention. [Figure 2] 10 is a typical flowchart for adjusting an imaging range. [Figure 3] FIG. 10 is a diagram illustrating a method for adjusting the θ axis using a multi-well. [Figure 4] 10A and 10B are diagrams illustrating a method for adjusting the θ-axis using a reference marker. [Figure 5] 10A and 10B are diagrams illustrating distributions of signal intensity and pixel counts according to X-axis and Y-axis adjustment. [Figure 6] FIG. 6 is a diagram illustrating a peak analysis method for the distribution in FIG. 5. [Figure 7] 10 is a flowchart of a modified example of adjusting the imaging range based on area. [Figure 8] FIG. 10 is a diagram illustrating an adjustment method using standard deviation when adjusting the X-axis and Y-axis. [Figure 9] 9 is a flowchart when the method of FIG. 8 is used. [Figure 10] FIG. 1 is a diagram illustrating the relationship between the multi-wells and the pitches of the photodetector. [Figure 11] 10A and 10B are diagrams illustrating application of the imaging range adjustment method to a circular well. [Figure 12] 10A and 10B are diagrams illustrating the effect obtained by applying the imaging range adjustment method to a square well. [Figure 13] FIG. 10 is a diagram illustrating the relationship between wells and pixels for various measurement conditions. [Figure 14] FIG. 1 is a diagram illustrating a method for signal analysis of pixel intensity within a well. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0017] [Example 1] Example 1 will be described below with reference to Figures 1 to 7. Example 1 describes a method for adjusting the imaging range of an imaging system that captures images of multiple measurement targets. In Example 1, the adjustment mechanism of the imaging system can adjust the imaging range in a total of four axes: the X, Y, Z axes and the Θ axis. By using the imaging system of this example, it is possible to increase the number of data points for a well.

[0018] 1 is a diagram showing the overall configuration of an imaging system according to Example 1. The imaging system includes a microscope and is capable of capturing images of multiple measurement targets 4 arranged on a plane. The microscope includes a light source 1 that irradiates light onto the measurement targets 4, one or more lenses 2, a half mirror 3, an XYZ-axis stage 5, a θ-axis stage 6, a camera lens 7, a camera 8, an imaging unit circuit 9, a control circuit 10, and a computer 13.

[0019] Although the imaging system according to this embodiment does not include the measurement target 4, it is also possible to configure an imaging system that includes the measurement target 4.

[0020] The imaging system can execute the imaging range adjustment method for imaging a plurality of measurement targets 4 according to this embodiment.

[0021] The computer 13 has a hardware configuration as a known computer, and includes, for example, a computing means and a storage means. The computing means includes, for example, a processor, and the storage means includes, for example, a storage medium such as a semiconductor memory device or a magnetic disk device. Some or all of the storage medium may be non-transitory storage media.

[0022] The computer may also include input / output means, which include, for example, input devices such as a keyboard and a mouse, output devices such as a display and a printer, and communication devices such as a network interface.

[0023] The storage means may store a program, and the processor may execute the program to cause the computer to perform the functions described in this embodiment.

[0024] In this embodiment, the storage means is, for example, memory 11, the calculation means functions as analysis unit 12, the input device is, for example, operation unit 14 for inputting information, and the output device is, for example, display unit 15 for displaying information related to the imaging system (including images captured by camera 8).

[0025] For example, a sensor-shift type CCD or CMOS camera can be used as the camera 8, thereby enabling the acquisition of images with high resolution and precision. By using a camera 8 with 1,000,000 or more imaging elements, images with higher resolution can be acquired. The imaging magnification can be designed arbitrarily, but a magnification between 0.4 and 2.5 times is well suited to existing imaging systems.

[0026] The beam spot diameter of light from the light source 1 is adjusted by one or more lenses 2 (two in this embodiment), and after passing through a half mirror 3, it is irradiated onto multiple measurement targets 4. In one embodiment, a uniform illumination unit such as a light guide can be introduced at the position of the lens 2 to provide uniform illumination light, thereby improving optical performance. The light emitted from the multiple measurement targets 4 is reflected by the half mirror 3, collected and imaged by a camera lens 7, and detected by a camera 8.

[0027] A plurality of measurement targets 4 are movably fixed to an XYZ-axis stage 5. The XYZ-axis stage 5 moves the measurement targets 4 in the Z-axis direction relative to the camera 8. For example, the XYZ-axis stage 5 functions as an adjustment mechanism for focusing the image on the measurement targets 4.

[0028] The XYZ-axis stage 5 is fixed rotatably relative to the Θ-axis stage 6. The XYZ-axis stage 5 and the Θ-axis stage 6 function as a drive mechanism that changes the relative position between the camera 8 and the measurement object 4. For example, the XYZ-axis stage 5 translates the measurement object 4 within the XY plane, and the Θ-axis stage 6 rotates the measurement object 4 within the XY plane.

[0029] The XYZ-axis stage 5 may have one or more movement mechanisms for each axis. For example, it may have two types of movement mechanisms for the X-axis, including a manual stage and an automatic stage (stepping motor or piezoelectric element). Furthermore, the photodetector element of the camera 8 may move along the X-axis and / or Y-axis, or may rotate around the Θ-axis (in which case the camera 8 also functions as a drive mechanism).

[0030] The imaging circuit 9 transmits signals of imaging conditions to the camera 8 and receives data from the camera 8. The data received by the imaging circuit 9 is transmitted to and recorded in memory 11 in the computer 13. The data is transmitted between the memory 11 and an analysis unit 12 (analysis mechanism). The analysis unit 12 analyzes the data and, depending on the analysis results (for example, if the analysis results do not satisfy predetermined conditions), transmits signals of imaging conditions to the imaging circuit 9 and signals of control conditions for each axis to the control circuit 10.

[0031] The control circuit 10 controls the XYZ-axis stage 5 and the Θ-axis stage 6 based on signals received from the analysis unit 12. The display unit 15 displays information related to the series of processes of the imaging unit circuit 9, the control circuit 10, the memory 11, and the analysis unit 12. Control values ​​and the like used in the series of processes can be input using the operation unit 14.

[0032] Figure 2 is a flowchart showing how to adjust the imaging range using the imaging system shown in Figure 1. The adjustment method will be described with reference to the optical components shown in Figure 1. A plurality of measurement targets 4 are placed on an XYZ axis stage 5 (S1).

[0033] The camera 8 captures images of the multiple measurement targets 4, and while acquiring the images, the XYZ-axis stage 5 is moved in the Z-axis direction (for example, moved up and down) based on the acquired images to achieve an optimal focus position (S2). In this way, the XYZ-axis stage 5 performs focusing on the multiple measurement targets 4. Note that a specific method for performing focusing based on images can be appropriately designed by a person skilled in the art based on known techniques, etc.

[0034] In the Θ-axis adjustment, the multiple measurement targets 4 are rotated by the Θ-axis stage 6 (S3) to align the direction of the multi-well with a predetermined direction (S4). That is, the Θ-axis stage 6 rotates the multiple measurement targets 4 so that they are aligned in the horizontal or vertical axis direction in the image. Details will be described later with reference to Figures 3 and 4.

[0035] After adjusting the Θ axis, the camera 8 captures images of a plurality of measurement objects 4 to obtain images. That is, the intensity is measured for all pixels of the camera 8 (S5). Then, based on the shape of the peak with the maximum intensity among the peaks in the histogram of pixel intensities in the image, the XYZ-axis stage 5 changes the relative position between the camera 8 and the plurality of measurement objects 4 in the X-axis (first axis) direction (S6).

[0036] Details will be described later in relation to FIG. 5. In this embodiment, the process of S6 is executed based on the height of the peak, and is executed so that the height of the peak with the maximum intensity among the peaks in the histogram of pixel intensities in the image is maximized (S7). S6 and S7 are executed while acquiring images by the camera 8 at any time.

[0037] In one example, in S6, the relative position is moved in the X-axis direction, for example, from position X0 to position X1, and the height of the peak is acquired. Then, in S7, the height H1 of the peak acquired at position X1 is compared with the height H0 of the peak acquired at position X0. If H1≧H0, it is determined that the height of the peak has not yet reached the maximum, and the process returns to S6. On the other hand, if H1<H0, it is determined that the height of the peak has reached the maximum, and the process proceeds to S8. In this case, the maximum height of the peak is H0.

[0038] In another example, the relative position may be swept within a predetermined X-direction range to determine the position where the height of the peak is maximum.

[0039] Thereafter, similarly, adjustment in the Y-axis direction is performed. That is, based on the shape of the peak with the maximum intensity among the peaks in the histogram of pixel intensities in the image, the XYZ-axis stage 5 changes the relative position between the camera 8 and the plurality of measurement objects 4 in the Y-axis (second axis orthogonal to the first axis) direction (S8). In this embodiment, the process of S8 is executed so that the height of the peak with the maximum intensity among the peaks in the histogram of pixel intensities in the image is maximized (S9). S8 and S9 are executed while acquiring images by the camera 8 at any time.

[0040] By performing the operations of this flowchart, the number of data points in the well that can be used for analysis increases. In one modified example, instead of or in addition to the XYZ-axis stage 5 and the Θ-axis stage 6, the relative positions of the camera 8 and the multiple measurement targets 4 may be changed by using X-axis, Y-axis, and Θ-axis adjustment mechanisms provided in the camera 8.

[0041] The above is the configuration and flowchart of the imaging system of this embodiment. Below, the detailed operational flow of the θ-axis adjustment and XY-axis adjustment, which are features of this system, will be explained.

[0042] As described above, the imaging system according to this embodiment includes a memory 11 that records data from the camera 8 and an analysis unit 12 that analyzes the data. The XYZ-axis stage 5 and the Θ-axis stage 6 change the relative positions of the camera 8 and the multiple measurement targets 4 while monitoring pixel intensity in accordance with the detection results of the camera 8. This configuration enables real-time position adjustment.

[0043] FIG. 3 shows a method for adjusting multiple measurement targets 4 horizontally. In this example, multiple rectangular wells 100 are used as the multiple measurement targets 4. The rectangular wells 100 have the same shape and size, e.g., a square. The rectangular wells 100 are arranged in a 3x3 pattern. The rectangular wells 100 are arranged at equal pitches in the vertical and horizontal directions on a plane. Here, "vertical direction" and "horizontal direction" refer to directions that are perpendicular to each other, but the absolute definition of the vertical direction or horizontal direction on the XYZ axis stage 5 can be designed arbitrarily. Furthermore, if 10,000 or more rectangular wells 100 are imaged at one time, a large number of wells can be processed efficiently.

[0044] The rectangular well 100 may be a reaction well of a multi-well plate or a reaction well of digital PCR. With such a configuration, this embodiment can be applied to determination of multi-well or digital PCR.

[0045] To evaluate the levelness of multiple measurement targets 4, a line profile on the sample is acquired. A line profile is a profile that represents pixel intensity at each position on a line parallel to the X-axis, for example. A horizontal line profile is acquired so that one or more wells are included. Between the data points and intensities acquired in the line profile, strong signals are observed at well positions, and background light intensity is observed at positions where no wells exist.

[0046] To evaluate the levelness, we focus on the change period of the signal and background light intensity. When multiple measurement targets 4 are installed at an angle, the change period is not constant and there is variation. When multiple measurement targets 4 are installed horizontally, the change period is constant.

[0047] FIG. 4 shows another method for adjusting multiple measurement targets 4 to be horizontal. The method shown in FIG. 4 uses a fiducial marker 200 fabricated on the measurement target, rather than a multi-well. A line passing through two specific vertices of the fiducial marker 200 is obtained, and evaluation is performed based on whether the line is horizontal. If the line is horizontal, it means that the measurement target is installed horizontally. The shape of the fiducial marker 200 is not limited to the illustrated shape.

[0048] The above is the method for horizontally arranging multiple measurement targets 4 by operating the θ-axis stage 6. Next, adjustment of the X-axis and Y-axis by the XYZ-axis stage 5 will be described.

[0049] Figure 5 shows the relationship between wells and pixels when multiple measurement targets 4 are adjusted in the X-axis and Y-axis directions using an XYZ-axis stage 5. Figure 5(a) corresponds to the intensity measurement after the Θ-axis adjustment (S5) in Figure 2.

[0050] At the start of imaging, the relationship between the square wells 100 and the pixels 300 is random. Therefore, there are pixels that cover the entire well, and there are also pixels that cover only part of the well.

[0051] If we plot the distribution of the number of pixels versus pixel intensity at this time on a graph, we see pixel 301 with an intensity of 0, pixel 302 with an intensity of 2.5, pixel 303 with an intensity of 4, pixel 304 with an intensity of 5, and pixel 305 with an intensity of 10. As such, there is a spread in the pixel intensity distribution. Since the spread of the pixel intensity distribution leads to a decrease in the accuracy of signal analysis, it is desirable to narrow the spread of the distribution as much as possible.

[0052] To narrow the pixel intensity distribution, adjustments are made in the X-axis and Y-axis directions using the XYZ-axis stage 5, as shown in Figures 5(b) and 5(c). The order in which adjustments are made in the X-axis and Y-axis directions does not matter. By adjusting the X-axis while monitoring the pixel intensity distribution, as shown in Figure 5(b), the number of pixels that fully cover the well (i.e., pixels whose entire area corresponds to the well) increases, while the number of pixels that only partially cover the well (i.e., pixels whose part of the area corresponds to the well and the other part corresponds to the background) decreases. As a result, the spread of the pixel intensity distribution decreases.

[0053] Here, when changing the relative position using the XYZ axis stage 5, the adjustment unit of the imaging range is equal to or smaller than the pixel pitch of the camera 8, and preferably is sufficiently smaller than the pixel pitch of the camera 8. For example, the adjustment unit of the imaging range is equal to or smaller than 1 / 10 or 1 / 100 of the pixel pitch.

[0054] By adjusting the Y-axis in the same way while monitoring the pixel intensity distribution from the state shown in Figure 5(b), the number of pixels that fully cover the well increases, while the number of pixels that partially cover the well decreases. As a result, the final pixel distribution is divided into pixels 301 with an intensity of 0 and pixels 305 with an intensity of 10. Note that while multiple peaks appear in the histogram in Figure 5(c), the peak at intensity 10 corresponds to the peak with the highest intensity, and the peak at intensity 0 corresponds to the peak with the lowest intensity.

[0055] By performing such a series of adjustments, it becomes possible to increase the number of pixels that fully cover the well (the number of data points that fully cover the well). The pixel intensity values ​​are, for example, actual measurements taken by camera 8, and the distribution in Figure 5 is one example.

[0056] 6 illustrates a peak analysis method. The index of peak analysis is, for example, the peak height or the peak area. For the peak area, for example, the half-width range of the peak can be obtained, and the area within the half-width range can be used.

[0057] Alternatively, the peak area may be determined by, for example, obtaining the half-width range of the peak, calculating the average intensity and standard deviation for all pixels within the half-width range, and using the area within the range of the average value ± the standard deviation. As described above, the peak with the highest intensity is the target of analysis. In other words, in this case, the area within the range of the average pixel intensity ± the standard deviation for the peak (more precisely, within the half-width range of the peak) is used. This peak analysis method enables more appropriate analysis that takes into account not only the peak height but also the distribution within the peak.

[0058] 7 shows a flowchart of a modified example of adjusting the imaging range using the peak analysis method based on the area. S7a is executed instead of S7 in FIG. 2, and S9a is executed instead of S9 in FIG.

[0059] In this modification, the process of S6 is performed based on the area of ​​the peaks, and is performed so as to maximize the area of ​​the peak with the highest intensity among the peaks in the histogram of pixel intensities of the image (S7a).Similarly, the process of S8 is also performed based on the area of ​​the peaks, and is performed so as to maximize the area of ​​the peak with the highest intensity among the peaks in the histogram of pixel intensities of the image (S9a).

[0060] In this way, by changing the relative position of the camera 8 and the measurement target 4 based on the peak height (Fig. 2) or area (Fig. 7), the relationship between the pixel and the measurement target can be optimized. For example, the number of data points in a well can be increased, making it possible to improve the reliability of signal intensity.

[0061] In the above-described first embodiment and its variants, the relative positions of the camera 8 and the multiple measurement targets 4 are changed based on the peak shape of the peak with the maximum intensity among the peaks in the histogram (i.e., the peak with intensity 10 in Figure 5(c)). However, as a variant, the relative positions of the camera 8 and the multiple measurement targets 4 may be changed based on the peak shape of the peak with the minimum intensity among the peaks in the histogram (i.e., the peak with intensity 0 in Figure 5(c)).

[0062] Alternatively, the relative positions of the camera 8 and the plurality of measurement targets 4 may be changed based on the shapes of both the peak with the maximum intensity and the peak with the minimum intensity among the peaks in the histogram (for example, based on the sum of the heights of these two peaks). In this way, the relative positions can be optimized taking into account a wide intensity range.

[0063] [Example 2] Hereinafter, the second embodiment will be described with reference to Figures 8 and 9. Explanations of parts common to the first embodiment may be omitted.

[0064] In Example 2, the relationship between wells and pixels is determined by standard deviation when multiple measurement targets 4 are adjusted in the X-axis and Y-axis directions using the XYZ-axis stage 5. This determination method differs from Example 1 (FIG. 5) in that it is not necessary to monitor the histogram of pixel intensity distribution.

[0065] Figure 8(a) corresponds to the relative position after the Θ-axis adjustment in Figure 2. At this time, the standard deviation of all pixel intensities used in the measurement is calculated. As in Example 1 (Figure 5), pixels that fully cover the well are assigned a pixel intensity of 10, pixels that do not cover the well at all are assigned a pixel intensity of 0, and pixels that partially cover the well maintain a pixel intensity between these two.

[0066] In Figure 8(a), the standard deviation of all pixel intensities is 3.8. Figure 8(b) shows the relative position after adjustment in the X-axis direction, and Figure 8(c) shows the relative position after adjustment in the Y-axis direction. These adjustments are made to maximize the standard deviation. This series of adjustments makes it possible to increase the number of data points. The pixel intensity values ​​are actual measurements taken by camera 8, and Figure 8 is just one example.

[0067] Figure 9 shows a flowchart of the operation of Figure 8. The flowchart is the same as that of Example 1 (Figure 2) except for S7b and S9b, in which branching decisions are made based on the value of the standard deviation.

[0068] That is, the XYZ axis stage 5 changes the position between the camera 8 and the object 4 in the X axis direction based on the standard deviation of pixel intensities in the image, and then changes the relative position in the Y axis direction based on the standard deviation of pixel intensities in the image.

[0069] As described above, in Example 2 as well, the number of data points in a well can be similarly increased, making it possible to further improve the reliability of signal intensity.

[0070] [Example 3] Hereinafter, the third embodiment will be described with reference to Fig. 10. Explanations of parts common to the first and second embodiments may be omitted.

[0071] Example 3 determines the multi-well configuration for increasing the number of data points per well. In Example 3, the well shape is rectangular. The well pitch of the multi-well is determined based on the imaging magnification of the measurement system and the pixel pitch of the photodetector. By using the multi-well configuration disclosed in this example, it is possible to increase the number of data points covering the well.

[0072] The multi-well configuration is determined by the following formulas 1 to 8, which are explained by the pixel pitch, the overflow ratio, and a positive integer. x , m y ) and positive integers (a, b, c, d) satisfy the conditions of Equation 7 and Equation 8.

number

[0073] Formulas 1 to 3 determine the arrangement conditions of the multiwells in the X-axis direction, and formulas 4 to 6 determine the arrangement conditions of the multiwells in the Y-axis direction, where: pixel x : pixel pitch in the x direction pixel y : pixel pitch in the y direction W x : Well size in x direction × imaging magnification W y : Well size in y direction × imaging magnification S x : well spacing in x direction × imaging magnification S y : Well spacing in the y direction × imaging magnification P x : well pitch in x direction × imaging magnification P y : Well pitch in y direction × imaging magnification m x1 :Protrusion amount in the x direction m x2 :Protrusion amount in x direction m y1 : Amount of overhang in the y direction m y2 : Amount of overhang in the y direction m x :protrusion ratio in x direction m y :Protrusion rate in the y direction a, b, c, d: positive integers is.

[0074] The value obtained by multiplying the pitch of each well by the imaging magnification (W x and W y ) is the pixel pitch of camera 8 (pixel x and pixel y Each well and / or camera 8 is configured so that the pixel pitch of the well is an integer multiple of at least two times the pixel pitch of the camera 8. For example, one side of a magnified well in the image is configured to span an integer number of pixels (two or more; four in the example of FIG. 5). In particular, it is preferable to configure the wells so that the value obtained by multiplying the well pitch by the imaging magnification is an integer multiple of at least five times the pixel pitch of the camera 8, so that one well can be covered by a sufficient number of pixels (for example, 25 or more).

[0075] According to this embodiment, it is preferable that "well pitch x imaging magnification" is an integer multiple of at least twice the "pixel pitch." For example, when "well pitch x imaging magnification" is twice the "pixel pitch," one pixel may be assigned to each well and one pixel may be assigned to each well partition in the X-axis and Y-axis directions, respectively. To increase the number of data points within a well, the positive integers (a, c) can be set to large values.

[0076] [Example 4] Hereinafter, the fourth embodiment will be described with reference to Fig. 11. Explanation of parts common to any of the first to third embodiments may be omitted.

[0077] Example 4 shows that even when the well shape is not rectangular but circular or hexagonal, it is possible to increase the number of data points in the well by adjusting the imaging field of view as in Example 1. In Example 4, the well is a circular well 400. When imaging is performed without adjusting the imaging range, the number of pixels that fully cover the well is, for example, about 8 pixels / well. On the other hand, by adjusting the imaging range, the number of pixels that fully cover the well can be increased to 9 pixels / well.

[0078] In one variation, the number of data points can also be increased by using hexagonal wells. However, since the pixel shape of camera 8 is generally square, square wells 100 (FIG. 5) are more compatible and can generate more data points. Similarly, from the perspective of increasing the number of data points, it can be said that a multi-well arrangement in a lattice pattern (i.e., a configuration in which each row and each column are arranged in a straight line) is better than an arrangement in a hexagonal close-packed pattern (i.e., a configuration in which each row is shifted by half a column).

[0079] The well shape can be, for example, circular with a diameter of 5 μm or more and 100 μm or less, or hexagonal with a circumscribed circle with a diameter of 5 μm or more and 100 μm or less, or square with a side length of 5 μm or more and 150 μm or less. Such a configuration is well compatible with existing imaging systems.

[0080] [Example 5] Hereinafter, the fifth embodiment will be described with reference to Fig. 12. Explanation of parts common to any of the first to fourth embodiments may be omitted.

[0081] Example 5 demonstrates the effect of implementing the imaging range adjustment method using a square well. A camera 8 with a pixel size of 6.5 × 6.5 μm and a hexagonal well with a circumscribed circle diameter of 60 μm are used.

[0082] When the microscope's imaging magnification is 1.16x, the average number of fully covered pixels (full pixels) in a hexagonal well is approximately 57. When full pixel coverage is defined as the total area of ​​full pixels relative to the well area, the coverage rate is 76.5%. On the other hand, when the imaging range is adjusted using the same measurement system using a square well with a side length of 44.83 μm, the number of full pixels in the square well is 64, achieving a full pixel coverage rate of nearly 100%.

[0083] By adjusting the well pitch and pixel pitch, it is possible to increase the number of effective pixels in a measurement. Furthermore, when acquiring the same number of data points using hexagonal and square wells, the well area can be reduced by using square wells. This allows for an increase in the number of wells that can be measured at one time. For example, under the conditions shown in Figure 12, it is possible to reduce the well area by approximately 25%. Therefore, if there is a chip that can accommodate 20,000 hexagonal wells, it is possible to arrange 25,000 square wells.

[0084] [Example 6] Hereinafter, the sixth embodiment will be described with reference to Fig. 13. Explanation of parts common to any of the first to fifth embodiments may be omitted.

[0085] Example 6 shows that the same effect can be obtained even if the pixel size or well size is changed from the conditions in Figure 12. The pixel size of the sensor of camera 8 can be changed, and can be selected from several types. For example, when changing the pixel size from 6.5 x 6.5 μm to 4.5 x 4.5 μm, it is possible to maintain the same number of data points before and after the change by appropriately changing the well size according to the calculation formula in Example 3.

[0086] When changing the well size from 60 μm to 30 μm, the number of data points decreases with the same measurement system. In such a case, the camera lens 7 of the imaging system is changed to double the imaging magnification. This allows the number of data points to be increased accordingly.

[0087] As described above, according to this embodiment, the present technology can easily accommodate changes in the camera or the size of the multi-well, and can increase the number of data points.

[0088] [Example 7] Hereinafter, the seventh embodiment will be described with reference to Fig. 14. Explanation of parts common to any of the first to sixth embodiments may be omitted.

[0089] Example 7 provides a signal analysis method for data acquired after adjusting the imaging range (for example, after the processing of FIG. 2 is completed). The image is divided into three regions: a region 500 of pixels that fully cover the well, a region 501 of pixels that partially cover the well, and a region 502 of pixels that do not cover the well at all.

[0090] For signal analysis, region 500 of pixels that fully cover the well (pixels where the entire pixel corresponds to the imaged object) and region 502 of pixels that do not cover the well at all (pixels where the entire pixel corresponds to the background) are used, but region 501 of pixels that only partially cover the well (pixels where part of the pixel corresponds to the imaged object and another part of the pixel corresponds to the background) are not used.

[0091] For example, if the adjustment is based on a histogram of pixel intensities, the histogram of pixel intensities includes pixel intensities in region 500 and pixel intensities in region 502, but does not include pixel intensities in region 501. The pixels can be limited in a similar manner when standard deviation is used.

[0092] The intensity of region 500 is the signal intensity, and the intensity of region 502 is the background intensity. In the analysis, a minimum of one pixel and a maximum of all pixels within each region can be used. The signal intensity may be used as is, or the value obtained by subtracting the background intensity from the signal intensity may be used. Alternatively, the average intensity of the signal intensity and background intensity may be calculated and used for the analysis.

[0093] This type of signal analysis can be applied to well counting in digital PCR, for example. By using only areas 500 and 502 and discarding area 501, it is possible to more accurately distinguish between luminescent and non-luminescent wells, and to more accurately count the number of wells.

[0094] [Other Examples] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations. [Explanation of symbols]

[0095] 1:Light source 2: Lens 3: Half mirror 4: Multiple measurement targets 5: XYZ axis stage 6: Theta axis stage 7: Camera lens 8: Camera (photodetector) 9: Image pickup circuit 10: Control circuit 11: Memory 12:Analysis Department 13: Computer 14:Operation section 15: Display section 100: Square well 200: Reference marker 300:pixels 301: 0 intensity pixel 302: Pixel with intensity 2.5 303: Pixel with intensity 4 304: Pixel with intensity 5 305: Pixel with intensity 10 400: Circular well 500: Area of ​​pixels that fully cover the well 501: Area of ​​pixels partially covering the well 502: Area of ​​pixels not covering wells

Claims

1. An imaging system for imaging color changes due to a digital PCR reaction for a plurality of measurement targets arranged on a plane, The imaging system includes: a light source that irradiates the plurality of measurement targets with light; a photodetector that detects light from the plurality of measurement targets and acquires an image; one or more lenses; an adjustment mechanism for focusing the image of the photodetector on the plurality of measurement targets; a drive mechanism for changing the relative positions of the photodetector and the plurality of measurement targets; an analysis mechanism for performing digital count measurements; and the driving mechanism is a driving mechanism that can rotate at least one of the plurality of measurement objects and the photodetector within the plane so that the plurality of measurement objects are arranged in a horizontal axis direction or a vertical axis direction within the image, and can change the relative position of the photodetector and the plurality of measurement objects in a first axis direction and / or a second axis direction perpendicular to the first axis direction, The plurality of measurement targets have the same shape and size, The plurality of measurement targets are arranged at equal pitches in the vertical and horizontal directions on the plane, a value obtained by multiplying the pitch of the plurality of measurement targets by an imaging magnification is an integer multiple of two or more times the pixel pitch of the photodetector, an imaging system, characterized in that, in changing the relative positions by the driving mechanism, the driving mechanism arranges the multiple measurement objects in the horizontal axis direction and the vertical axis direction within the image, and then adjusts the relative positions in at least one of the horizontal axis direction and the vertical axis direction, and at this time, the adjustment unit of the imaging range is equal to or less than the pixel pitch.

2. a memory for recording data from the photodetector; The analysis mechanism analyzes the data, 2. The imaging system according to claim 1, wherein the driving mechanism adjusts the relative position in accordance with a detection result of the photodetector.

3. Each of the measurement objects is It is circular and has a diameter of 5 μm or more and 100 μm or less, A hexagon with a circumscribed circle diameter of 5 μm or more and 100 μm or less, or A square with a side length of 5 μm or more and 150 μm or less.

2. The imaging system according to claim 1, wherein:

4. 2. The imaging system according to claim 1, wherein the value obtained by multiplying the pitch of the plurality of measurement targets by an imaging magnification is an integer multiple of five or more times the pixel pitch of the photodetector.

5. 2. The imaging system according to claim 1, wherein the imaging magnification is equal to or greater than 0.4 and equal to or less than 2.

5.

6. 2. The imaging system according to claim 1, wherein the number of the measurement objects is 10,000 or more.

7. 2. The imaging system of claim 1, wherein the photodetector is a CCD or CMOS camera.

8. 8. The imaging system according to claim 7, wherein the number of imaging elements of the photodetector is 1,000,000 or more.

9. 1. A method for adjusting an imaging range for imaging color changes due to a digital PCR reaction for a plurality of measurement targets arranged on a plane, comprising: the imaging range adjustment method is performed by an imaging system, The imaging system includes: a light source that irradiates the plurality of measurement targets with light; a photodetector that detects light from the plurality of measurement objects; one or more lenses; an adjustment mechanism for focusing the image of the photodetector on the plurality of measurement targets; a drive mechanism for changing the relative positions of the photodetector and the plurality of measurement targets; an analysis mechanism for performing digital count measurements; and The plurality of measurement targets have the same shape and size, The plurality of measurement targets are arranged at equal pitches in the vertical and horizontal directions on the plane, The imaging range adjustment method includes: the driving mechanism performs focusing on the plurality of measurement targets; capturing images of the plurality of measurement targets using the photodetector; The driving mechanism rotates at least one of the plurality of measurement objects and the photodetector within the plane so that the plurality of measurement objects are aligned in a horizontal axis direction or a vertical axis direction within the image; the driving mechanism changes the relative positions of the photodetector and the plurality of measurement targets in either the horizontal axis direction or the vertical axis direction based on the shape of at least one of the maximum and minimum peaks in a histogram of pixel intensities in the image; the driving mechanism changes the relative position in the other of the horizontal axis direction and the vertical axis direction based on a peak shape of at least one of a maximum peak and a minimum peak among peaks in a histogram of pixel intensities in the image; An imaging range adjustment method comprising:

10. The imaging range adjustment method according to claim 9 , wherein the driving mechanism changes the relative position based on an area or a height of the peak.

11. The imaging range adjustment method according to claim 10 , wherein the area of ​​the peak is an area within a range of the average value of pixel intensity at the peak ±standard deviation.

12. 10. The imaging range adjustment method according to claim 9, wherein the driving mechanism changes the relative position based on the sum of the heights of the peaks in the histogram that have the maximum intensity and the peaks that have the minimum intensity.

13. The histogram is the pixel intensity of a pixel whose entirety corresponds to the imaged object; the pixel intensity of the pixel whose entire pixel corresponds to the background; Including, Some of the pixels correspond to the imaged object, and other pixels do not contain pixel intensity of pixels corresponding to the background. The imaging range adjustment method according to claim 9 .

14. 1. A method for adjusting an imaging range for imaging color changes due to a digital PCR reaction for a plurality of measurement targets arranged on a plane, comprising: the imaging range adjustment method is performed by an imaging system, The imaging system includes: a light source that irradiates the plurality of measurement targets with light; a photodetector that detects light from the plurality of measurement objects; one or more lenses; an adjustment mechanism for focusing the image of the photodetector on the plurality of measurement targets; a drive mechanism for changing the relative positions of the photodetector and the plurality of measurement targets; an analysis mechanism for performing digital count measurements; and The plurality of measurement targets have the same shape and size, The plurality of measurement targets are arranged at equal pitches in the vertical and horizontal directions on the plane, The imaging range adjustment method includes: the driving mechanism performs focusing on the plurality of measurement targets; capturing images of the plurality of measurement targets using the photodetector; The driving mechanism rotates at least one of the plurality of measurement objects and the photodetector within the plane so that the plurality of measurement objects are aligned in a horizontal axis direction or a vertical axis direction within the image; the drive mechanism changing the relative position along either the horizontal axis or the vertical axis based on a standard deviation of pixel intensities in the image; the drive mechanism changing the relative position along the other of the horizontal axis or the vertical axis based on a standard deviation of pixel intensities in the image; An imaging range adjustment method comprising:

15. 2. The imaging system according to claim 1, wherein the driving mechanism adjusts the horizontal direction so that a period between the pixel intensity at the well position and the background light intensity is constant.

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