Experiment support device, experiment support system, experiment support method and program

Abstract

To improve the efficiency of a series of works in an experiment.SOLUTION: An experiment support device comprises: one or more non-transitory computer-readable media including commands; and one or more processors executing the commands. The command is configured to cause the one or more processors to execute operations. The operations comprises: causing a display device to display a condition table TB indicating an experiment condition that should perform measurement according to the input of the experiment condition; and causing the display device to display at least one of the measurement result based on the measurement data and the analysis result of the measurement data in a cell according to the input of the measurement data acquired by using a measurement device under the experiment condition corresponding to the cell of the condition table TB.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The disclosure of this specification relates to an experiment support device, an experiment support system, an experiment support method, and a program. [Background technology]

[0002] In departments such as research and development, quality analysis, and production technology, the processing conditions for industrial products (including, for example, semiconductor components, electronic components, materials, metals, automotive parts, etc.) are determined by measuring samples made under various processing conditions with measuring equipment and comparing the measurement results.

[0003] This technique can also be used in the bioindustry. For example, by photographing samples cultured under various different culture conditions, such as the frequency of medium replacement, the number of subcultures, the temperature in the incubator, and the concentration of oxygen and carbon dioxide, and comparing the images of the samples, desirable culture conditions can be found.

[0004] In these experiments conducted to find conditions, an experimenter first creates an experimental plan and writes it down in a lab notebook. Then, following the experimental plan written in the notebook, the experimenter measures the sample using a measuring device, organizes the measurement results, and records them in the notebook. This is a task that is repeated by the experimenter. During this process, the repeated trips between the lab notebook and the measuring device are one factor that reduces the work efficiency of the experimenter.

[0005] A technology related to such a problem is described, for example, in Patent Document 1. Patent Document 1 describes a three-dimensional shape measuring device that analyzes a plurality of acquired measurement data using a plurality of analysis methods, and displays the analysis results obtained by the plurality of analysis methods for each measurement data side by side. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2016-011853 A Summary of the Invention [Problem to be solved by the invention]

[0007] According to the technology described in Patent Document 1, measurement data is analyzed using multiple analysis methods, and the analysis results are displayed side by side, thereby supporting the experimenter in examining the measurement data. However, even when the technology described in Patent Document 1 is used, the experiment plan still needs to be managed in a lab notebook, so the workload associated with going back and forth between the lab notebook and the device is not reduced.

[0008] In view of the above-mentioned circumstances, an object of one aspect of the present invention is to provide a technique for improving the efficiency of a series of tasks in an experiment. [Means for solving the problem]

[0009] An experimental support device according to one embodiment of the present invention includes one or more non-transitory computer-readable media containing instructions and one or more processors that execute the instructions, the instructions being configured to cause the one or more processors to perform operations, the operations including, in response to input of experimental conditions, causing a display device to display a table of conditions indicating the experimental conditions under which measurements should be performed, and, in response to input of measurement data acquired using a measurement device under experimental conditions corresponding to a cell of the table of conditions, causing the display device to display in the cell at least one of a measurement result based on the measurement data or an analysis result of the measurement data.

[0010] An experiment support system according to one embodiment of the present invention includes the license support device according to the above aspect, and a measurement device that outputs the measurement data to the experiment support device.

[0011] An experimental support method according to one embodiment of the present invention includes displaying a condition table indicating the experimental conditions under which measurements should be performed in response to input of experimental conditions, and displaying at least one of measurement results based on the measurement data obtained using a measurement device under experimental conditions corresponding to a cell of the condition table, or analysis results of the measurement data, in the cell in response to input of the measurement data obtained using a measurement device under experimental conditions corresponding to the cell of the condition table.

[0012] A program according to one embodiment of the present invention causes a computer to execute a process in which, in response to input of experimental conditions, a display device displays a condition table indicating the experimental conditions under which measurements should be performed, and, in response to input of measurement data acquired using a measurement device under experimental conditions corresponding to a cell of the condition table, the display device displays in the cell at least one of the measurement results based on the measurement data or the analysis results of the measurement data. Effect of the Invention

[0013] According to the above aspect, a technique for improving the efficiency of a series of operations in an experiment can be provided. [Brief description of the drawings]

[0014] [Figure 1] 1 is a diagram illustrating an example of the configuration of an experiment support system 1. [Diagram 2] FIG. 2 is a diagram illustrating an example of the configuration of a measurement device 200. [Diagram 3] 1 is a diagram illustrating an example of the configuration of an experiment support device 100. [Figure 4] 4 is a flowchart showing an example of processing performed by the experiment support device 100. [Diagram 5] 13 is a flowchart showing another example of the process performed by the experiment support device 100. [Figure 6] FIG. 13 is a diagram illustrating a condition table TB. [Figure 7] FIG. 13 is a diagram illustrating an example of a main screen 141. [Figure 8] 13 is a flowchart illustrating an example of a condition setting process. [Figure 9] FIG. 11 is a diagram for explaining a condition setting procedure. [Figure 10] FIG. 13 is a diagram illustrating an example of a main screen 141 on which a condition table TB, which is a two-condition matrix, has been created. [Figure 11] FIG. 13 is a diagram illustrating an example of a main screen 141 on which a condition table TB, which is a condition list matrix, has been created. [Figure 12] 13 is a flowchart illustrating an example of a data registration process. [Figure 13] FIG. 13 is a diagram illustrating a data acquisition screen 143 before data acquisition. [Figure 14] FIG. 14 is a diagram illustrating an example of a data acquisition screen 143 after data acquisition. [Figure 15] 13 is a flowchart illustrating an example of an analysis process. [Figure 16] FIG. 13 is a diagram illustrating an analysis screen 144 before analysis. [Figure 17] FIG. 13 is a diagram illustrating an analysis screen 144 after analysis. [Figure 18] FIG. 13 is a diagram for explaining a method of color-coding cells. [Figure 19] FIG. 13 shows an example of a main screen 141 after measurement and analysis. [Figure 20] FIG. 13 shows another example of the main screen 141 after measurement and analysis. [Figure 21] FIG. 13 shows yet another example of the main screen 141 after measurement and analysis. [Figure 22] FIG. 13 shows yet another example of the main screen 141 after measurement and analysis. [Figure 23] FIG. 13 shows yet another example of the main screen 141 after measurement and analysis. [Figure 24] FIG. 13 shows yet another example of the main screen 141 after measurement and analysis. [Diagram 25] FIG. 13 is a diagram illustrating an example of a two-condition matrix setting screen. [Figure 26] FIG. 2 is a perspective view of a measuring device 300. [Figure 27] FIG. 2 is a diagram illustrating an example of the configuration of a measurement device 300. [Figure 28]3 is a diagram illustrating an example of the configuration of a light source unit 304 and an imaging unit 305. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] Fig. 1 is a diagram illustrating an example of the configuration of an experiment support system 1. As shown in Fig. 1, the experiment support system 1 includes an experiment support device 100 and one or more measuring devices (measuring devices 200, 300, and 400) that output measurement data to the experiment support device 100. The experiment support system 1 and the experiment support device 100 are a system and a device that support measurement experiments on samples or specimens (hereinafter, both will be referred to as specimens unless otherwise distinguished) that are repeatedly performed under different experimental conditions, and support the implementation of the measurement experiments and the examination and evaluation of the measurement results and the experimental conditions.

[0016] Specifically, the experiment support system 1 and the experiment support device 100 create and manage plans for measurement experiments (hereinafter simply referred to as experiment plans), and display a list of measurement results and / or analysis results of measurement data. More specifically, the experiment support system 1 and the experiment support device 100 create a condition table indicating under what experimental conditions measurements should be performed, and display it on a display device. Furthermore, the experiment support system 1 and the experiment support device 100 associate each cell of the created condition table with measurement data measured under experimental conditions corresponding to that cell and / or analysis data generated based on the measurement data, thereby displaying a list of measurement results and / or analysis results on the condition table.

[0017] The condition table indicates the experimental conditions under which the measurement should be performed. Therefore, in the experiment support system 1 and the experiment support device 100, the experimenter does not need to refer to the experiment notebook to confirm the experimental conditions under which the measurement should be performed. In addition, in the experiment support system 1 and the experiment support device 100, the measurement results and / or analysis results are displayed in a list on the condition table. Therefore, there is no need to organize and record the measurement results and analysis results in the experiment notebook, and it is possible to consider the measurement results, analysis results, and experimental conditions without referring to the experiment notebook. In this way, the condition table can play at least a part of the role of the conventional experiment notebook. Therefore, the experimenter can omit referring to the experiment notebook by referring to the condition table. Therefore, according to the experiment support system 1 and the experiment support device 100, it is possible to minimize the number of times to and from the experiment notebook and the device, thereby making the series of tasks in the experiment more efficient, and as a result, the burden on the experimenter can be reduced.

[0018] In this specification, the measurement data refers to data generated by a measurement device performing a measurement, and the measurement result refers to information displayed on a display device based on the measurement data. For example, if the measurement data is image data, the measurement result is an image displayed based on the image data. In addition, in this specification, the analysis data refers to data generated by an experiment support device by analyzing the measurement data using a predetermined analysis method, and the analysis result refers to information displayed on a display device based on the analysis data. For example, if the measurement data is image data, the analysis data is a representative value that represents an image obtained by analyzing the image data, and the analysis result is an image in which the representative value is visualized using symbols such as numbers, colors, and concentrations.

[0019] Experimental conditions refer to all conditions necessary to reproduce the measurement results and analysis results obtained by a measurement experiment. Experimental conditions include conditions for the sample (hereinafter referred to as sample conditions), conditions for the measurement device (hereinafter referred to as device conditions), and conditions for the experimental environment other than the sample and device (hereinafter referred to as environmental conditions). If the sample is a processed product, the sample conditions include processing conditions (e.g., temperature, humidity, processing speed, processing time, etc. during product processing). Sample conditions also include component conditions of the sample (e.g., the amount or content ratio of a specific component contained in the sample). Device conditions include various settings of the device. If the device conditions are a photographing device, the device conditions include photographing conditions (e.g., illumination intensity, exposure time, photographing magnification, etc.). Environmental conditions include conditions that specify the environment in which the sample and / or measurement device are placed. If an optical measurement is performed by a measurement device, the environmental conditions include the intensity (brightness) of the ambient light at the time of measurement.

[0020] FIG. 2 is a diagram illustrating the configuration of the measuring device 200. The measuring device 200, which is an example of a measuring device that generates measurement data, is a microscope device that acquires image data of a sample, and more specifically, is a laser scanning microscope device. That is, the measuring device included in the experiment support system 1 or that outputs measurement data to the experiment support device 100 may include a microscope device. The measuring device may also include a laser scanning microscope device, and the experiment support system 1 including the measuring device 200 and the experiment support device 100 may be a laser scanning microscope system. Hereinafter, the configuration of the measuring device 200 will be specifically described with reference to FIG. 2.

[0021] The measuring device 200 includes a laser light source 201, a polarizing beam splitter (hereinafter referred to as PBS) 202, a scanning unit 203 which is a scanning means for scanning a sample 206, a 1 / 4λ plate 204, an objective lens 205, an imaging lens 207, a pinhole plate 208, a photodetector 209, an AD converter 210, a revolver 211, an XY stage 214, a white light source 215, an imaging lens 216, and a camera 217.

[0022] The revolver 211 functions as a means for switching the objective lens 205 and also as a means for changing the relative distance between the objective lens 205 and the sample 206. That is, in the experiment support system 1, the revolver 211 is an example of a scanning means for scanning the sample 206 in the optical axis direction of the objective lens 205, and the scanning unit 203 is an example of a scanning means for scanning the sample 206 in a direction perpendicular to the optical axis. In addition, the XY stage 214 is an example of a means for moving the sample 206 relative to the objective lens 205 in a direction perpendicular to the optical axis of the objective lens 205.

[0023] The laser light emitted from the laser light source 201 passes through the PBS 202 and then enters the scanning unit 203. The scanning unit 203 includes, for example, a galvanometer scanner and a resonant scanner capable of scanning light in mutually orthogonal directions. The laser light deflected by the scanning unit 203 is converted from linearly polarized light to circularly polarized light by the ¼λ plate 204, and then irradiated onto the sample 206 via the objective lens 205 attached to the revolver 211.

[0024] In the measurement device 200, a pair of scanners included in the scanning unit 203 is disposed at or near a position optically conjugate with the pupil position of the objective lens 205. Therefore, by the scanning unit 203 deflecting the laser light, the focusing position of the laser light moves on the focal plane of the objective lens 205 in the XY directions perpendicular to the optical axis of the objective lens, whereby the sample 206 is two-dimensionally scanned with the laser light.

[0025] Here, the two-dimensional scanning (XY scanning) by the scanning unit 203 and the driving of the revolver 211 in the optical axis direction (Z direction) of the objective lens 205 (Z scanning) are controlled by the experiment support device 100 that controls the measurement device 200. That is, the experiment support device 100 is an example of a scanning control means that controls the scanning means. Note that the method of the two-dimensional scanning by the scanning unit 203 is not particularly limited, but for example, raster scanning, which is generally used in confocal microscopes, may be adopted. In addition, the switching of the objective lens 205 arranged on the optical path of the measurement device 200 by the rotational driving of the revolver 211 and the driving of the XY stage 214 in the direction perpendicular to the optical axis of the objective lens 205 (XY direction) are also controlled by the experiment support device 100.

[0026] The laser light reflected on the surface of the sample 206 (hereinafter referred to as reflected light) is converted from circularly polarized light to linearly polarized light by the ¼ lambda plate 204 which enters it via the objective lens 205, and then enters the PBS 202 via the scanning unit 203. At this time, the reflected light entering the PBS 202 has a polarization plane perpendicular to the polarization plane of the laser light entering the PBS 202 from the laser light source 201 side, so is reflected by the PBS 202 and guided to the imaging lens 207.

[0027] The imaging lens 207 focuses the light reflected by the PBS 202. A pinhole plate 208 provided on the path of reflected light from the PBS 202 has a pinhole formed at a position optically conjugate with the focusing position of the laser light formed on the focal plane of the objective lens 205. Therefore, when a certain portion of the surface of the sample 206 is at the focusing position of the laser light by the objective lens 205, the reflected light from this portion is focused at the pinhole and passes through the pinhole. On the other hand, when a certain portion of the surface of the sample 206 is deviated from the focusing position of the laser light by the objective lens 205, the reflected light from this portion is not focused at the pinhole, so it does not pass through the pinhole and is blocked by the pinhole plate 208.

[0028] The light passing through the pinhole is detected by the photodetector 209. The photodetector 209 is, for example, a photomultiplier tube (PMT). The photodetector 209 receives the light passing through the pinhole, i.e., the reflected light from a portion of the surface of the sample 206 that coincides with the focusing position of the laser light by the objective lens 205, and outputs a detection signal having a magnitude corresponding to the amount of received light as a luminance signal indicating the luminance of the portion. This luminance signal, which is an analog signal, is analog-digitally converted by the AD converter 210 and input to the experiment support device 100 as luminance value information indicating the luminance of the portion. That is, the measurement device 200 outputs measurement data consisting of this luminance value information and scanning position information from the scanning unit 203 to the experiment support device 100. In this case, the measurement data is confocal image data which is a set of luminance values ​​at each coordinate, and the experiment support device 100 can display a confocal image which is an example of a measurement result based on the measurement data acquired from the measurement device 200.

[0029] On the other hand, light (white light) emitted from a white light source 215 is focused at the pupil position of an objective lens 205 attached to a revolver 211, and then irradiated onto a sample 206. This illuminates the sample 206 by the Kohler illumination method. The light reflected from the surface of the sample 206 enters an imaging lens 216, which focuses the reflected light on a light receiving surface of a camera 217.

[0030] The camera 217 is a camera having a light receiving surface at a position optically conjugate with the focal plane of the objective lens 205, for example, a color CCD camera having a CCD (Charge-Coupled Device) image sensor, or a color CMOS camera having a CMOS (Complementary MOS) image sensor. The camera 217 photographs the sample 206 using reflected light collected on the light receiving surface, and outputs non-confocal image data obtained by photographing to the experiment support device 100. That is, the measurement device 200 outputs measurement data, which is non-confocal image data of the sample 206, to the experiment support device 100. In this case, the measurement data is non-confocal image data that is a collection of color information at each coordinate, and the experiment support device 100 can display a non-confocal image, which is an example of a measurement result, based on the measurement data acquired from the measurement device 200.

[0031] Fig. 3 is a diagram illustrating the configuration of an experiment support device 100. The experiment support device 100, which is an example of an experiment support device that acquires measurement data from a measurement device, is a microscope control device that configures a microscope system together with a measurement device 200, which is a microscope device. However, the experiment support device that acquires measurement data from a measurement device does not necessarily have to control the measurement device, and the measurement device may be controlled by a device other than the experiment support device. The configuration of the experiment support device 100 will be specifically described below with reference to Fig. 3.

[0032] The experiment support device 100 is a device that controls a measuring device and acquires measurement data generated by the measuring device. Specifically, the experiment support device 100 controls the photographing of a sample by the measuring device 200 and acquires the measurement data obtained by photographing from the measuring device 200. Note that the experiment support device 100 may be a computer that includes one or more non-transitory computer-readable media containing instructions and one or more processors that execute the instructions, and the instructions may be configured to cause the one or more processors to execute a predetermined operation.

[0033] More specifically, the experiment support device 100 may include, for example, one or more processors 110, one or more memory devices 120, an input device 130, a display device 140, and a communication device 150, as shown in FIG. 3, which may be connected via a bus 160.

[0034] Each of the one or more processors 110 is hardware including, for example, a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), etc., and performs programmed processing by executing a program 121 stored in one or more storage devices 120. Furthermore, the one or more processors 110 may include an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), etc.

[0035] Each of the one or more storage devices 120 may include, for example, one or more arbitrary semiconductor memories, and may further include one or more other storage devices. The semiconductor memories may include, for example, volatile memories such as RAM (Random Access Memory), and non-volatile memories such as ROM (Read Only Memory), programmable ROM, and flash memory. The RAM may include, for example, DRAM (Dynamic Random Access Memory), SRAM (Static Random Access Memory), and the like. The other storage devices may include, for example, magnetic storage devices including magnetic disks, optical storage devices including optical disks, and the like.

[0036] The one or more storage devices 120 are non-transitory computer-readable media, and are an example of a storage unit of the experiment support system 1. At least one of the storage devices 120 stores measurement data acquired from a measurement device.

[0037] The input device 130 is a device that is directly operated by an experimenter, and may be, for example, a keyboard, a mouse, or a touch panel. The display device 140 may be, for example, a liquid crystal display, an organic EL display, or a CRT (Cathode Ray Tube) display. The display may have a built-in touch panel. The communication device 150 may be a wired communication module or a wireless communication module.

[0038] 3 is an example of a hardware configuration of the experiment support device 100, and the experiment support device 100 is not limited to this configuration. The experiment support device 100 is not limited to a general-purpose device, and may be a dedicated device. Furthermore, the experiment support device 100 may be configured integrally with the measurement device 200. In other words, the experiment support system 1 may be configured by a single device or by multiple devices.

[0039] The experiment support device 100 configured as described above may generate various types of image data indicating the measurement results based on the confocal image data or non-confocal image data, which is the measurement data output from the measuring device 200, by having the processor 110 execute the program 121, and may display the various types of measurement results on the display device 140.

[0040] For example, the experiment support device 100 may control the measurement device 200 to change the relative distance between the sample 206 and the objective lens 205, and may acquire confocal image data and non-confocal image data from the measurement device 200 each time the relative distance changes by a predetermined value. After that, the experiment support device 100 may compare the luminance values ​​of pixels at the same coordinates (pixels at the same coordinates on a plane perpendicular to the Z direction) in the acquired multiple image data. Then, the experiment support device 100 may detect, for each pixel, the maximum luminance value and the position information (height information) in the Z direction when the image data having the maximum luminance value was acquired. The experiment support device 100 may generate three-dimensional (3D) data such as laser extended image data, color extended image data, and height image data based on the multiple image data, the maximum luminance value for each pixel, and the height information.

[0041] The laser extended image data is data of an extended focus image generated based on a plurality of confocal image data. The color extended image data is data of an extended focus image generated based on a plurality of non-confocal image data. Furthermore, the height image data is data of an image that represents height using colors or shading in a color table, generated based on a plurality of confocal image data. The experiment support device 100 may display each image as a measurement result in two-dimensional and / or three-dimensional display based on these image data.

[0042] Furthermore, the experiment support device 100 may control the measuring device 200 so that multiple regions of the sample 206 having different coordinates in a direction perpendicular to the optical axis of the objective lens 205 are photographed. Also, the measuring device 200 may be controlled so that photographing is performed at multiple positions in each region having different coordinates in the optical axis direction. Furthermore, the experiment support device 100 may generate map image data based on multiple confocal image data and non-confocal image data obtained by photographing.

[0043] The map image data is generated based on a plurality of confocal image data or a plurality of non-confocal image data, and is data of an image obtained by pasting together a plurality of different image data. The experiment support device 100 may display the map image as a measurement result in two-dimensional and / or three-dimensional display based on the map image data.

[0044] Fig. 4 is a flowchart showing an example of processing performed by the experiment support device 100. Fig. 5 is a flowchart showing another example of processing performed by the experiment support device 100. Fig. 6 is a diagram showing an example of a condition table TB. Hereinafter, an experiment support method performed in the experiment support device 100 will be described with reference to Figs. 4 to 6. Note that the processing shown in Figs. 4 and 5 are each an example of an experiment support method, and are performed, for example, by the processor 110 executing the program 121.

[0045] 4 starts, the experimenter uses the input device 130 to input the experimental conditions considered in advance into the experiment support device 100. The experiment support device 100 detects the input by the experimenter and sets the conditions (step S1). More specifically, the processor 110 creates a condition table in response to the input of the experimental conditions, and causes the display device 140 to display the created condition table.

[0046] Here, the condition table refers to a table showing the experimental conditions (including a combination of multiple experimental conditions) under which measurements should be performed. The condition table has one or more dedicated areas (cells) for each experimental condition, and is typically a two-dimensional table (matrix), although there are no particular limitations. Furthermore, inputting experimental conditions refers to, for example, inputting the number of experimental conditions, inputting the names of the experimental conditions, inputting the values ​​of the experimental conditions, or inputting a combination of these. The number of experimental conditions refers to the number of experimental conditions, or more specifically, the number of types of experimental conditions. The values ​​of the experimental conditions may include numerical values, character strings, etc.

[0047] When the condition setting is completed, the experiment support device 100 registers data in the cells of the condition table (step S2). More specifically, the processor 110 registers, in the cell of the condition table selected by the experimenter, the measurement data acquired using the measuring device 200 under the experimental conditions corresponding to that cell. That is, the processor 110 associates the measurement data with the cell of the condition table. Note that the measurement data registered in the cell may be measurement data acquired in advance using the measuring device 200 before the cell is selected, or may be measurement data acquired using the measuring device 200 by the experiment support device 100 controlling the measuring device 200 after the cell is selected.

[0048] Furthermore, when the experiment support device 100 acquires measurement data by controlling the measuring device 200 after cell selection, the experiment support device 100 may name the file name of the acquired measurement data using the experimental conditions at the time of measurement (i.e., the experimental conditions corresponding to the cell). Also, when the experiment support device 100 registers the measurement data acquired in advance before cell selection in a cell, the experiment support device 100 may rename the file name of the measurement data using the experimental conditions at the time of measurement. That is, in step S2, the experiment support device 100 may name the file name of the measurement data acquired using the measuring device 200 under the experimental conditions corresponding to the cell in the condition table using the experimental conditions at the time of acquisition of the measurement data.

[0049] When the data is registered in the cell of the condition table, the experiment support device 100 displays the measurement result in that cell (step S3). More specifically, the processor 110 causes the display device 140 to display the measurement result based on the measurement data registered in step 2 in the cell in which the measurement data was registered in step S2. In other words, in step S3, in response to the input of measurement data acquired using the measurement device 200 under experimental conditions corresponding to the cell of the condition table, the processor 110 causes the display device 140 to display the measurement result based on that measurement data in the cell.

[0050] Thereafter, the experiment support device 100 judges whether or not an end instruction has been given (step S4), and if an end instruction has not been given (step S4NO), the processes of steps S2 and S3 are repeated. As a result, every time measurement data is registered in a cell of the condition table, a measurement result based on the measurement data measured under the experimental conditions corresponding to that cell is added. That is, the processor 110 causes the display device 140 to update the display of the condition table every time measurement data acquired using the measurement device 200 is input.

[0051] Furthermore, the experiment support device 100 may perform the process shown in Fig. 5 instead of the process shown in Fig. 4. When the process shown in Fig. 5 is started, the experimenter uses the input device 130 to input the experimental conditions considered in advance to the experiment support device 100. The experiment support device 100 detects the input by the experimenter, sets the conditions (step S11), and registers the data in the cells of the created condition table (step S12). The processes of steps S11 and S12 are the same as the processes of steps S1 and S2 in Fig. 4.

[0052] When data is registered in the cells of the condition table, the experiment support device 100 further analyzes the registered measurement data (step S13). More specifically, the processor 110 analyzes the measurement data using one or more analysis methods to generate analysis data indicating the analysis results. The one or more analysis methods may be explicitly specified by the experimenter. In addition, one or more analysis methods determined based on the past analysis history of the experiment support device 100 may be specified for the measurement data.

[0053] The analysis data generated in step S13 may be registered in a cell together with the measurement data. That is, the processor 110 may associate the measurement data and the analysis data with a cell of the condition table. In addition, in step S13, the experiment support device 100 may name the file name of the analysis data using the experimental conditions when the measurement data corresponding to the analysis data was acquired, or may name the file name of the analysis data using the experimental conditions and the name of the analysis method used in the analysis.

[0054] When the analysis of the measurement data is completed, the experiment support device 100 colors the cells in which the measurement data and the analysis data are registered (step S14). Specifically, the processor 110 determines the color to be assigned to the cell in which the analysis data is registered based on the analysis data generated in step S13, thereby color-coding the cells in the condition table. More specifically, the processor 110 may determine the color to be assigned to the cell according to the value of the analysis data, and may, for example, make the color of the cell closer to a warm color such as red as the value increases, and closer to a cool color such as blue as the value decreases. In addition, the color coding may be performed by assigning different colors to cells according to differences in hue, different colors to cells according to differences in brightness, or different colors to cells according to different combinations of hue and brightness. In addition, the colors include achromatic colors in addition to chromatic colors. That is, the color coding may be performed in grayscale.

[0055] After completing the color coding, the experiment support device 100 displays at least one of the measurement result and the analysis result in the cell (step S15). More specifically, the processor 110 causes the display device 140 to display at least one of the measurement result based on the measurement data registered in step 12 and the analysis result based on the analysis data generated in step S13 in the cell in which the measurement data and the analysis data have been registered. At this time, the color of the cell (more specifically, the background color of the cell) is displayed in the color determined by the color coding in step S14.

[0056] After that, the experiment support device 100 judges whether or not an end instruction has been given (step S16), and if an end instruction has not been given (step S16 NO), the process repeats steps S12 to S15. As a result, every time measurement data and analysis data are registered in a cell of the condition table, at least one of the measurement result and the analysis result based on the measurement data measured under the experimental conditions corresponding to that cell is additionally displayed. In the following, unless there is a particular distinction between the measurement result and the analysis result, they will be collectively referred to as the experiment result.

[0057] By implementing the experiment support method shown in Fig. 4 or Fig. 5, the experiment support device 100 can create a condition table TB having a cell for each experimental condition to be measured as shown in Fig. 6, and can display a list of experimental results in the condition table TB. As a result, an experimenter can distinguish and recognize whether the experimental conditions to be measured are experimental conditions that have already been measured or experimental conditions that have not yet been measured by referring to the condition table TB as shown in Fig. 6. Therefore, without referring to a lab notebook, the experimenter can identify the experimental conditions for a new measurement to be performed and continue the experiment efficiently. In addition, since it becomes difficult to overlook experimental conditions that should be measured, it is possible to prevent measurement omissions from occurring.

[0058] In addition, since the experimental results are displayed in a list, it is easy to grasp the tendency or anomaly of the experimental results caused by the difference in the experimental conditions. Furthermore, since the display of the condition table is updated every time data is registered in a cell, the experimental results obtained while acquiring the measurement data can be evaluated at any time. Therefore, it is possible to predict the presence or absence of correlation between a specific experimental condition and the experimental results before the measurement under all experimental conditions is completed. In particular, by implementing the experimental support method shown in FIG. 5, the cells of the condition table are color-coded as shown in FIG. 6, so that the presence or absence of correlation between a specific experimental condition and the experimental results can be more intuitively grasped. Therefore, it is possible to easily and quickly determine the necessity of measurement under each experimental condition based on the experimental results, and for example, the measurement under a combination of experimental conditions that differs only in the experimental condition that is not correlated can be omitted, thereby reducing the workload of the experimenter. As described above, according to the above-mentioned experimental support device 100 and experimental support system 1, it is possible to significantly reduce the number of times to go back and forth between the experimental notebook and the device, and to make a series of tasks in the experiment more efficient.

[0059] FIG. 4 shows an example in which measurement data is registered in a cell, and FIG. 5 shows an example in which measurement data and analysis data are registered in a cell. However, at least one of measurement data and analysis data may be registered in a cell, and as a result, at least one of measurement results and analysis results may be displayed in the cell. Therefore, only analysis data may be registered in a cell, or only analysis results may be displayed. Also, at least one of one measurement data and one analysis data may be registered in each cell. Therefore, multiple measurement data measured under the same experimental conditions may be registered in each cell, any measurement result of the multiple registered measurement data may be displayed in each cell, or multiple measurement results may be displayed in each cell. Also, multiple analysis data may be registered in each cell. Any analysis result of the multiple registered analysis data may be displayed in each cell, or multiple analysis results may be displayed in each cell, or one or more new analysis results calculated using multiple analysis results (for example, the average value, mode, median, maximum value, minimum value, etc. of multiple analysis results) may be displayed in each cell.

[0060] The processing in each step of the experiment support method shown in FIG. 5 will be described in more detail. FIG. 7 is a diagram illustrating a main screen 141. FIG. 8 is a flowchart showing an example of a condition setting process. FIG. 9 is a diagram for explaining a condition setting procedure. FIG. 10 is a diagram illustrating a main screen 141 on which a condition table TB, which is a two-condition matrix, is created. FIG. 11 is a diagram illustrating a main screen 141 on which a condition table TB, which is a condition list matrix, is created. Hereinafter, the condition setting process in step S11 in FIG. 5 will be described in more detail with reference to FIG. 7 to FIG. 11.

[0061] When the processor 110 of the experiment support device 100 executes an experiment support application program (hereinafter simply referred to as the program), a main screen 141 shown in Fig. 7 is displayed on the display device 140. The condition setting process shown in Fig. 8 is started, for example, when the experimenter presses a condition setting button (button B1) on the main screen 141.

[0062] When the process shown in FIG. 8 is started, the processor 110 first causes the display device 140 to display the condition setting screen 142 shown in FIG. 9 (step S21). After that, the processor 110 acquires the experimental conditions input by the experimenter to the condition setting screen 142 (step S22). As shown in FIG. 9, the experimenter can specify the number of conditions, which is the number of experimental conditions specified for each measurement data, on the condition setting screen 142. When the experimenter specifies the number of conditions on the condition setting screen 142, the processor 110 acquires the specified number of conditions. In addition, the experimenter can specify a condition name and a condition value in the input area 142a as shown in FIG. 9. When the experimenter specifies a condition name and a condition value in the input area 142a, the processor 110 acquires the specified condition name and condition value.

[0063] Then, processor 110 determines the specified number of conditions (step S23), creates a condition table in a format according to the number of conditions (steps S24, S25), and causes display device 140 to display the created table on main screen 141 (step S26).

[0064] Specifically, when the processor 110 determines in step S23 that the number of conditions is two, it creates a two-condition matrix table as a condition table (step S24) and causes the display device 140 to display the created two-condition matrix table on the main screen 141 (step S26). More specifically, when the processor 110 determines that the number of conditions is two, it creates two cells in the input area 142a for inputting condition names and a plurality of cells for inputting condition values ​​for each condition name, as shown in FIG. 9, and prompts the experimenter to input the condition names and condition values. Thereafter, when the experimenter inputs the condition names (temperature and humidity in FIG. 9) and the condition values ​​(temperature condition values ​​of 20, 25, and 30, and humidity condition values ​​of 70, 80, 83, and 86 in FIG. 9), the processor 110 creates a condition table TB, which is a two-condition matrix table, and causes the display device 140 to display the condition table TB on the main screen 141, as shown in FIG. 10.

[0065] The two-condition matrix table refers to a condition table in which, when one of two experimental conditions specified for each measurement data is the first experimental condition and the other is the second experimental condition, a set C1 of values ​​of the first experimental condition and a set C2 of values ​​of the second experimental condition are arranged so as to intersect with each other. Note that Fig. 10 shows an example in which the sets C1 and C2 are arranged so as to be perpendicular to each other.

[0066] In the two-conditions matrix table, it is preferable that the values ​​of the first experimental condition are arranged in order of the numerical value or the degree of the value of the first experimental condition, and it is preferable that the values ​​of the second experimental condition are arranged in order of the numerical value or the degree of the value of the second experimental condition. Note that Fig. 10 shows an example in which the values ​​of the first experimental condition (temperature) are arranged in ascending order of their numerical value (20, 25, 30), and the values ​​of the second experimental condition (humidity) are arranged in ascending order of their numerical value (70, 80, 83, 86).

[0067] On the other hand, when the processor 110 determines in step S23 that the number of conditions is other than 2, it creates a condition list matrix table (step S25) and causes the display device 140 to display the created condition list matrix table on the main screen 141 (step S26). More specifically, when the processor 110 determines that the number of conditions is other than 2, it creates cells in the input area 142a in the same number as the number of conditions in which condition names are input, and a plurality of cells in which condition values ​​are input for each condition name, and prompts the experimenter to input the condition name and the condition value. Thereafter, when the experimenter inputs the condition name (for example, temperature, humidity, and lighting) and the condition value (for example, 20, 25, and 30 as the temperature condition value, 70, 80, 83, and 86 as the humidity condition value, and “strong” and “weak” as the lighting condition value), the processor 110 creates a condition table TB, which is a condition list matrix table, and causes the display device 140 to display the condition table TB on the main screen 141 as shown in FIG. 11.

[0068] The condition list matrix table refers to a condition table in which the sets of values ​​of one or more experimental conditions specified for each measurement data are arranged so that they do not intersect with each other. Fig. 11 shows an example in which a set of values ​​C1 of the first experimental condition, a set of values ​​C2 of the second experimental condition, and a set of values ​​C3 of the third experimental condition are arranged in parallel.

[0069] In addition, in the condition list matrix, it is preferable that the values ​​of at least one of the one or more experimental conditions are arranged in order of the numerical value or degree of the value of at least one of the experimental conditions. Note that Fig. 11 shows an example in which the values ​​of the first experimental condition (temperature) are arranged in ascending numerical order (20, 25, 30).

[0070] Fig. 12 is a flow chart showing an example of the data registration process. Fig. 13 is a diagram showing an example of the data acquisition screen 143 before data acquisition. Fig. 14 is a diagram showing an example of the data acquisition screen 143 after data acquisition. The data registration process of step S12 in Fig. 5 will be described in further detail below with reference to Figs. 12 to 14.

[0071] The data registration process shown in Fig. 12 is started, for example, when an experimenter selects a cell in a condition table displayed on the main screen 141. More specifically, it is started by selecting a blank cell in the two-conditions matrix table shown in Fig. 10, or a blank cell in the conditions list matrix table shown in Fig. 11. Note that, before or after selecting a cell, the experimenter places a sample 206 that matches the selected cell or the experimental conditions corresponding to the selected cell on the XY stage 214 of the measuring device 200.

[0072] When the process shown in Fig. 12 is started, the processor 110 first causes the display device 140 to display the data acquisition screen 143 shown in Fig. 13 (step S31). The data acquisition screen 143 includes an area R1 for displaying an image based on image data acquired by the measuring device 200, an area R2 for displaying a map image and a current observation position, an area R3 for setting observation using the measuring device 200, and an area R4 for setting the data acquisition process to be performed after pressing the button B2.

[0073] 12, a live image is displayed in region R1. Region R3 shows a setting example in which the measuring device 200 acquires both non-confocal image data (color) and confocal image data (laser) using a 5x objective lens (zoom magnification 1x). Region R4 shows a setting example in which 3D data (laser extend image data, color extend image data, height image data) is automatically acquired for one area.

[0074] When the experimenter presses button B2 after making necessary settings on the data acquisition screen 143, the processor 110 acquires measurement data (step S32). Specifically, the processor 110 controls the measuring device 200, which measures the sample 206 under the control of the processor 110. The processor 110 then acquires the measurement data obtained by the measurement from the measuring device 200. More specifically, the measuring device 200 performs z-stack imaging to generate image data in each of a plurality of states in which the relative distance between the sample 206 and the objective lens 205 is different, and outputs a plurality of confocal image data and a plurality of non-confocal image data to the experiment support device 100 as measurement data. The experiment support device 100 acquires these image data as measurement data.

[0075] The processor 110, which has acquired the measurement data, names the file of the measurement data using the experimental conditions corresponding to the cell (step S33). For example, the processor 110 may name the file of the measurement data acquired under the experimental conditions of temperature 20 and humidity 70 as "temperature20_humidity70" and store it in the storage device 120.

[0076] Thereafter, the processor 110 causes the display device 140 to display the measurement results based on the measurement data stored in the storage device 120 on the data acquisition screen 143 (step S34). More specifically, the processor 110 causes the display device 140 to display the measurement results in an area R1 of the data acquisition screen 143, as shown in Fig. 14. Note that, although Fig. 14 shows an example in which a laser extend image is displayed three-dimensionally as the measurement result, the measurement result is not limited to this example. A color extend image or a height image may also be displayed as the measurement result.

[0077] The experimenter may check the displayed measurement results and select whether or not to perform analysis. If analysis is to be performed on the measurement data, the experimenter may, for example, press button B3 displayed on data acquisition screen 143. If analysis is not to be performed, the experimenter may observe sample 206 again and re-obtain measurement data.

[0078] Fig. 15 is a flow chart showing an example of the analysis process. Fig. 16 is a diagram showing an example of the analysis screen 144 before the analysis. Fig. 17 is a diagram showing an example of the analysis screen 144 after the analysis. Hereinafter, the analysis process of step S13 in Fig. 5 will be described in further detail with reference to Figs. 15 to 17.

[0079] 15 is started, for example, when an experimenter checks the measurement results displayed on the data acquisition screen 143 and issues an instruction to perform analysis. More specifically, it is started when the experimenter presses button B3 on the data acquisition screen 143 shown in FIG.

[0080] When the process shown in FIG. 15 is started, the processor 110 first causes the display device 140 to display the analysis screen 144 shown in FIG. 16 (step S41). In the analysis screen 144, a file F1 of measurement data to be analyzed is displayed together with its file name in the area on the left side of the screen. In addition, an image selected using thumbnails of various images (laser extend image D1, color extend image D2, height image D3, map image D4) displayed in the area on the right side of the screen is displayed in two-dimensional or three-dimensional display in area 144a in the center of the screen. Note that FIG. 16 shows an example in which the laser extend image D1 is displayed in three-dimensional display in area 144a.

[0081] Thereafter, the experimenter specifies an analysis method and a region of interest (ROI), and the processor 110 analyzes the measurement data (step S42). More specifically, the processor 110 analyzes the region of interest ROI specified on the image displayed in the area 144a using an analysis method selected by the experimenter from the analysis methods (Analysis A, Analysis B, Analysis C, Analysis D) displayed on the shortcut bar on the analysis screen 144, and generates analysis data.

[0082] The processor 110 that has generated the analysis data names the file of the analysis data using the experimental conditions when the measurement data was acquired (step S43). The processor 110 may name the file of the analysis data using the name of the analysis method in addition to the experimental conditions, and store the file in the storage device 120.

[0083] Thereafter, the processor 110 causes the display device 140 to display the analysis result on the analysis screen 144 based on the analysis data (step S44). More specifically, the processor 110 causes the display device 140 to display the analysis result RS near the region of interest ROI in the region 144a, as shown in Fig. 17. Note that Fig. 17 shows how the laser extend image is two-dimensionally displayed in the region 144a, the region of interest ROI is analyzed using the analysis method A, and the surface roughness parameters Sa (arithmetic mean height), Sz (maximum height), and Sq (root mean square height) are measured as the analysis result RS. That is, in this example, the analysis method A is a method of measuring surface roughness.

[0084] 17 illustrates surface roughness measurement as an example of an analysis method, but the analysis method performed by the processor 110 may include various measurements other than surface roughness measurement, such as width measurement, step (height) measurement, volume measurement, surface angle measurement, sphere measurement, etc. Furthermore, the analysis method may include profile measurement that measures the brightness or height along an arbitrary line on an image, difference analysis that measures the difference in height profile with a reference image, inter-surface step measurement that measures the step between multiple target regions (surfaces), planar measurement that measures the number or area of ​​a specific shape, particle analysis that measures an area extracted from an image by binarizing image data, etc.

[0085] 18 is a diagram for explaining a method for color-coding cells. Hereinafter, the color-coding process in step S14 in FIG. 5 will be described in further detail with reference to FIG.

[0086] When analysis data is generated by the analysis and the analysis result of the measurement data is determined, the processor 110 colors the cells in the condition table in which the measurement data and analysis data are registered, based on the analysis data. The method of color coding is not particularly limited, but for example, as shown in Fig. 18, a color may be assigned in advance to the value of the analysis data (analysis value), and a color corresponding to the analysis value may be assigned to the cell in the condition table.

[0087] 19 to 24 are diagrams showing examples of the main screen 141 after measurement and analysis, respectively. The display process of step S15 in FIG. 5 will be described in further detail below with reference to FIG. 19 to FIG.

[0088] When the measurement and analysis are completed, the processor 110 causes the display device 140 to display the main screen 141 in the foreground, and causes the measurement result MS1 to be displayed in the cell of the condition table TB selected in the data registration process of step S12 (for example, the cell corresponding to the experimental conditions of temperature 20 and humidity 70), as shown in FIG. 19. The results (measurement results, analysis results) displayed in the cells can be switched by operating the buttons displayed on the shortcut bar. FIG. 19 shows a state in which the measurement button is enabled, and as a result, the measurement results are displayed in the condition table TB. Note that the results displayed in the cells can be switched by any UI component, not limited to buttons, and may be switched by tab operation, for example.

[0089] Furthermore, when another cell (for example, a cell corresponding to the experimental conditions of temperature 25 and humidity 70) is selected and the measurement and analysis are completed, processor 110 displays the measurement result MS2 in the newly selected cell, as shown in FIG. 20. By repeating the selection, measurement, and analysis of cells in this manner, measurement results are added one by one to the cells in the condition table TB. This makes it possible to recognize at a glance the experimental conditions that have not been measured (for example, in the case where the condition table TB of FIG. 21 is displayed, the experimental conditions of temperature 25 and humidity 80).

[0090] Moreover, by simply operating the buttons on the shortcut bar, it is also possible to display a condition table TB in which analysis results are displayed in cells, as shown in Figures 22 and 23. Note that Figure 22 shows an example in which analysis results using analysis method A (for example, surface roughness measurement) are displayed in cells, and Figure 23 shows an example in which analysis results using analysis method D (for example, volume measurement) are displayed in cells.

[0091] By displaying the analysis results in a list in the condition table TB, the correlation between the experimental conditions and the experimental results can be understood simply by referring to the condition table TB. For example, by referring to the condition table TB shown in FIG. 22, it is possible to understand the tendency for surface roughness to increase depending on temperature. Also, by referring to the condition table TB shown in FIG. 23, it is possible to understand the tendency for volume to increase as the temperature and humidity increase. Also, by color-coding the cells according to the analysis results, it is possible to understand these trends at a glance, and this can greatly improve the work efficiency of the experimenter compared to the conventional method of examining things using a lab notebook.

[0092] 19 to 23 show examples in which a two-conditions matrix table is displayed as the condition table TB, but a condition list matrix table may be displayed as the condition table TB on the main screen 141 as shown in FIG. 24. When the condition list matrix table is displayed on the main screen 141, a two-conditions matrix button may be added to the shortcut bar. In the display using the condition list matrix table, the experimental results are arranged in one direction, so that it is possible to easily grasp the correlation between a specific experimental condition and the experimental result. In contrast, in the display using the two-conditions matrix table, the experimental results are arranged two-dimensionally, so that it is possible to easily grasp the correlation between two experimental conditions and the experimental result, and the experimental result can be evaluated more efficiently than in the display using the condition list matrix table.

[0093] When the experimenter presses the two-conditions matrix button, the processor 110 causes the display device 140 to display, for example, a two-conditions matrix setting screen 145 shown in Fig. 25. On the two-conditions matrix setting screen 145, the experimenter can select two experimental conditions constituting the two-conditions matrix table as selected conditions from among the multiple experimental conditions constituting the condition list matrix table, and further select conditions for fixing the values ​​of the remaining experimental conditions as fixed conditions. Note that Fig. 25 illustrates an example of a setting in which temperature and humidity are selected as selected conditions, and the lighting value, which is one of the remaining experimental conditions, is fixed to "high."

[0094] By executing the settings shown in Fig. 25, the processor 110 can create the two-conditions matrix table shown in Fig. 23 from the condition-list matrix table shown in Fig. 24, and change the condition table TB displayed on the display device 140 to the two-conditions matrix table. By displaying the two-conditions matrix table, the correlation between the experimental conditions and the experimental results can be more easily understood than when the condition-list matrix table is displayed. In addition, once the condition-list matrix table is created, the two-conditions matrix table can be created with a simple operation using any experimental condition included in the condition-list matrix table. Therefore, by switching the experimental conditions and displaying the two-conditions matrix tables corresponding to various combinations of experimental conditions, experimental conditions that are correlated with the experimental results can be found.

[0095] The above-mentioned embodiments are specific examples shown to facilitate understanding of the invention, and the present invention is not limited to these embodiments. Modifications of the above-mentioned embodiments and alternative forms that replace the above-mentioned embodiments may be included. That is, each embodiment can have its components modified within the scope of its purpose and scope. In addition, new embodiments can be implemented by appropriately combining multiple components disclosed in one or more embodiments. In addition, some components may be deleted from the components shown in each embodiment, or some components may be added to the components shown in the embodiment. Furthermore, the processing procedures shown in each embodiment may be performed in a different order as long as there is no contradiction. That is, the experiment support device, experiment support system, experiment support method, and program of the present invention can be variously modified and changed within the scope of the claims.

[0096] For example, in the above-described embodiment, an example was shown in which the experiment support device 100 performs the experiment support method using measurement data measured by the measuring device 200, which is an industrial microscope device, but the experiment support device 100 may use measurement data measured by other measuring devices. The measuring device may be, for example, a biological microscope device, a scanning probe microscope (SPM) such as a scanning tunnel microscope (STM) or an atomic force microscope (AFM), a white light interferometer, or the like. The measuring device may also be any imaging device, and may use, for example, measurement data measured by the measuring device 300, which is an imaging device that images a sample contained in a culture vessel.

[0097] Fig. 26 is a perspective view of the measuring device 300. Fig. 27 is a diagram illustrating an example of the configuration of the measuring device 300. Fig. 28 is a diagram illustrating an example of the configuration of the light source unit 304 and the photographing unit 305. The measuring device 300 shown in Fig. 26 may be used, for example, in a state in which it is placed in an incubator in order to photograph a sample without removing it from the incubator. Hereinafter, the configuration of the measuring device 300 will be described with reference to Figs. 26 to 28.

[0098] 26 and 27, the measuring device 300 is placed in an incubator with the culture vessel 10 placed on a transmission window 301 of the measuring device 300, and, for example, captures an image of the sample in the culture vessel 10 according to an instruction from the experiment support device 100 to generate image data. Note that the transmission window 301 is a transparent top plate that constitutes the upper surface of the housing 302 of the measuring device 300, and constitutes a mounting surface on which the culture vessel is placed. The transmission window 301 is made of, for example, glass or transparent resin.

[0099] 26, the measuring device 300 includes a box-shaped housing 302 having a transparent transmission window 301 on the upper surface in which the culture vessel 10 is placed, and a positioning member 20 that positions the culture vessel 10 at a predetermined position on the transmission window 301 (mounting surface). The positioning member 20 is fixed to the housing 302. However, the positioning member 20 can be removed as necessary, and may be replaced with another positioning member having a different shape depending on the vessel to be used.

[0100] As shown in Figs. 27 and 28, the measuring device 300 further includes a stage 303 that moves within a housing 302, a pair of light source units 304 that illuminate the sample, and an image capturing unit 305 that captures the sample. The stage 303, the light source unit 304, and the image capturing unit 305 are housed within the housing 302. The light source unit 304 and the image capturing unit 305 are installed on the stage 303, and move relative to the culture vessel 10 as the stage 303 moves within the housing 302. The stage 303 is movable in an X direction and a Y direction that are parallel to the transmission window 301 (mounting surface) and perpendicular to each other. However, the stage 303 may also move in a Z direction that is perpendicular to both the X direction and the Y direction.

[0101] 27 and 28 show an example in which the light source unit 304 and the photographing unit 305 are installed on the stage 303 and move together within the housing 302, but the light source unit 304 and the photographing unit 305 may move independently within the housing 302. Also, while an example in which a pair of light source units 304 are arranged on the left and right sides of the photographing unit 305 is shown in Fig. 27 and 28, the arrangement and number of the light source units 304 are not limited to this example. For example, three or more light source units 304 may be provided on the stage 303, or only one light source unit 304 may be provided.

[0102] 28, the light source unit 304 includes a light source 306 and a diffusion plate 307. The light source 306 includes, for example, a light emitting diode (LED). The light source 306 may include a white LED, or may include a plurality of LEDs that emit light of a plurality of different wavelengths, such as R (red), G (green), and B (blue). The light emitted from the light source 306 enters the diffusion plate 307.

[0103] The diffusion plate 307 diffuses the light emitted from the light source 306. The diffusion plate 307 is not particularly limited, but may be, for example, a frosted diffusion plate having an uneven surface. However, the diffusion plate 307 may be an opal diffusion plate having a coated surface, or may be another type of diffusion plate. Furthermore, a mask 307a may be formed on the diffusion plate 307 to limit the emission area of ​​the diffused light. The light emitted from the diffusion plate 307 travels in various directions.

[0104] As shown in FIG. 28, the photographing unit 305 includes an optical system 308 and an image sensor 309. The optical system 308 collects light that has passed through the transmission window 301 and entered the housing 302. The optical system 308 is not particularly limited, but may be, for example, a finite correction type objective lens that forms an image at a finite position. However, the optical system 308 may include an infinity correction type objective lens, and the optical system 308 as a whole may constitute a finite correction optical system. The optical system 308 focuses on the bottom surface of the culture vessel 10 in which the sample is present, and collects light that has entered the housing 302 onto the image sensor 309, forming an optical image of the sample on the image sensor 309.

[0105] The imaging element 309 is an optical sensor that converts detected light into an electrical signal. The imaging element 309 is specifically an image sensor, and is not particularly limited, but may be, for example, a CCD (Charge-Coupled Device) image sensor or a CMOS (Complementary MOS) image sensor.

[0106] In the measuring device 300 configured as above, oblique illumination is adopted to visualize the sample in the culture vessel 10, which is a phase object. Specifically, the light emitted by the light source 306 is diffused by the diffusion plate 307 and emitted outside the housing 302 without passing through the optical system 308. That is, the light source unit 304 emits light traveling in various directions toward the outside of the housing 302 without passing through the optical system 308. Then, a part of the light emitted outside the housing 302 is reflected, for example, by the upper surface of the culture vessel 10, and is deflected above the sample, and further, a part of the light deflected above the sample is irradiated on the sample and enters the housing 302 by passing through the sample and the transmission window 301. Then, a part of the light entering the housing 302 is collected by the optical system 308 to form an image of the sample on the image sensor 309. That is, the optical system 308 collects light that has passed through the transparent window 301 and entered the housing 302, in order to form an image of the sample in the culture vessel 10 placed on the transparent window 301 on the image sensor 309. Finally, the measuring device 300 generates image data of the sample based on the electrical signal output from the image sensor 309, and outputs the image data to the experiment support device 100 as measurement data.

[0107] The experiment support device 100 may perform the above-mentioned experiment support method based on the measurement data acquired from the measurement device 300. When an experiment is performed using the measurement device 300, the experiment conditions are not particularly limited, but examples thereof include the frequency of medium exchange, the type of medium, the number of passages of cell culture, the culture time, the temperature, the CO2 concentration, and the O2 concentration. The analysis method is not particularly limited, but examples thereof include a method for measuring the number of cells, the cell density, the number of colonies, the growth rate, the number of divisions, the colony area, and the colony height.

[0108] In the above-described embodiment, an example was shown in which a sample was manually placed in the measurement device according to a selected cell in the condition table and then measured, but the sample may be placed automatically according to the selection of the cell. For example, samples according to various experimental conditions may be stored in advance, and a sample according to a cell selected by an experimenter may be transported to the measurement device by a transport device. In this case, the transport device may identify a sample according to the experimental conditions based on identification information attached to a container that contains the sample. The identification information may be, for example, a one-dimensional code such as a barcode, or a two-dimensional code such as a QR code (registered trademark).

[0109] The transport device may also sequentially place samples corresponding to various experimental conditions on the measurement device, and the measurement device may sequentially measure the samples transported by the transport device to generate measurement data. The measurement device may specify experimental conditions corresponding to the samples using identification codes attached to the sample containers at the time of measurement, and may output the specified experimental conditions together with the measurement data to the experiment support device. In this case, the experiment support device may automatically register the measurement data and analysis data in the cells of the condition table without the experimenter selecting a cell after creating a condition table based on the experimental conditions output from the measurement device.

[0110] In this specification, the expression "based on A" does not mean "based only on A", but means "based at least on A" and further means "based at least partially on A". That is, "based on A" may be based on B in addition to A, or may be based on a part of A.

[0111] As used herein, the terms "first," "second," and the like, modifying a noun do not limit the quantity or order of the elements described by the noun. These terms are used to distinguish between two or more elements, not less, not more. Thus, the specification of a "first" and a "second" element does not imply that the "first" element precedes the "second" element, nor does it negate the presence of a "third" element. [Explanation of symbols]

[0112] 1. Experiment Support System 100 ···Experimental support equipment 110 Processor 120...Storage device 121 Program 140...Display device 200, 300, 400...Measuring device 206 Sample C1, C2: Experimental conditions C2 Experimental conditions MS1, MS2: Measurement results RS...Analysis results TB...Condition table

Claims

1. one or more non-transitory computer readable media containing instructions; one or more processors for executing said instructions; the instructions are configured to cause the one or more processors to perform an operation; The operation includes: displaying, on the display device, a condition table showing the experimental conditions under which the measurement should be performed in response to the input of the experimental conditions; In response to input of measurement data acquired using a measurement device under experimental conditions corresponding to a cell of the condition table, displaying at least one of a measurement result based on the measurement data or an analysis result of the measurement data in the cell on the display device. An experiment support device characterized by:

2. 2. The experiment support device according to claim 1, The display device displaying at least one of the measurement result and the analysis result in the cell includes updating the display of the condition table on the display device every time the measurement data acquired using the measurement device is input. An experiment support device characterized by:

3. The experiment support device according to claim 1 or 2, Displaying the condition table on the display device includes creating the condition table in a format corresponding to the number of conditions, which is the number of the experimental conditions specified for each of the measurement data. An experiment support device characterized by:

4. 4. The experiment support device according to claim 3, When the number of conditions is two, displaying the condition table on the display device includes arranging a set of values ​​of a first experimental condition specified for each of the measurement data and a set of values ​​of a second experimental condition specified for each of the measurement data so as to intersect with each other. An experiment support device characterized by:

5. The experiment support device according to claim 4, Displaying the condition table on the display device includes: The values ​​of the first experimental conditions are arranged in the table of conditions in order of the numerical value or degree of the values ​​of the first experimental conditions; The values ​​of the second experimental conditions are arranged in the table of conditions in order of the numerical value or degree of the values ​​of the second experimental conditions. An experiment support device characterized by:

6. 4. The experiment support device according to claim 3, When the number of conditions is other than two, displaying the condition table on the display device includes arranging sets of values ​​of one or more experimental conditions specified for each of the measurement data so that they do not intersect with each other. An experiment support device characterized by:

7. 7. The experiment support device according to claim 6, Displaying the condition table on the display device includes arranging values ​​of at least one experimental condition among the one or more experimental conditions in the condition table in order of numerical value or degree of the value of the at least one experimental condition. An experiment support device characterized by:

8. The experiment support device according to any one of claims 1 to 7, The operations further include analyzing the measurement data using one or more specified analysis methods to generate analysis data indicative of the analysis results; Displaying at least one of the measurement result and the analysis result in the cell on the display device includes displaying the analysis result in the cell on the display device. An experiment support device characterized by:

9. 9. The experiment support device according to claim 8, The operations further include coloring one or more cells in the condition table that display the analysis results based on the analysis data. An experiment support device characterized by:

10. The experiment support device according to any one of claims 1 to 9, The operation further includes: naming a file of the measurement data acquired using the measurement device under an experimental condition corresponding to a cell of the condition table, using the experimental condition when the measurement data was acquired. An experiment support device characterized by:

11. An experiment support device according to any one of claims 1 to 10, A measuring device that outputs the measurement data to the experiment support device. An experiment support system characterized by:

12. The experiment support system according to claim 11, The measuring device includes a microscope device for acquiring image data of a sample. An experiment support system characterized by:

13. The experiment support system according to claim 12, The microscope device includes a laser scanning microscope device. An experiment support system characterized by:

14. Displaying a condition table showing the experimental conditions under which measurements should be performed in response to input of the experimental conditions; In response to input of measurement data acquired using a measurement device under experimental conditions corresponding to a cell of the condition table, displaying at least one of a measurement result based on the measurement data or an analysis result of the measurement data in the cell.

13. An experiment support method comprising:

15. displaying, on the display device, a condition table showing the experimental conditions under which measurements should be performed in response to the input of the experimental conditions; In response to input of measurement data acquired by using a measurement device under experimental conditions corresponding to a cell of the condition table, at least one of a measurement result based on the measurement data and an analysis result of the measurement data is displayed on the display device in the cell. A program that causes a computer to execute a process.

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