Colony counting device, control method, and program

Abstract

To mitigate burden on a user regarding counting colonies.SOLUTION: A colony counting device includes: an acquisition section that acquires an image of colonies generated in a test individual; and an execution section that executes first software, the execution section executing processing of counting the number of the colonies from the image of the colonies. The execution section reads a user file that holds information in a matrix format, the user file being created by second software different from the first software, in order to count the colonies generated in the test individual or to manage a count result of the colonies. Furthermore, the execution section creates a count table to be used to count the colonies based on the user file.SELECTED DRAWING: Figure 18

Description

[Technical Field]

[0001] The present invention relates to a colony counting device, a control method, and a program. [Background technology]

[0002] Food manufacturing factories use colony counters to inspect whether products are contaminated with bacteria. Inspectors form a culture medium in a petri dish, place a food sample in the culture medium, and culture it in an incubator or the like for a predetermined period of time. After that, the inspector removes the petri dish from the incubator and counts the colonies (bacterial colonies) using the colony counter. Thus, the counting accuracy of the colony counter is important for food hygiene management. Patent Document 1 proposes counting the number of colonies from petri dish images acquired by a camera. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-171334 Summary of the Invention [Problem to be solved by the invention]

[0004] Users typically create an inspection list and count table using commonly available spreadsheet software, print them out on paper, and then, referring to the inspection list, cultivate fungi in the medium for each test individual (sample name) and count the colonies produced by the fungi visually or using a colony counter. Furthermore, users handwrite the colony count results in the count table. Then, users open the original count table in spreadsheet software and manually input the count results from the paper count table into an electronic file. This process is prone to transcription errors, placing a heavy burden on users.

[0005] On the other hand, if count tables were created using a colony counter that can display electronic count tables, the workload of transcription would be reduced. In this case, users would have to become familiar with the colony counter's user interface to create count tables, which was a barrier to introducing colony counters. In such cases, if users could create count tables for colony counters using spreadsheet software that they are familiar with, the barrier to introducing colony counters would be lowered.

[0006] Therefore, an object of the present invention is to reduce the burden on users regarding colony counting. [Means for solving the problem]

[0007] The present invention is, for example, an acquisition unit for acquiring an image of a colony occurring on the specimen; an execution unit that executes first software and executes a process of counting the number of colonies from the image of the colonies; The execution unit: a reading unit that reads a user file that holds information in a matrix format and that is created by second software different from the first software in order to count the colonies that occur in the test individual or to manage the colony count results; a creation unit that creates a count table used for counting the colonies based on the user file; The present invention provides a colony counting device having: [Effects of the Invention]

[0008] According to the present invention, the burden on the user regarding colony counting is reduced. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing a colony counting device. [Figure 2] FIG. 2 is a diagram illustrating the electrical configuration of a head device. [Figure 3] FIG. 2 is a diagram illustrating the electrical configuration of a control device. [Figure 4] A diagram explaining the user interface (UI). [Figure 5] A diagram illustrating the UI for creating a count table from a sample database. [Figure 6] A diagram explaining the UI for creating a new count table. [Figure 7] A diagram explaining a spreadsheet. [Figure 8] A diagram illustrating the UI for adding a column element. [Figure 9] A diagram explaining the UI during inspection. [Figure 10] A diagram explaining the UI when instructing a count. [Figure 11] A diagram explaining the UI when registering count results in a cell. [Figure 12] FIG. 10 is a diagram illustrating a UI for automatically identifying a target cell. [Figure 13] FIG. 10 is a diagram illustrating a UI for resetting counting conditions. [Figure 14] 10 is a flowchart showing a process executed by a PC. [Figure 15] 10 is a flowchart showing editing of a sample database. [Figure 16] 1 is a flowchart illustrating a colony counting method. [Figure 17] A diagram explaining business files. [Figure 18] A diagram explaining the configuration file. [Figure 19] FIG. 1 is a diagram explaining the function of each cell. [Figure 20] FIG. 10 is a diagram illustrating a count table. [Figure 21] FIG. 10 is a diagram illustrating a count table. [Figure 22] FIG. 10 is a diagram illustrating reflection of counting results. [Figure 23] FIG. 10 is a diagram for explaining how to handle blank cells. [Figure 24] FIG. 10 is a diagram illustrating a petri dish having multiple storage areas. [Figure 25]FIG. 10 is a diagram illustrating a setting file for a petri dish having multiple storage areas. [Figure 26] A diagram explaining how to refer to the inspection settings included in the sample DB. [Figure 27] FIG. 10 is a diagram illustrating tags related to averaging processing. [Figure 28] FIG. 10 is a diagram illustrating a method for converting a configuration file into a count table without using tags. [Figure 29] A diagram explaining customizing inspection settings. [Figure 30] 10 is a flowchart showing a method for creating a count table. [Figure 31] 10 is a flowchart showing a method for acquiring an inspection column setting. [Figure 32] 10 is a flowchart showing a method for obtaining inspection settings. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, the embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the invention as claimed, and not all combinations of features described in the embodiments are necessarily essential to the invention. Two or more of the features described in the embodiments may be arbitrarily combined. Furthermore, the same reference numerals are used for the same or similar components, and redundant explanations will be omitted.

[0011] Example 1 [Colony counting device] 1 shows a colony counting device 1. The colony counting device 1 includes a head device 1a and a control device (personal computer (PC)) 1b, which will be described later. The head device 1a and the PC 1b may be connected by wire using, for example, a universal serial bus (USB) cable, or may be connected wirelessly.

[0012] The head device 1a has an upper unit 2, a support unit 3, and a lower unit 4. A camera and a lighting device are provided inside the head device 1a. The support unit 3 is located between the upper unit 2 and the lower unit 4 and supports the upper unit 2. A stage 5 is provided on the top surface of the lower unit 4. The stage 5 is provided with a transparent window 6 on which a petri dish 15 is placed and a positioning member 7 for positioning the petri dish 15 at the center of the transparent window 6. An operation unit 8 and a front camera 10 are provided on the front of the lower unit 4. The operation unit 8 includes multiple switches (e.g., a first hardware button 8a, a second hardware button 8b, and a third hardware button 8c) for the user to input instructions. The front camera 10 is optional and reads, for example, two-dimensional symbols (barcodes). The front camera 10 is located in a recess 4a provided on the front of the housing of the head device 1. A power switch 9 is provided on the side of the lower unit 4.

[0013] FIG. 2 shows the electrical configuration of the head device 1a. The MCU 20 is a processor that executes a control program 27 stored in the storage device 25 and controls the head device 1a in accordance with the control program 27. Note that MCU is an abbreviation for microcontroller unit. The MCU 20 controls the main camera 11 and the front camera 10 via the imaging control unit 21 to acquire various image data. The imaging control unit 21 controls, for example, the exposure time of the main camera 11. The MCU 20 turns on and off the ring illumination devices 12 and 13 and the coaxial illumination device 14 via the illumination control unit 22. The illumination control unit 22 controls the driving power supplied to the ring illumination devices 12 and 13 and the coaxial illumination device 14. The MCU 20 accepts user input from the operation unit 8 via the operation acceptance unit 23. The operation acceptance unit 23 includes an input circuit that generates a signal indicating the state of the switch unit of the operation unit 8. The communication circuit 24 is a circuit that communicates with the PC 1b shown in FIG. 3 via a communication cable 26. The communication circuit 24 may include a wireless communication circuit and a LAN interface circuit. LAN is an abbreviation for local area network. The communication cable 26 may be, for example, a USB cable. The storage device 25 includes, for example, a read-only memory (ROM) that stores a control program 27 and a random access memory (RAM) used as a work area. The storage device 25 may store, for example, inspection conditions 28 set by the PC 1b and inspection images 29 acquired by the main camera 11. The inspection conditions 28 may include, for example, lighting conditions, imaging conditions, and counting conditions. The inspection image 29 is an image of a petri dish 15 containing a culture medium and a sample.

[0014] FIG. 3 shows a PC 1b that controls the head device 1a. The MCU 30 is a processor that executes programs stored in a storage device 35 and controls the PC 1b and the head device 1a in accordance with the programs. The MCU 30 accepts user instructions from a keyboard 32 and a pointing device 33 connected to an input / output circuit 31. The MCU 30 controls a printer 38 connected to the input / output circuit 31 to print tables and other data on paper. The MCU 30 displays various information on a display device 37 via a display control unit 36, such as a graphics board. The communication circuit 34 communicates with the head device 1a via the communication cable 26. The communication circuit 34 may include a wireless communication circuit and a LAN interface circuit. The storage device 35 includes, for example, a read-only memory (ROM) that stores programs and a random access memory (RAM) used as a work area. The storage device 35 may also include a hard disk drive (HDD) and a solid-state drive (SSD). The storage device 35 may store an application program 39, inspection conditions 28, inspection images 29, a sample DB 40, a count table 55, and the like. DB is an abbreviation for database. The application program 39 is responsible for, for example, creating and editing the sample DB 40 and the count table 55 and controlling the head device 1. The inspection conditions 28 are set by the MCU 30 in accordance with the application program 39. The inspection images 29 are received from the head device 1. The sample DB 40 is a database referenced when creating the count table 55. The count table 55 is a table in which a plurality of cells are arranged in an array, and includes row elements and column elements.

[0015] The communication circuit 34 of the PC 1b may perform wireless communication with a terminal device 1c such as a smartphone or tablet terminal. The terminal device 1c may display a count table 55 or an inspection list created from the count table 55. The inspection list includes the petri dish number, sample name, bacterial species, culture medium, dilution ratio, incubation time, etc., and is referred to when the user prepares the specimen for inspection in the petri dish 15.

[0016] The spreadsheet program 41 is an optional, widely used spreadsheet software. The business file 200 and the setting file 210 created by the spreadsheet program 41 will be described in detail in the second embodiment.

[0017] [Inspection Procedure] The general testing procedure is as follows: (1) The user handwrites an inspection list. The inspection list contains multiple lines, and each line can contain information such as the petri dish number, bacterial species, dilution ratio, count, and comments (such as the sample name). The petri dish number is identification information assigned in advance according to a predetermined rule to identify culture conditions such as the type of medium and dilution ratio. (2) The user writes numbers on the lids of the petri dishes according to the inspection list, or writes numbers that have been written on the petri dishes in advance into the inspection list. (3) The user prepares the medium according to the dilution ratio written in the test list. If the dilution ratio is not written in the test list, the user writes the actual dilution ratio in the test list. (4) The user pours (mixes) the sample into the culture medium of each petri dish. The user writes the sample name in the comment field of the test list. (5) The user places the petri dish into the incubator. (6) After a predetermined time has elapsed, the user removes the petri dish from the incubator and counts the number of colonies. For example, the user looks through the bottom of the petri dish and marks the colonies with an oil-based pen to indicate that they have been counted. The number of colonies is then written into the inspection list. Alternatively, the user may count the number of colonies for each bacterial species while visually checking the bacterial species. In this case, the user writes the number of colonies for each bacterial species for each petri dish into the inspection list. (7) The user starts up the PC and reads the numbers and characters written on the inspection list and enters them into the spreadsheet software. The number of colonies is tallied using the spreadsheet software's macro function.

[0018] As described above, in conventional inspection procedures, inspection lists are created by hand, which is a very tedious task for users. Furthermore, if there is an input error when transferring the values written on the inspection list to a spreadsheet, the total results may also be incorrect. Even if the number of colonies could be automatically obtained using a colony counter, the conventional method still requires handwriting the inspection list, writing the colony counts onto the inspection list, and transferring the inspection list to the spreadsheet, which means there is a possibility of input and data errors.

[0019] Therefore, in this embodiment, we propose creating an electronic inspection list using PC 1b, counting colonies according to the electronic inspection list, directly inputting the count results into the electronic inspection list, and tallying the input numbers. This will reduce the user's burden in post-processing the colony count results. Furthermore, since the user's handwriting or manual input is reduced, input errors will also be reduced and inspection accuracy will be improved.

[0020] [Creating an inspection list (count table)] 4 shows the UI 50 of the counting application program displayed on the display device 37 of the PC 1b. The counting application program is stored in the storage device 35 and executed by the MCU 30. The UI 50 has buttons, links, tabs, and the like for switching between multiple functions of the counting application program.

[0021] The UI 50 has a table creation area 51 and a DB display area 61. DB is an abbreviation for database. The table creation area 51 displays at least a count table 55. A title display section 52 accepts input from the keyboard 32 of a title (name) given to the count table 55 and displays it. A button 53 is a button for switching between performing / not performing counting for each cell. A button 54 is a button for instructing to add a column to the count table 55. An averaging setting section 56 has a checkbox for instructing whether to average the count results, and a selection section for the number of count values to be averaged (= number of count repetitions).

[0022] The DB display area 61 displays a list of pre-registered count item templates (e.g., sample DB 40). Here, a count item corresponds to one row in the count table 55. Count items are usually distinguished by the name of the object to be inspected (sample name). The name display section 62 displays the name of the pre-registered template (sample name). The indicator 63 is an object that visually displays a classification tag associated with a sample name. A classification tag is a tag that indicates a classification defined by the user (e.g., staple food, prepared dish, dessert). For example, the indicator 63 may represent different classification tags by different colors. The indicator 63 may represent different classification tags by different shapes. The button 67 is a button for expanding and displaying one or more sub-items that have a parent-child relationship with a certain sample name. A parent-child relationship refers to the relationship between a certain sample and multiple ingredients that make up that sample. For example, if a sandwich is the parent, the ingredients that make up the sandwich (e.g., ham, lettuce, and egg) are the children. Button 64 is a button for instructing that the corresponding template be added to count table 55. By preparing sample DB 40 in advance in this way, the user can easily create count table 55.

[0023] In the example shown in FIG. 4, when the user presses the button 64 associated with sandwich, the MCU 30 adds a row to the count table 55, displays "1" as the ID in the ID display cell of the added row, and displays "sandwich" in the cell displaying the sample name in the added row. "ID" is an abbreviation for identification information. That is, the ID and sample name are set for each row, and are "settings for each row." Furthermore, the MCU 30 reads the sandwich test conditions registered in the sample DB 40 from the storage device 35, adds a new column to the count table 55, and displays the read test conditions in the new column. In this example, the test conditions include the bacterial species (e.g., viable bacteria / E. coli), the dilution ratio of the culture medium, and the incubation time of the sample. Each column includes, for example, a bacterial species cell, a dilution ratio cell, an incubation time cell, and a count value cell. That is, the bacterial species, dilution ratio, and incubation time are set for each column, and are "settings for each column." In this example, the test has not yet been performed and the count value has not yet been obtained, so nothing is entered in the count value cell. The first test item for sandwich testing is to use a medium with a dilution ratio of 100 for general viable bacteria and an incubation time of 48 hours. The second test item for sandwich testing is to use a medium with a dilution ratio of 1000 for general viable bacteria and an incubation time of 48 hours. In this way, the MCU 30 adds columns according to the number of test items.

[0024] In FIG. 5, when the user presses the button 64 associated with kimchi, the MCU 30 reads the kimchi inspection conditions registered in the sample DB 40 from the storage device 35 and adds the rows and columns corresponding to the read inspection conditions to the count table 55.

[0025] In this example, kimchi has two test items. The first test item for kimchi is to test for general viable bacteria using a 100x dilution medium and an incubation time of 48 hours. This is the same as the first test item for sandwich. Therefore, the MCU 30 discards the first test item included in the kimchi template and does not add it as a new column. The second test item for kimchi is to test for E. coli using a 100x dilution medium and an incubation time of 24 hours. The MCU 30 adds this as a new column to the count table 55.

[0026] Note that sandwiches are not tested for E. coli, so the text or image indicating "not tested" may be displayed in the cell for the count value. Similarly, kimchi is not tested for general viable bacteria using a 1000x dilution medium, so the text or image indicating "not tested" may be displayed in the cell for the count value.

[0027] Note that counting can also be performed or not performed by operating the count inversion button 53. When the count inversion button 53 is operated with a cell corresponding to E. coli selected for a sandwich, the MCU 30 may be able to switch between displaying a character or image indicating "not tested" and leaving the field blank for inputting the count result.

[0028] As shown in Figures 4 and 5, a search box 65 and a tag search refinement button 66 may be added. If the number of templates registered in the sample DB 40 increases, the DB display area 61 may be unable to display all of the templates at once. Therefore, the MCU 30 may search and extract templates from the storage device 35 based on the characters entered in the search box 65, and display the search results in the DB display area 61. Furthermore, when the tag search refinement button 66 is pressed, the MCU 30 may display only sample products filtered by the specified classification tag. For example, the same classification tag may be assigned to multiple sample products. In this case, multiple sample products assigned the selected classification tag are added to the count table 55.

[0029] 6 shows the UI 50 when creating a new count table. For example, the MCU 30 can run spreadsheet software in parallel with the application program 39.

[0030] 7 shows a sheet 70 of spreadsheet software. The MCU 30 receives an instruction to copy and paste the sheet 70 or a group of cells selected in the spreadsheet software to the UI 50. In this way, the MCU 30 may create the count table 55 shown in FIG.

[0031] FIG. 8 shows a dialog box 90 for adding a column. When a button 54 on the UI 50 is pressed, the MCU 30 displays the dialog box 90 on the display device 37. The item name setting unit 91 accepts input of the name of the bacterial species, which is the column's item name. The column type setting unit 92 accepts setting of whether the column type is a count column or a free column. A count column is a column containing cells into which count values are input. A free column is a column into which the user can freely input text, images, and other information, such as notes and comments. The dilution ratio setting unit 93 accepts input of the dilution ratio. The incubation time setting unit 94 accepts input of the incubation time. The algorithm setting unit 95 accepts settings for image processing to be applied to the inspection image. The residue removal mode is a mode that reduces residue (e.g., dust, dirt, handwriting) attached to the petri dish 15 or the like through image processing. The rapid mode is a mode that emphasizes rapid result confirmation and is a mode that inspects petri dishes 15 that have been incubated for a shorter incubation time than conventional methods with high sensitivity. The culture medium type setting unit 96 accepts the selection of the type of culture medium (e.g., general viable bacteria (white), general viable bacteria (black)), etc. When the list button 96a is pressed, the MCU 30 may read candidate culture medium types from the storage device 35, create a list, and display it on the display device 37. The count setting unit 97 accepts settings such as the shooting conditions of the main camera 11 (e.g., exposure time), lighting type (e.g., brightness, lighting device), display processing type, and image processing type. In other words, the bacterial species, dilution ratio, culture time, algorithm setting, culture medium type, or count setting accepted in the dialog 90 is set for each column as the default setting.

[0032] [Counting process] FIG. 9 shows a UI 100 displayed on the display device 37 of PC 1b while PC 1b controls the head device 1a to perform a counting process. The count table area 101 displays the count table 55 edited through the UI 50. The result area 102 displays an inspection image 103 acquired by the main camera 11 of the head device 1a. The inspection image 103 may be a moving image or a still image. Generally, when adjusting the exposure time of the main camera 11, selecting the brightness of the ring illumination devices 12 and 13 and the coaxial illumination device 14, selecting the light-emitting elements to be turned on, selecting image processing, and the like, the MCU 30 acquires a moving image from the main camera 11 and displays it in the result area 102. When performing a counting process, the MCU 30 acquires a still image from the main camera 11 and displays it in the result area 102.

[0033] The check box 106 is a control object for selecting whether or not to display the count result in the count value area 104. The first software button 105a is a button having the same function as the first hardware button 8a. The second software button 105b is a button having the same function as the second hardware button 8b. In this example, the first software button 105a is assigned the instruction to take a picture (shoot button). The second software button 105b is assigned the instruction to register (register button). In FIG. 9, the second software button 105b is shown with a dashed line, which means that it cannot be operated.

[0034] The user selects a cell corresponding to the Petri dish 15 placed on the stage 5 from among the multiple cells included in the count table displayed in the count table region 101 by clicking the cell with the pointer 57. As shown in FIG. 9, the cell selected by the pointer 57 may be highlighted to indicate which cell was selected by the user. Each cell is associated with inspection conditions (such as sensitivity for binarizing colonies, type of illumination device, and brightness) and stored in the storage device 35. The MCU 30 reads the inspection conditions associated with the selected cell from the storage device 35 and transmits them to the head device 1a. The MCU 20 of the head device 1a controls the main camera 11, ring illumination devices 12 and 13, and coaxial illumination device 14 according to the received inspection conditions, acquires an image, and transmits it to the PC 1b. When another cell is selected, the MCU 30 reads the inspection conditions associated with the selected cell from the storage device 35 and transmits them to the head device 1a. The MCU 20 of the head device 1a controls the main camera 11, ring illumination devices 12 and 13, and coaxial illumination device 14 according to the received inspection conditions, acquires images, and transmits them to the PC 1b. In this way, the user can change the inspection conditions by selecting a cell.

[0035] 10 shows a UI 100 that the MCU 30 displays on the display device 37 when the first software button 105a or the first hardware button 8a, which is a photographing button, is pressed. An image 103 (still image) of the petri dish 15 is displayed in the result area 102. The MCU 30 assigns the first software button 105a from the photographing button to a button that instructs counting (count button).

[0036] FIG. 11 shows a UI 100 that the MCU 30 displays on the display device 37 when the first software button 105a or the first hardware button 8a, which is a count button, is pressed. When the count button is pressed, the MCU 30 instructs the head device 1a to count colonies. The MCU 20 of the head device 1a counts colonies in accordance with the count instruction and transmits the count value to the PC 1b. Note that the counting process may be performed by the MCU 30. The MCU 30 displays the count value in the count value area 104. In this case, the MCU 30 may convert the count value into CFU / mL (the number of colonies per unit volume (milliliter)) and display it in the count value area 104. For example, each time the count value area 104 is clicked with the pointer 57, the MCU 30 may switch the display between the count value only, CFU / mL only, and the count value + CFU / mL. Note that CFU is an abbreviation for colony-forming unit. Furthermore, when the count value is acquired, the MCU 30 reassigns the first software button 105a from the count button to the photograph button, and changes the second software button 105b and the second hardware button 8b, which are assigned as registered buttons, from an inoperable state to an operable state.

[0037] FIG. 12 shows a state in which the registration button is pressed. The MCU 30 may write a count value to the currently selected cell and change the next cell to the selected cell (cell of interest). In this example, the cell of interest (active cell) is changed from the cell in the first row to the cell in the second row. In this way, the MCU 30 automatically selects the next cell, thereby reducing the burden on the user. The MCU 30 also changes the second software button 105b and second hardware button 8b assigned to the registration button from an operable state to an inoperable state.

[0038] The UI 100 shown in Fig. 12 has a change menu 109 for changing the display target of the cell. In Fig. 12, "Count" is selected in the change menu 109, so "100" is displayed in the cell.

[0039] 13 shows a UI 100 that the MCU 30 displays on the display device 37 when a cell in which a count value has been entered is double-clicked. The setting screen 120 includes control objects for adjusting parameters related to the colony detection algorithm among the inspection conditions associated with the cell selected by double-clicking. The slide bar 121 is a control object for setting, for example, a threshold for removing small particles by image processing. The slide bar 122 is a control object for adjusting the colony detection sensitivity.

[0040] The MCU 30 may superimpose marks such as circles on the portions detected as colonies in the image 103 displayed in the result area 102. Since the MCU 30 changes the algorithm in response to adjustments made to the slide bars 121 and 122, the positions and number of marks indicating colonies also change. This will make it easier for the user to find the appropriate adjustment amount.

[0041] [flowchart] (1) Main processing of PC1b 14 is a flowchart showing a series of processes executed by the MCU 30 of the PC 1b. The MCU 30 executes the following processes in accordance with a count application program stored in the storage device 35.

[0042] In step S1, the MCU 30 edits the count table. As described with reference to FIGS. 4 to 8, the count table is edited or created through the UI 50.

[0043] In S2, the MCU 30 stores the count table in the storage device 35.

[0044] In S3, the MCU 30 identifies the count table. Identification of the count table may be performed using the front camera 10 and an inspection list or a user authentication tag, or may be performed using a file dialog.

[0045] In S4, the MCU 30 reads the specified count table from the storage device 35. As a result, the UI 100 shown in FIG.

[0046] In S5, the MCU 30 specifies a cell into which the count value is to be written. Initially, a cell in the top row in the count table may be selected, or a cell clicked with the pointer 57 may be selected.

[0047] In S6, the MCU 30 identifies the test conditions associated with the active cell. For example, the MCU 30 reads the test conditions associated with each cell from the storage device 35 when creating the count table.

[0048] In S7, the MCU 30 sets the inspection conditions associated with the active cell to the head device 1a. As described above, the MCU 30 transmits the sensitivity of the main camera 11, the lighting devices to be turned on, the brightness, the number of light-emitting elements to be turned on (illumination direction), image processing (HDR, ring removal), counting algorithm (parameters such as thresholds), etc. to the head device 1a.

[0049] In S8, the MCU 30 determines whether the inspection conditions have changed. As described above, the inspection conditions associated with a cell can be changed at any time, even during inspection. Therefore, if the inspection conditions have been changed, the MCU 30 returns to S7 and transmits the changed inspection conditions to the head device 1a. If the inspection conditions have not been changed, the MCU 30 proceeds to S9.

[0050] In S9, the MCU 30 determines whether a shooting instruction has been input by the user. The user can issue a shooting instruction by pressing the first hardware button 8a of the head device 1a or the first software button 105a of the UI 100. If a shooting instruction has not been input, the MCU 30 returns from S9 to S8. If a shooting instruction has been input, the MCU 30 proceeds from S9 to S10.

[0051] In S10, the MCU 30 transmits an image capture instruction to the head device 1a.

[0052] In S11, the MCU 30 acquires an image (inspection image) of the petri dish image 103 acquired by the main camera 11 from the head device 1a, and displays the inspection image in the result area 102 of the UI 100.

[0053] In S12, the MCU 30 determines whether a count instruction has been input. The user can input a count instruction by pressing the first hardware button 8a of the head device 1a or the first software button 105a of the UI 100, which is assigned as the count button. If a count instruction has not been input, the MCU 30 returns from S12 to S8. If a count instruction has been input, the MCU 30 proceeds from S12 to S13.

[0054] In S13, the MCU 30 transmits a count instruction to the head device 1a. When the counting process is executed by the PC 1b, the MCU 30 executes the counting process instead of the MCU 20.

[0055] In S14, the MCU 30 receives the count result from the head device 1a and displays the count result in the count value area 104. When the MCU 30 executes the count process in S14, the MCU 30 displays the count result obtained by executing the count process in the count value area 104.

[0056] In S15, the MCU 30 determines whether the inspection conditions, such as image processing and counting algorithm, have changed. If the inspection conditions have changed, the process returns to S13. If the inspection conditions have not changed, the MCU 30 proceeds to S16. Note that the change in inspection conditions in S8 is assumed to be a change in inspection conditions that requires re-acquisition of images. The change in inspection conditions in S15 is assumed to result in a change in image processing for the acquired images, but does not require re-acquisition of images.

[0057] In S16, the MCU 30 determines whether a registration instruction has been input by the user. The user can input a registration instruction by pressing the second hardware button 8b of the head device 1a or the second software button 105b of the UI 100, which is assigned as the registration button. If a registration instruction has not been input, the MCU 30 returns from S16 to S8, and performs reshooting or changes the inspection conditions. If a registration instruction has been input, the MCU 30 proceeds from S16 to S17.

[0058] In S17, the MCU 30 registers the count result in the active cell.

[0059] In S18, the MCU 30 determines whether all counting has been completed. For example, if counting results have been entered into all cells in the count table, the MCU 30 determines that counting has been completed. If there are still cells that have not been entered, the MCU 30 proceeds from S18 to S5 and changes the active cell to the next cell (cell identification).

[0060] (3) Registering the sample database A count table has multiple rows and columns, and each cell is associated with an inspection condition. Count tables and inspection lists may be created daily. However, inspections may be performed on the same sample every day. Therefore, by registering frequently inspected samples in the sample DB 40 in advance, the burden of creating a count table can be reduced. Therefore, when creating a sample table, the user may register row elements corresponding to each sample in the sample DB 40.

[0061] 15 is a flowchart showing the process of editing the sample DB 40 executed by the MCU 30 of the PC 1b. The MCU 30 executes the following process in accordance with the application program 39 stored in the storage device 35.

[0062] In S41, the MCU 30 accepts a selection of a row element from among a plurality of row elements included in the count table that the user wishes to register in the sample DB 40. For example, the MCU 30 may accept a click with the pointer 57 on any of the row elements included in the sample table.

[0063] In S42, the MCU 30 receives an instruction to add the selected line element. For example, the instruction to add may be input when a right click is performed with the pointer 57 while the line element is selected.

[0064] In S43, the MCU 30 acquires the sample name of the row element instructed to be added and determines whether the same sample name is already registered in the sample DB 40 (duplication determination). If the row element instructed to be added does not already exist, the MCU 30 proceeds from S43 to S45. If the row element instructed to be added exists in the sample DB 40, the MCU 30 proceeds from S43 to S44.

[0065] In S44, the MCU 30 inquires of the user whether or not to overwrite the row element in the sample DB 40. If a cancel instruction is input, the MCU 30 cancels the addition of the row element. If an overwrite instruction is input, the MCU 30 proceeds from S44 to S45.

[0066] In S45, the MCU 30 acquires the item names (for example, sample name, bacterial species, medium type, dilution ratio) that constitute the row element to be added.

[0067] In S46, the MCU 30 obtains from the storage device 35 the check conditions associated with the cells of the row elements.

[0068] In S47, the MCU 30 registers the item name and the inspection conditions in the sample DB 40.

[0069] In S48, the MCU 30 updates the display of the sample DB 40 in the UI 50.

[0070] (6) Colony counting 16 shows the colony counting process executed by the MCU 20 of the head device 1a in accordance with a control program, although the image processing and counting process may be executed by the MCU 30.

[0071] In S81, the MCU 20 acquires the counting algorithm from the inspection conditions received from the PC 1b. Specifically, image processing and threshold parameters (e.g., binarization threshold) used in the counting algorithm are acquired.

[0072] In S82, the MCU 20 applies a counting algorithm to the inspection image acquired by the main camera 11. For example, image processing such as HDR or ring removal is applied to the inspection image.

[0073] In S83, the MCU 20 counts the colonies included in the inspection image according to the inspection conditions (threshold parameters).

[0074] <Example 2> Incidentally, some users create inspection lists and count tables using commonly available spreadsheet software (spreadsheet program 41). Such users may be required to install the colony counting device 1 and transition to an environment where inspection lists and count tables are created using application program 39. In this case, the user may wish to reuse the inspection lists and count tables created using commonly available spreadsheet software as assets. Alternatively, the user may wish to continue creating inspection lists and count tables, or the setting files that serve as the basis for them, using commonly available spreadsheet software.

[0075] Therefore, in the second embodiment, a function for converting a user file (setting file) created by a commonly used spreadsheet software into an examination list or a count table is proposed.

[0076] (1) Procedure (i) The user creates an inspection list using a spreadsheet software they use. If an inspection list has already been created, this step is skipped. The format of the electronic file of the inspection list can be CSV format, Microsoft Excel (registered trademark) format, or the like.

[0077] (ii) The user uses spreadsheet software to reuse the inspection list and create a setting file for the list to be read into the colony counting device 1. For example, the user uses the spreadsheet software to add cells to the inspection list and write tag information in the added cells. The user saves the inspection list with embedded tag information from the spreadsheet software as a setting file.

[0078] (iii) PC 1b performs colony counting according to the setting file or by converting the setting file into a count table for colony counting device 1.

[0079] (2) User files created by spreadsheet software (2-1) Business file (inspection list and count sheet) FIG. 17 shows a business file 200 created by a user using a spreadsheet program 41. This business file 200 was used as an inspection list and count table, or simply as a count table. The leftmost column contains the name of the sample. The second column contains the date and time the sample was manufactured. The third column contains the information that a white medium was used for the general viable bacteria, with a dilution ratio of 1:10. The fourth column contains the information that a white medium was used for the general viable bacteria, with a dilution ratio of 1:100. The fifth column contains the information that a white medium was used for the general viable bacteria, with a dilution ratio of 1:1000. The sixth column contains the information that a dark medium was used for the coliform bacteria, with a dilution ratio of 1:10. The seventh column contains the information that a dilution ratio for Staphylococcus aureus was 1:10. The eighth column contains lot information indicating the manufacturing lot. The ninth column contains comments (remarks).

[0080] It has been common for users to print out such business files 200 on paper using a printer and use them as an inspection list and count table.

[0081] (2-2) User files (setting files) created by spreadsheet software 18 shows a settings file 210 that a user creates using a spreadsheet program 41. The settings file 210 is created by the user using the spreadsheet program 41 to add tags and character strings to a business file 200. For example, the user may create the settings file 210 by copying and renaming the business file 200. In this case, both the business file 200 and the settings file 210 are maintained in the storage device 35.

[0082] The [START] tag is a tag that defines the start position of the column (column element) and row (row element) required to create the count table 55 in the configuration file 210. The start position is expressed as cell coordinates and may be expressed, for example, as (start column, start row). The tag is a tag that defines the end position of the column and row required to create the count table 55 in the configuration file 210. The end position is expressed as cell coordinates and may be expressed, for example, as (end column, end row).

[0083] The [DATE] tag indicates that this is a column in which date and time information such as the date and time of manufacture is written. The [COUNT] tag indicates that this is a column containing count cells in which colony count results are entered. In Figure 18, the first row from the top and the two cells corresponding to the fourth and fifth columns from the left are blank. This is an abbreviation that means that the tags follow the tags of the cells to the left of the relevant cells. In other words, the [COUNT] tag indicates that the fourth and fifth columns also contain count cells. The [COMMENT] tag indicates that this is a column in which the user can freely enter text.

[0084] The [MEDIUMTYPE] tag indicates the type of culture medium and the name of the test setting. The test setting information indicates various parameters (e.g., imaging conditions, image processing conditions) set in the colony counter 1. The [FAVORRITES] tag indicates the name of a test setting that the user has previously registered as a favorite among multiple test settings. The [NAME] tag indicates the name of a column (e.g., the name of the bacterium) displayed in the count table 55. The [EARLY] tag indicates whether the rapid mode is enabled. The rapid mode is a mode in which counts are performed at the end of the legally required incubation period and at a shorter interval. The rapid mode has the advantage of being able to identify samples that should be discarded and reproduced during a long incubation period. The [DILUTION] tag indicates the dilution ratio. The [ON] tag indicates that counts should be performed using the default test settings or that the rapid mode is enabled. For example, in Figure 18, the [ON] tag is written in the sandwich set row. This means that the test setting named by the [MEDIUMTYPE] tag ("General Viable Bacteria [Background: White]") should be applied to that count cell. "General Viable Bacteria [Background: White]" is linked to General Viable Bacteria Setting 1. If you look at the third column, instead of the [ON] tag, for Omelette Rice, the name of the test setting, "General Viable Bacteria Setting 2", is entered as a string. This indicates that "General Viable Bacteria Setting 2" should be applied instead of "General Viable Bacteria [Background: White]" (i.e., the default test setting, General Viable Bacteria Setting 1).

[0085] There is no description in the column for the dilution ratio 1:100 for Omurice, which suggests that counting for the dilution ratio 1:100 is not performed for Omurice.

[0086] As shown in FIG. 18, when colony counts are performed for multiple culture conditions or bacterial species for one sample name, a [COUNT] tag is written in each corresponding column.

[0087] FIG. 19 is a diagram illustrating the cell group in the setting file 210. As shown in FIG.

[0088] The cell group CG1 consists of one or more cells in which the identification information (sample name) of the specimen to be inspected is written.

[0089] Cell group CG2 includes a cell with a [DILUTION] tag and one or more cells with the actual dilution ratio. Cell group CG2 maintains the culture conditions, so it may also include cell groups CG4 and CG5.

[0090] Cell group CG3 consists of cells corresponding to each count cell in count table 55. Each cell of cell group CG3 contains an [ON] tag indicating that counting should be performed with the default test settings, an arbitrary character string indicating that counting should be performed with the test settings specified by the written character string, or a blank (null character) indicating that counting should not be performed.

[0091] Cell group CG4 consists of a cell with the [MEDIUMTYPE] tag and a cell with a string indicating the name of the default test setting. A blank cell in cell group CG4 indicates that the test setting in the cell to the right is valid.

[0092] Cell group CG5 consists of cells with the [FAVORITES] tag and cells with the name of the favorite test setting entered. A blank cell in cell group CG5 indicates that the default test setting specified by the [MEDIUMTYPE] tag is valid.

[0093] (3) Count table FIG. 20 shows that the count table 55 created by converting or analyzing the setting file 210 is displayed in the count table area 101. Comparing the setting file 210 illustrated in FIG. 18 with the count table 55 illustrated in FIG. 20, it can be seen that the positional relationship between the cells is basically maintained in both cases. The MCU 30 stores and maintains the relationship between the cells in the setting file 210 and the corresponding cells in the count table 55 in the storage device 35. Furthermore, among the cells in the count table 55, the count cell 224 is associated with an inspection setting. The MCU 30 identifies an inspection setting based on the tag information of the cell in the setting file 210 and associates the identified inspection setting with the corresponding count cell 224.

[0094] 18 and the count table 55 illustrated in FIG. 20, the MCU 30 copies the sample names written in the cell group CG1 of the setting file 210 to the sample name column in the count table 55. The MCU 30 also copies the production date and time written in the cell specified by the [DATE] tag in the setting file 210 to the production date and time column in the count table 55.

[0095] The MCU 30 also copies the dilution factor described in the cell group CG2 identified by the [DILUTION] tag directly to the row of the dilution factor in the count table 55. The MCU 30 also copies the column name specified by the [NAME] tag to the row in the count table 55 that holds the column name.

[0096] The MCU 30 divides the column for which the quick mode is enabled by the [EARLY] tag and the [ON] tag into two columns. The first column 227 stores the first count result (e.g., at 24 hours). The second column 228 stores the second count result (e.g., at 48 hours).

[0097] The MCU 30 provides count cells 224, 226 in the count table 55 so as to correspond to each cell of the cell group CG3 in the setting file 210. Here, the MCU 30 may display an icon 225 for confirming or editing the inspection setting associated with the count cell 224 in the count cell 224 where counting should be performed. The icon 225 is clicked, for example, with the pointer 57. The MCU 30 grays out the count cells 226 where counting is not performed.

[0098] In this way, in the second embodiment, the user can create the business file 200 and the setting file 210 using the spreadsheet program 41 that he or she normally uses. Furthermore, the MCU 30 can convert the setting file 210 into a count table 55 for the colony counting device 1 according to a conversion or import function installed in the application program 39. This reduces the burden of creating the count table 55.

[0099] (4) Other examples of count tables FIG. 21 shows another example of a count table 55 created from the configuration file 210. In the count table 55 shown in FIG. 20, multiple count cells 224, 226 are arranged in one row for one sample name. However, this is merely an example. As shown in FIG. 21, a row in which the count results are input may be created for each combination of sample name and dilution factor. In FIG. 21, if there are three combinations of sample name and dilution factor, the number of rows in which the count results are input is also three. In this way, the cell arrangement in the configuration file 210 does not have to match the cell arrangement in the count table 55.

[0100] (5) Reflecting the count results from the count table to the configuration file 22 shows the procedure for reflecting count results entered into count cells 224a, 224b, and 224c of count table 55 in configuration file 210 and business file 200 in colony counting device 1. MCU 30 stores in storage device 35 the relationships between count cells 224a and 224b in count table 55, corresponding cells 237a, 237b, and 237c in configuration file 210, and corresponding cells 238a, 238b, and 238c in business file 200. For example, storage device 35 stores inter-cell relationship information indicating that count cells 224a, 237a, and 238a are a group of cells related to each other. Similarly, storage device 35 stores inter-cell relationship information indicating that count cells 224b, 237b, and 238b are a group of cells related to each other. Furthermore, the storage device 35 also stores inter-cell relationship information indicating that the count cells 224c, 237c, and 238c are interrelated cell groups. The MCU 30 references these relationships and reflects the count results from the count table 55 to the setting file 210 and the business file 200. That is, the count results input to the count cells 224a, 224b, and 224c are reflected in the cells 237a, 237b, and 237c and the cells 238a, 238b, and 238c, respectively. Here, the example in which the count results are reflected in the setting file 210 has been described. However, this is merely an example. The MCU 30 may output the count results as a new file in a format conforming to the data structure stored in the application.

[0101] Incidentally, both the settings file 210 and the business file 200 are created using a spreadsheet program 41. Spreadsheet programs 41, such as Microsoft Excel (registered trademark), have a cell reference function. For example, cell 238a in the business file 200 may be written to reference cell 237a in the settings file 210 (e.g., =[settings file.xlsx]worksheet name!cell coordinates). As a result, the count results copied from the count table 55 to the settings file 210 may also be input into the business file 200.

[0102] (6) Allowing blank rows (blank cells) FIG. 23 shows the process of converting a settings file 210 in which there is a blank cell in the cell group CG1 that holds sample names into a count table 55. A user may create a new settings file 210 by copying a previously created settings file 210. Normally, the number of samples to be inspected is fixed, but occasionally some samples may become out of stock and be excluded from inspection. In this case, it would be convenient for the user if the out-of-stock samples could be easily excluded from inspection.

[0103] 23, the user deletes the names of samples to be excluded from inspection, leaving them blank. At this time, the contents of inspection-specified cells such as cell group CG3 do not need to be deleted. When MCU 30 analyzes configuration file 210 and finds a blank cell in cell group CG1, it ignores all inspection-specified cells in the same row (blank line) as the blank cell and creates count table 55.

[0104] 23, count rows (rows including count cells) corresponding to blank rows identical to blank cells in cell group CG1 in configuration file 210 are not provided in count table 55. As a result, in count table 55, the count row for salad bowl is placed next to the count row for sandwich set, and the count row for omelet sandwich is placed below the count row for omelet rice.

[0105] In this way, the MCU 30 creates the count table 55 while ignoring blank cells in accordance with the conversion function of the application program 39. This makes it easy to exclude some samples that are out of stock from inspection, which is convenient for the user.

[0106] Note that even if the text in the inspection specification cell remains, it is simply ignored, which is advantageous when production of some samples that were out of stock is resumed, because the inspection settings for that sample name can be restored (the text in the inspection specification cell is made valid) simply by writing the sample name back into the blank cell.

[0107] (7) Dividing the Petri Dish Users may use a Petri dish that is divided into multiple compartments by dividing walls, which is useful for obtaining multiple counts of the same sample under different incubation conditions (e.g., dilution ratios).

[0108] 24 illustrates a petri dish 15 divided into M (e.g., M=4) effective areas 231 to 234 by dividing walls. In this case, the MCU 30 must divide the effective area to be counted in the image of the petri dish 15 into M areas and perform counting for each of the M effective areas. The setting work for making the colony counting device 1 perform this was complicated and difficult for the user.

[0109] FIG. 25 illustrates a method for specifying customized test settings for each sample. In this example, cell group CG3 contains the following strings: "upper left detection," "lower left detection," "upper right detection," and "lower right detection," which indicate the names of test settings previously registered as favorites. When the MCU 30 scans the setting file 210 and finds a test specification cell in cell group CG3 that contains a string indicating the name of the test setting, it associates the name of the test setting with the corresponding count cell 224 in the count table 55. When the user presses the icon 225 displayed in that count cell 224, the MCU 30 reads the test setting from the storage device 35 based on the name of the test setting associated with that count cell 224, applies it to the colony counting device 1, and executes counting. By creating test settings with the names "upper left detection," "lower left detection," "upper right detection," and "lower right detection" in advance, the user can easily create a count table 55 for tests using a Petri dish 15 divided into four effective areas 231-234.

[0110] In this way, any character string specifying the name of the inspection setting may be written in the inspection specification cell of cell group CG3. That is, the user may directly write the name of the inspection setting in each inspection specification cell, not just for the divided Petri dishes 15. For example, the user may store multiple inspection settings in advance in the storage device 35, each with different combinations of binarization sensitivity, desired threshold for small particles, degree of shape division, degree of lint removal, sample information (e.g., medium type, Petri dish diameter, name of microorganism, amount of sample liquid), and photography settings (e.g., lighting setting, brightness setting, anti-glare enabled / disabled, high-resolution enabled / disabled, etc.), and write the names of those inspection settings in the inspection specification cells. This allows the inspection setting to be linked to the count cell 224.

[0111] (8) Reference the sample database A user may wish to always associate the same test setting with a sample of the same name. As described above, if the user remembers the name of a specific test setting, the user can simply enter that name in the test specification cell. However, it would be difficult to memorize the names of all test settings. Meanwhile, in the sample DB 40, test settings are associated with sample names. Therefore, it would be convenient for the user if the test settings stored in the sample DB 40 for each sample name could be associated with the count cell 224 via the setting file 210.

[0112] FIG. 26 is a diagram illustrating the [SAMPLEDB] tag. The [SAMPLEDB] tag can be written in an examination specification cell. When the MCU 30 finds the [SAMPLEDB] tag while scanning the configuration file 210, it references the sample DB 40 based on the sample name in the row where the [SAMPLEDB] tag exists, and associates the examination configuration (the name of the examination configuration) associated with the sample name with the examination specification cell in which the [SAMPLEDB] tag is written. More specifically, the MCU 30 associates the examination configuration stored in the sample DB 40 with the count cell 224 in the count table 55 corresponding to the examination specification cell. This allows the user to associate the examination configuration with the count cell 224 even if they do not memorize the name of the specific examination configuration associated with the sample name.

[0113] (9) Manufacturing date and lot number 18 and other figures, a [COMMENT] tag is provided in the second embodiment. The reason for this will be explained below.

[0114] A user may wish to distinguish between multiple samples with the same sample name by the manufacturing date and time or lot number. For example, a user may want to collectively describe the context (e.g., manufacturing date and time or lot number) when performing a series of tests in a column called "comments" in count table 55. Generally, information must be entered for each petri dish in the comment column. Therefore, it has not been easy for a user to efficiently enter the context information they manage into the comment column.

[0115] Therefore, in the second embodiment, column information according to the context is allowed to be added to the setting file 210. This allows the addition of the type of data desired by the user for each sample.

[0116] For the manufacturing date and time, a [DATE] tag is provided specifically for the date and time attribute. The [DATE] tag means that the input character string is treated as date and time information (date and time attribute). The [DATE] tag also makes it possible to search using the manufacturing date and time as a key. Furthermore, when exporting the count results to a spreadsheet file managed by the spreadsheet program 41, the MCU 30 may assign a time attribute to the manufacturing date and time column in the spreadsheet file. This will make data management easier for the user.

[0117] The [COMMENT] tag is a tag for realizing a comment column in the count table 55. In Fig. 18, for example, by using the [NAME] tag in addition, the name "Lot" can be given to the comment column. The MCU 30 may recognize the character string "Lot" as an attribute indicating a lot number or the like.

[0118] As shown in Figure 18, by using the [COMMENT] tag and [DATE] tag, not only test settings such as dilution ratio but also the sample lot and manufacturing date and time can be reflected in the count table 55 and can be managed by the application program 39.

[0119] (10) Averaging process It may be desirable to culture fungi in multiple petri dishes 15 using the same test settings (e.g., bacterial species, dilution ratio) for the same test object, obtain count results for each of the multiple petri dishes 15, and then average the multiple count results. Therefore, in Example 2, the [REPEAT: n] tag is employed. When the MCU 30 finds a [REPEAT: n] tag while scanning the settings file 210, it recognizes that the same test settings will be applied and n counts will be performed, and places n count rows to which the same test settings are applied in the count table 55.

[0120] FIG. 27 shows the conversion result (count table 55) of the configuration file 210 in which the [REPEAT:n] tag is written. In this example, the [REPEAT:2] tag is written, and the MCU 30 recognizes that two counts will be performed for the sample names "onigiri" and "taiyaki" using the default test settings (general viable bacteria [background: white]) and the average of the results will be calculated. The MCU 30 places three count cells each for "onigiri" and "taiyaki" in the count table 55. The first count cell stores the result of the first count. The second count cell stores the result of the second count. The third count cell stores the average of the first and second count results.

[0121] In this way, when the MCU 30 finds a [REPEAT: n] tag while scanning the configuration file 210, it places n count rows for the sample names written above the cell with the [REPEAT: n] tag in the cell group CG1 in the count table 55. In addition, the MCU 30 also places a count row in the count table 55 for storing the average value.

[0122] As illustrated in FIG. 27, the MCU 30 may place a count column to indicate names such as first time, second time, and average value between the column storing the sample name and the column storing the count result.

[0123] (11) Configuration file without tags In the above-described setting file 210, the MCU 30 reads tags such as [START], , [COUNT], and [COMMENT] to create the count table 55 and associates a predetermined test setting with the count cell 224. However, in the second embodiment, the tags may be omitted.

[0124] 28 shows a method for creating a count table 55 from an untagged configuration file 210. The storage device 35 stores conversion rules in advance. For example, the conversion rules state that a sample name is entered in column A, that a test setting name is entered in the first row, that a fungus name is entered in the third row, and that a dilution factor is entered in the fifth row. The conversion rules also include instructions to copy the sample name entered in column A to the sample name column in the count table 55, to associate the test setting identified by the name in the first row with a count cell in the count table 55, to copy the character string entered in the third row to the fungus name cell in the count table 55, and to copy the character string entered in the fifth row to the dilution factor cell in the count table 55.

[0125] In this way, the conversion rules have rules indicating to which cell of coordinates in the count table 55 a character string described in a cell of specific coordinates in the setting file 210 should be copied. Furthermore, the conversion rules also have rules indicating that an inspection setting identified by a character string described in a cell of specific coordinates in the setting file 210 should be linked to the corresponding count cell 224 in the count table 55. The MCU 30 scans the cells in the setting file 210 in accordance with the conversion rules, interprets the character string described in the cell of specific coordinates in accordance with the conversion rules, and reflects it in the count table 55.

[0126] In this way, by storing the conversion rules in advance in the storage device 35, the MCU 30 can convert the setting file 210 into the count table 55 without using tags. Alternatively, it can be said that the user needs to be familiar with the conversion rules and then input character strings in accordance with the conversion rules into predetermined cells in the setting file 210.

[0127] (12) Customizing some of the inspection settings In FIG. 18, the test configuration is specified by a combination of the [ON] tag and the [MEDIUMTYPE] tag, or by using the [FAVORITES] tag, the [SAMPLEDB] tag, or by directly entering the test configuration name. However, this is merely an example. The contents of the test configuration may be directly written in the test specification cell. For example, if a default test configuration has J parameters, all J parameters may be written in the test specification cell. This means that the default test configuration is not actually used. Alternatively, K parameters out of J parameters may be written in the test specification cell (J>K>=1). In this case, the default test configuration is applied to JK parameters out of J parameters, and the test configuration written in the test specification cell is applied to the K parameters. In other words, it is possible to customize part of the default test configuration.

[0128] FIG. 29 shows an example of a settings file 210 that allows customization of some or all of the default inspection settings. In this example, the sensitivity setting value and the small particle removal threshold are directly written in the inspection specification cell for the sample named "Sausage." That is, of the inspection setting named "General Viable Bacteria [Background: White]" specified by the [MEDIUMTYPE] tag, only the sensitivity and the small particle removal threshold are customized to the values specified in the inspection specification cell. The image brightness is directly written in the inspection specification cell for the sample named "Frozen Pizza." That is, of the inspection setting named "General Viable Bacteria [Background: White]" specified by the [MEDIUMTYPE] tag, only the image brightness is customized to the value specified in the inspection specification cell.

[0129] In this way, by directly writing the inspection parameters in the inspection specification cell, it is possible to customize some or all of the default inspection settings.

[0130] (13) Flowchart (13-1) Main flowchart FIG. 30 shows the process of converting a settings file 210 created by a user using a spreadsheet program 41 into a count table 55 by an application program 39.

[0131] In S91, the MCU 30 reads the setting file 210 from the storage device 35. The setting file 210 may be specified through a UI such as a file dialog. The MCU 30 functions as a file reading unit.

[0132] In S92, the MCU 30 searches for the [START] tag in the setting file 210 and sets the coordinates of the cell in which the [START] tag is written as the start coordinates of the conversion process. In this way, the MCU 30 functions as a tag search unit and a start coordinate setting unit.

[0133] In S93, the MCU 30 searches for an tag in the setting file 210 and sets the coordinates of the cell in which the tag is written as the end coordinates of the conversion process. In this way, the MCU 30 functions as a tag search unit and an end coordinate setting unit.

[0134] In S94, the MCU 30 starts scanning from the cell with the [START] tag to the right and searches for a cell with any tag written in. In this way, the MCU 30 functions as a cell scanning unit and a tag searching unit.

[0135] In S95, the MCU 30 acquires the inspection column setting corresponding to the discovered tag. Here, the inspection column setting is an information set (e.g., column name, etc.) required to set the corresponding column in the count table 55. According to FIG. 18, the [DATE] tag, [COUNT] tag, and [COUNT] tag are discovered. Details of S95 will be described later with reference to FIG. 31. In this way, the MCU 30 functions as an acquisition unit that acquires the inspection column setting.

[0136] In S96, the MCU 30 determines whether the scanning position has reached the end column (the column where the tag is written). If the scanning position is not the end column, the MCU 30 returns to S94, moves the scanning position one column to the right, and searches for a tag. When the scanning position has reached the end column, the MCU 30 proceeds from S96 to S97. In this way, the MCU 30 functions as a determination unit.

[0137] In S97, the MCU 30 starts scanning downward from the cell in which the [START] tag is written, and searches for a cell in which any tag or sample name is written.

[0138] In S98, the MCU 30 acquires the inspection settings for each sample. Details of S98 will be described later with reference to Fig. 32. In this way, the MCU 30 functions as an inspection setting acquisition unit.

[0139] In S99, the MCU 30 determines whether the scanning position has reached the end row (the row where the tag is written). If the scanning position is not the end row, the MCU 30 returns to S97, moves the scanning position down by one column, and searches for a tag. When the scanning position has reached the end column, the MCU 30 proceeds from S96 to S97.

[0140] In S100, when the MCU 30 finds the [REPEAT] tag, it reflects the averaging setting in the count table 55. In this way, the MCU 30 functions as a tag reflecting section or an averaging setting reflecting section.

[0141] (13-2) Sub-flowchart FIG. 31 shows the details of S95.

[0142] In S101, the MCU 30 determines whether the [COUNT] tag is found. If the [COUNT] tag is found, the MCU 30 proceeds from S101 to S102. Note that if the cell to the right of the cell containing the [COUNT] tag is blank, the MCU 30 also proceeds to S102.

[0143] In S102, the MCU30 recognizes the column containing the cell with the [COUNT] tag as a count execution column, and obtains the test column settings (e.g., the name of the default test setting, the column name (the name of the bacterial species), the dilution ratio, and other test settings) from the column.

[0144] In S103, the MCU 30 reflects the acquired test column settings in the count table 55.

[0145] If the found tag is not a [COUNT] tag in S101, the MCU 30 proceeds from S101 to S104.

[0146] In S104, the MCU 30 determines whether the found tag is a [DATE] tag. If a [DATE] tag is found, the MCU 30 proceeds from S104 to S105.

[0147] In S105, the MCU 30 recognizes the column containing the cell with the [DATE] tag as a column for managing the manufacturing date and time. Then, the MCU 30 proceeds from S105 to S103, and reflects the column for managing the manufacturing date and time in the count table 55. For example, the manufacturing date and time written in the column is copied to the corresponding column in the count table 55.

[0148] If the found tag is not a [DATE] tag in S104, the MCU 30 proceeds from S104 to S106.

[0149] In S106, the MCU 30 determines whether the found tag is a [COMMENT] tag. If a [COMMENT] tag is found, the MCU 30 proceeds from S106 to S107.

[0150] In S107, the MCU 30 recognizes the column containing the cell in which the [COMMENT] tag is written as a comment column and acquires the character string written in that column (e.g., lot, comment column name).The MCU 30 then proceeds from S106 to S103 and reflects the comment column in the count table 55. For example, the MCU 30 copies the character string acquired from the comment column of the configuration file 210 (e.g., column name such as lot) to the corresponding column in the count table 55.

[0151] (13-3) Sub-flowchart FIG. 32 shows the details of S98.

[0152] In S111, the MCU 30 obtains the names of the samples from the setting file 210. Note that blank cells are skipped.

[0153] In S112, the MCU 30 determines the column type. If the tag indicating the column type is a [COUNT] tag, the MCU 30 proceeds from S112 to S113.

[0154] In S113, the MCU 30 searches for the dilution factor, for example, from the cell at the intersection of the [COUNT] tag or a blank cell and the [DILUTION] tag.

[0155] In S114, the MCU 30 moves downward from the cell of the dilution ratio and branches the process depending on the value of the cell: If the value of the cell is [ON], the MCU 30 proceeds from S114 to S115.

[0156] In S115, the MCU 30 recognizes the cell with the [ON] tag as a count cell (inspection-specified cell) and associates the default inspection setting specified by the [MEDIUMTYPE] tag with the cell. As a result, the default inspection setting is associated with the count cell in the count table 55 that corresponds to the inspection-specified cell in the setting file 210. In this way, the MCU 30 functions as an associating unit.

[0157] In S116, it is determined whether or not the search for the dilution factor is complete. If multiple dilution factors exist for one sample name, the MCU 30 returns from S116 to S113.

[0158] If the cell value is an arbitrary character string in S114, the MCU 30 proceeds from S114 to S119.

[0159] In S119, the MCU 30 recognizes the cell as an inspection-specified cell and associates the inspection setting indicated by the character string written in the inspection-specified cell with the count cell 224 corresponding to the inspection-specified cell. As a result, the inspection setting specified by the name in the inspection-specified cell in the setting file 210 is associated with the count cell 224 in the count table 55 corresponding to the inspection-specified cell. Thereafter, the MCU 30 proceeds from S119 to S116.

[0160] If the value of the cell is [SAMPLEDB] in S114, the MCU 30 proceeds from S114 to S120.

[0161] In S120, the MCU 30 recognizes the cell as an inspection-designated cell, acquires the inspection setting corresponding to the sample name from the sample DB 40, and links the acquired inspection setting to the count cell 224 corresponding to the inspection-designated cell. As a result, the inspection setting acquired from the sample DB 40 based on the sample name is linked to the count cell 224 in the count table 55 corresponding to the inspection-designated cell. The MCU 30 then proceeds from S120 to S116.

[0162] If the value of the cell is blank in S114, the MCU 30 proceeds from S114 to S121.

[0163] In S121, the MCU 30 recognizes the cell as a non-count cell. For example, the MCU 30 may gray out the non-count cell 226 in the count table 55 that corresponds to the blank test-designated cell. The MCU 30 then proceeds from S121 to S116.

[0164] If it is determined in S112 that the tag indicating the column type is a [DATE] tag, the MCU 30 proceeds from S112 to S117.

[0165] In S117, the MCU 30 obtains the value of the cell as date and time information, and copies the date and time information to the corresponding count cell 224 in the count table 55. After that, the MCU 30 proceeds from S117 to S116.

[0166] If it is determined in S112 that the tag indicating the column type is a [COMMENT] tag, the MCU 30 proceeds from S112 to S118.

[0167] In S118, the MCU 30 obtains the value of the cell as comment information, and copies the comment information to the corresponding count cell 224 in the count table 55. After that, the MCU 30 proceeds from S118 to S116.

[0168] <Summary> [Point 1] The head device 1a is an example of an acquisition unit that acquires images of colonies occurring on the specimen under inspection. The MCU 30 may function as an acquisition unit by reading a colony image file designated by a user. The MCU 30 is an execution unit that executes first software (e.g., application program 39) and functions as an execution unit that executes a process for counting the number of colonies from the colony image. The MCU 30 functions as a reading unit that reads a user file (e.g., setting file 210) that holds information in a matrix format and is created by second software (e.g., spreadsheet program 4) different from the first software in order to count colonies occurring on the specimen under inspection or to manage the results of the colony counting. Furthermore, the MCU 30 functions as a creation unit that creates a count table 55 used for colony counting based on the user file. In this way, by converting the setting file 210 created by a spreadsheet program 41 different from the application program 39 that controls the colony counting device 1 into the count table 55, the burden on the user for creating the count table 55 is reduced. This reduces the burden on the user regarding colony counting. [Point 2] The storage device 35 functions as a storage means for storing multiple test settings (e.g., general viable bacteria [white background], general viable bacteria - setting 2, coliform bacteria - dark medium) to be applied to the test specimen. As illustrated in FIG. 20, the count table 55 has a first cell indicating the type of test specimen, a second cell indicating the culture conditions (e.g., dilution ratio, etc.) to be applied to the test specimen, and a third cell (e.g., count cell 224) that stores the colony count results obtained by applying the culture conditions suggested by the second cell to the test specimen indicated by the first cell. The MCU 30, functioning as a creation unit, links the third cell to one of the multiple test settings based on information written in a position corresponding to the third cell in the user file (e.g., a test specification cell in cell group CG3). In this way, the test settings may be linked to the count cell 224 via the setting file 210.

[0169] [Point 3] 19 , the user file may include a first cell group (e.g., CG1) that holds type information indicating the type of test specimen, a second cell group (e.g., CG2) that indicates culture conditions to be applied to the test specimen, and a third cell group (e.g., CG3) that holds setting information identified by a combination of the type of test specimen and the culture conditions and associated with imaging conditions for acquiring an image to be applied to the test specimen or image processing settings to be applied to the image. The MCU 30, functioning as a creation unit, may create the count table 55 by using the type information (e.g., sandwich set) held in the first cell group as the test specimen name in the count table 55 and the names of the culture conditions (e.g., 1:10, 1:100, etc.) held in the second cell group as the culture conditions in the count table 55. Because the cells in the setting file 210 correspond to the cells in the count table 55, the user may create the setting file 210 while keeping the count table 55 in mind.

[0170] [Point 4] The image processing settings may include a detection threshold (e.g., binarization sensitivity) for detecting colonies to be counted from the image, or an exclusion threshold for particulate images to be excluded from the image from being counted (e.g., small particle removal threshold).

[0171] [Point 5] The storage device 35 may function as a storage unit that stores a plurality of pieces of setting information prepared in advance. Each cell in the third cell group may be linked to one of the plurality of pieces of setting information stored in the storage unit based on the input value of each cell (e.g., the name given to the test setting, the [SAMPLEDB] tag, the combination of the [ON] tag and the [MEDIUMTYPE] tag, etc.). In this way, there is a degree of freedom in the method of specifying the test setting, which may allow the user to easily specify the test setting.

[0172] [Point 6] In the count table 55, the count cell 224 into which the count result for each combination of test individuals and culture conditions is input may be linked to setting information linked to a cell corresponding to the count cell in the third cell group in the user file. By clicking the icon 225 of a count cell 224 in the count table 55, the MCU 30 applies the test setting linked to the count cell 224 and causes the colony counting device 1 to perform counting. Here, the count cell 224 may be linked directly or indirectly to the test setting. In the former case, when the count table 55 is created, the test setting may be identified by the test-designated cell of the cell group CG3 in the setting file 210, and the identified test setting may be linked to the count cell 224. In the latter case, the count cell 224 references the test-designated cell of the cell group CG3 in the setting file 210, and when the icon 225 is pressed, the MCU 30 may identify the test-designated cell linked to the count cell 224 and further identify the test setting linked to the test-designated cell.

[0173] [Point 7] The third cell group in the user file includes a test specification cell corresponding to the count cell 224 in the count table 55. The test specification cell may hold a first character string (e.g., [ON]). As illustrated in FIG. 19, the fourth cell group (e.g., CG4) included in the user file may include a cell linked to one of multiple test settings. For example, this cell is a cell corresponding to the first character string (e.g., [ON]) described in the test specification cell (e.g., a cell in a row containing the [MEDIUMTYPE] tag or the [FAVORITES] tag). This cell may contain a character string (e.g., the name of the test setting (e.g., general viable bacteria [background: white])). The test setting (e.g., general viable bacteria - setting 1) linked to the character string described in this cell may be linked to the count cell 224. In this way, a character string (e.g., [ON]) indicating that the default test setting is to be specified may be described in the test specification cell.

[0174] [Point 8] The multiple test settings may include test settings created or selected by the user based on the culture conditions. As described above, the user may register some of the multiple test settings as favorites. A test specification cell in the third cell group in the user file corresponding to the count cell 224 in the count table 55 may contain a second character string (e.g., [ON]). In this case, the fifth cell group (e.g., CG5) included in the user file is referenced. The fifth cell group also contains a cell linked to one of the multiple test settings (e.g., a cell containing the character string "coliforms - dark medium"). The MCU 30 links the test setting (e.g., coliforms - dark medium) linked to the cell corresponding to the second character string to the count cell 224. Note that in the example of FIG. 19, the name of the default test setting is written in cell group CG4, and the name of the test setting registered as a favorite is written in cell group CG5. In the example of FIG. 19, the name of the test setting is written in only one of cell groups CG4 or CG5. Therefore, if the [ON] tag is written in cell group CG3, the test setting name written in cell group CG4 or CG5 is identified. If the test setting name is written in both cell group CG4 and cell group CG5, the test setting name written in cell group CG5 may be used preferentially.

[0175] [Point 9] 26 , an inspection specification cell corresponding to a count cell 224 in the third cell group may hold a third character string (e.g., [SAMPLEDB]). In this case, the MCU 30 links, among multiple inspection settings, an inspection setting that is linked to the inspection object (e.g., sample name) of the inspection specification cell corresponding to the count cell 224 to the count cell 224. In this way, the count cell 224 may be linked to an inspection setting stored in the sample DB 40 or the like via the setting file 210.

[0176] [Point 10] Test settings may be set for each type of colony-forming bacteria (e.g., general viable bacteria, coliform bacteria, Staphylococcus aureus). The culture conditions applied to the test specimen may include the type of bacteria.

[0177] [Point 11] The culture conditions applied to the test individual may include a combination of the type of bacteria and the dilution ratio.

[0178] [Point 12] As shown in Figure 19 and other examples, in a user file, a third cell group (e.g., CG3) may include multiple cells with different dilution ratios for a single test specimen type. Each of these multiple cells may contain a string indicating a test setting associated with a combination of the test specimen type and dilution ratio. In Figure 19, counting is specified for a sandwich set at three dilution ratios (1:10, 1:100, and 1:1000). In this case, there are three test specification cells for each of the three combinations. In Figure 19, each of the three test specification cells contains "On," but the name of a test setting, such as "General Viable Bacteria Setting 2," may also be specified. Furthermore, the strings written in the three test specification cells do not have to be the same. In other words, each of the three combinations may specify a different test setting.

[0179] [Point 13] In the user file, there may be culture conditions in which a multiple counting mode (e.g., rapid mode) is enabled, in which the first count is performed after a predetermined time shorter than the specified culture time has elapsed, and the second count is performed after the specified culture time has elapsed. In Figure 19, the rapid mode is enabled by the [EARLY] tag and the [ON] tag.

[0180] 20, the creation unit (MCU 30) may create count table 55 including a first count cell in column 227 that holds the result of the first count and a second count cell in column 228 that holds the result of the second count for the same test specimen. In this way, by simply creating one column in setting file 210, multiple columns corresponding to the mode are automatically arranged in count table 55.

[0181] [Point 14] The acquisition unit may include an imaging unit (e.g., main camera 11) that captures an image of the test specimen and generates an inspection image of the test specimen. MCU 30 may include a setting unit that sets first detection parameters for detecting colonies from a first inspection image of the test specimen cultured for a predetermined time, and second detection parameters for detecting colonies from a second inspection image of the test specimen cultured for a specified incubation time. Here, the detection sensitivity of the first detection parameter is higher than the detection sensitivity of the second detection parameter. MCU 30 may apply the first detection parameters to the first inspection image to count colonies and input the intermediate result to a first count cell in column 227, and apply the second detection parameters to the second inspection image to count colonies and input the final result to a second count cell in column 228.

[0182] [Point 15] As shown in Fig. 24, the test specimen may be contained in a test container (Petri dish 15) divided into multiple containment areas by separation walls. As shown in Fig. 25, in the user file, the third cell group may include a cell for each containment area identified by a combination of the type of test specimen, the culture conditions, and the containment area. The cell for each containment area may include a character string (e.g., "top left detection") that indicates the test setting to be applied to that containment area.

[0183] [Point 16] 25, in the third cell group of the user file, the inspection setting suggested by the character string (e.g., upper left detection) stored in the cell associated with a first containing area (e.g., upper left valid area 231) among the plurality of containing areas includes excluding the remaining areas (e.g., valid areas 232-234) of the plurality of containing areas excluding the first containing area from the counting targets. In the third cell group of the user file, the inspection setting suggested by the character string (e.g., lower left detection) stored in the cell associated with a second containing area (e.g., lower left valid area 234) among the plurality of containing areas includes excluding the remaining areas (e.g., valid areas 231-233) of the plurality of containing areas excluding the second containing area from the counting targets.

[0184] [Point 17] 22 , when a count result is input to a count cell 224 included in the count table 55, the MCU 30 may function as a copy unit that copies the count result to an examination specification cell corresponding to the count cell 224 in the setting file 210. Furthermore, the MCU 30 may copy the count result to the business file 200.

[0185] [Point 18] As described in relation to FIG. 23, when the creation unit (MCU30) finds a blank cell in the first cell group (for example, CG1), it may create the count table 55 while ignoring the row containing the blank cell.

[0186] [Point 19] 27, the creation unit (MCU 30) may find a tag (e.g., a [REPEAT: n] tag) in the configuration file 210 that specifies performing n counts on the same test specimen and determining statistical values (e.g., average value, standard deviation) of the n count results. In this case, the MCU 30 may allocate n cells in the count table 55 for storing the n count results and a cell for storing the statistical values.

[0187] [Point of View 20] As described in relation to Figure 28, the creation unit (MCU30) may link the test settings to the count cell 224 in which the count result is stored in the count table 55 based on the character string written in the cell located at a specific coordinate (e.g., B1, C1, B3, C3, B5, C5, A6 to A7) in the setting file 210.

[0188] [Point of View 21] 29 , a cell included in the third cell group may describe at least one parameter (e.g., sensitivity: 5.5, small particle removal: 0.3, imaging brightness: 150, etc.) among multiple parameters that configure the inspection setting. In this case, the creation unit (MCU 30) may customize a part of the inspection setting linked to that cell to the parameters specified in that cell, and then link that inspection setting to the count cell 224 corresponding to that cell in the count table 55.

[0189] [Point of View 22] The user file may be a CSV file created by the second software, spreadsheet software (e.g., spreadsheet program 41), or a file in the spreadsheet software's own table format (e.g., xslx format). The xslx format is particularly popular on the market, and many users are familiar with it. Therefore, users can easily create the setting file 210 that will be the basis for the count table 55 using spreadsheet software that they are familiar with.

[0190] [Point of View 23] As illustrated in FIG. 19 , the configuration file 210 is an example of a configuration file that stores information in multiple cells with N rows and M columns. The configuration file 210 may include a first cell storing the type of test specimen (e.g., sample name), a second cell storing the culture conditions of the test specimen (e.g., dilution ratio), a third cell storing the target bacterial species (e.g., a cell in a row containing a [NAME] tag), and a fourth cell indicating a test setting identified by a combination of the type of test specimen, the culture conditions of the test specimen, and the target bacterial species. For example, the fourth cell may be a test-designated cell included in cell group CG3, a cell in a row containing a [MEDIUMTYPE] tag, or a cell in a row containing a [FAVORITES] tag. The MCU 30 functions as a reading unit that reads the configuration file 210. The storage device 35 may store multiple test settings corresponding to at least one of the type of test specimen and the target bacterial species to identify individual test settings corresponding to at least one of the type of test specimen and the target bacterial species. The MCU 30 functions as a count table generator that generates a count table 55 including multiple count candidate cells (e.g., count cell 224) that store count results obtained by a test based on the type of test specimen, the culture conditions of the test specimen, the target bacterial species, and the test settings suggested by a fourth cell, which is determined by a combination of the type of test specimen, the culture conditions of the test specimen, and the target bacterial species, all of which are included in the setting file 210 read by the reader. Each of the multiple count candidate cells is identified by a combination of the type of test specimen, the culture conditions of the test specimen, and the target bacterial species. The display controller 36 functions as a display controller that displays the count table 55 generated by the count table generator (MCU 30) on a display unit (e.g., display device 37). The pointing device 33 functions as a cell identifier that identifies a cell into which a count result is input from among the multiple count candidate cells included in the count table 55 displayed by the display controller 36. The MCU 30 functions as an inspection execution unit that acquires an inspection image, which is an image of an inspection individual, based on the inspection settings, and counts the colonies included in the inspection image.Furthermore, the MCU 30 functions as a count table editing unit that assigns the colony count results counted by the inspection execution unit to one cell identified by the cell identification unit.

[0191] [Point of View 24] The MCU 30 functions as a reading unit that reads a setting file having first test settings corresponding to the arrangement determined by the row or column items, each of which includes the type of test specimen, the culture conditions for the test specimen, and the bacterial species to be detected. The storage device 35 stores second test settings corresponding to at least one of the type of test specimen or the bacterial species to be detected, in order to identify individual test settings corresponding to each of the multiple types of test specimen or the multiple bacterial species to be detected. The MCU 30 may also function as a count table generator that generates a count table 55 including multiple count candidate cells that store count results counted by a test based on the type of test specimen, the culture conditions for the test specimen, the bacterial species to be detected, and the first test settings (e.g., information for specifying the test settings stored in cell group CG3) corresponding to the arrangement determined by the combination of the type of test specimen, the culture conditions for the test specimen, and the bacterial species to be detected, contained in the setting file read by the reading unit, and second test settings (e.g., actual test settings) stored in the storage device corresponding to the first test settings.

[0192] The invention is not limited to the above-described embodiment, and various modifications and variations are possible within the scope of the gist of the invention. [Explanation of symbols]

[0193] 1: Colony counting device, 35: Storage device, 30: MCU

Claims

1. an acquisition unit for acquiring an image of a colony occurring on the specimen; an execution unit that executes first software and executes a process of counting the number of colonies from the image of the colonies; The execution unit: a reading unit that reads a user file that holds information in a matrix format and that is created by second software different from the first software in order to count the colonies that occur in the test individual or to manage the colony count results; a creation unit that creates a count table used for counting the colonies based on the user file; A colony counting device having:

2. further comprising a storage means for storing a plurality of test settings to be applied to the test specimen; the count table has a first cell indicating the type of the test individual, a second cell indicating the culture conditions to be applied to the test individual, and a third cell for holding the count results of colonies counted by applying the culture conditions suggested by the second cell to the test individual suggested by the first cell, 2. The colony counting device according to claim 1, wherein the creation unit links the third cell to any one of the plurality of test settings based on information described at a position corresponding to the third cell in the user file.

3. The user file is a first cell group that holds type information indicating the type of the test specimen; a second cell group indicating culture conditions to be applied to the test individual; a third cell group that stores test settings that are specified by a combination of the type of the test individual and the culture conditions, and that are associated with imaging conditions for acquiring the image that is applied to the test individual or image processing settings that are applied to the image; Including, 2. The colony counting device according to claim 1, wherein the creation unit creates the count table by adopting type information stored in the first cell group as names of test individuals in the count table and adopting names of the culture conditions stored in the second cell group as culture conditions in the count table.

4. 4. The colony counting device according to claim 3, wherein the image processing settings include a detection threshold for detecting colonies to be counted from the image, or an exclusion threshold for particulate images to be excluded from the image as count targets.

5. further comprising a storage unit that stores a plurality of test settings prepared in advance; 4. The colony counting device according to claim 3, wherein each of the cells in the third cell group is linked to one of the plurality of test settings stored in the memory unit based on an input value of each cell.

6. 6. The colony counting device according to claim 5, wherein in the count table, a count cell into which a count result for each combination of the test individual and the culture conditions is input is linked to the test setting that is linked to a cell in the third cell group in the user file that corresponds to the count cell.

7. If a cell in the third group of cells in the user file corresponding to the count cell in the count table holds a first character string, 7. The colony counting device according to claim 6, wherein a fourth cell group included in the user file includes a cell linked to any one of the plurality of test settings, and the test setting linked to the cell corresponding to the first character string is linked to the count cell.

8. the plurality of test settings include test settings created or selected by a user according to culture conditions; If a cell in the third cell group in the user file corresponding to the count cell in the count table holds a second character string, 7. The colony counting device according to claim 6, wherein a fifth cell group included in the user file includes a cell linked to any one of the plurality of test settings, and the test setting linked to a cell corresponding to the second character string is linked to the count cell.

9. If a cell in the third cell group corresponding to the count cell holds a third character string, The colony counting device according to claim 6 , wherein, among the plurality of test settings, a test setting linked to the test specimen in a cell corresponding to the count cell is linked to the count cell.

10. the test setting is provided for each type of bacteria that forms the colony, The culture conditions applied to the test individual include the type of the bacterium, The colony counting device according to claim 5.

11. The culture conditions applied to the test individual include a combination of the type of the bacterium and a dilution ratio. The colony counting device according to claim 10.

12. 12. The colony counting device according to claim 11, wherein in the user file, the third cell group includes a plurality of cells each having a different dilution ratio for a type of one test individual, and the plurality of cells include a character string suggesting the test setting linked to a combination of the type of the test individual and the dilution ratio.

13. When the user file contains a culture condition in which a multiple counting mode is enabled, in which a first count is performed when a predetermined time shorter than a specified culture time has elapsed, and a second count is performed when the specified culture time has elapsed, 2. The colony counting device according to claim 1, wherein the creation unit creates a count table including, for the same test individual, a first count cell that holds the result of the first count and a second count cell that holds the result of the second count.

14. the acquisition unit has an imaging unit that captures an image of the inspection object and generates an inspection image of the inspection object, the execution unit has a setting unit that sets first detection parameters for detecting the colonies from a first inspection image of the test specimen that has been cultured for the predetermined time, and sets second detection parameters for detecting the colonies from a second inspection image of the test specimen that has been cultured for the specified culture time, the detection sensitivity of the first detection parameter is higher than the detection sensitivity of the second detection parameter; The execution unit further applies the first detection parameter to the first inspection image to count the colonies and input an intermediate result to the first counting cell, and applies the second detection parameter to the second inspection image to count the colonies and input a final result to the second counting cell. The colony counting device according to claim 13.

15. The test specimen is contained in a test container divided into a plurality of storage areas by separation walls, 4. The colony counting device according to claim 3, wherein in the user file, the third cell group includes a cell for each storage area identified by a combination of the type of the test individual, the culture conditions, and the storage area, and the cell for each storage area includes a character string suggesting an inspection setting to be applied to the storage area.

16. In the third cell group of the user file, the inspection setting suggested by the character string stored in the cell associated with a first storage area among the plurality of storage areas includes excluding the remaining areas of the plurality of storage areas excluding the first storage area from counting targets; In the third cell group of the user file, the inspection setting suggested by the character string stored in a cell associated with a second storage area among the plurality of storage areas includes excluding the remaining areas of the plurality of storage areas excluding the second storage area from counting targets. The colony counting device according to claim 15.

17. 4. The colony counting device according to claim 3, further comprising a copying unit that, when a count result is input to a count cell included in said count table, copies said count result to a cell in said user file that corresponds to said count cell.

18. The colony counting device according to claim 3 , wherein when the creation unit finds a blank cell in the first cell group, the creation unit creates the count table while ignoring a row including the blank cell.

19. 2. The colony counting device according to claim 1, wherein when the creation unit finds a tag in the user file that specifies performing n counts on the same test individual and calculating a statistical value of the n count results, the creation unit places n cells in the count table for storing the n count results and a cell for storing the statistical value.

20. 2. The colony counting device according to claim 1, wherein the creation unit associates an inspection setting with a count cell in which a count result is stored in the count table, based on a character string written in a cell located at a predetermined coordinate in the user file.

21. 4. The colony counting device according to claim 3, wherein, when at least one parameter among a plurality of parameters constituting an inspection setting is described in a cell included in the third cell group, the creation unit customizes a part of the inspection setting linked to the cell to the at least one parameter, and then links the inspection setting to a count cell corresponding to the cell in the count table.

22. 2. The colony counting device according to claim 1, wherein the user file is a CSV file created by spreadsheet software that is the second software, or a table-format file unique to the spreadsheet software.

23. a reading unit that reads a setting file that holds information in a plurality of cells of N rows x M columns, the setting file including: a first cell that stores the type of test specimen; a second cell that stores the culture conditions of the test specimen; a third cell that stores the bacterial species to be detected; and a fourth cell that is specified by a combination of the type of test specimen, the culture conditions of the test specimen, and the bacterial species to be detected and that indicates test settings; a storage unit that stores a plurality of test settings corresponding to at least one of the type of the test specimen and the bacterial species to be detected, in order to identify an individual test setting corresponding to at least one of the type of the test specimen and the bacterial species to be detected; a count table generating unit that generates a count table including a plurality of count candidate cells that store count results counted by a test based on the type of test individual included in the setting file read by the reading unit, the culture conditions of the test individual, the bacterial species to be detected, and the test settings suggested by the fourth cell, which is determined by a combination of the type of the test individual, the culture conditions of the test individual, and the bacterial species to be detected, among the plurality of test settings, wherein each of the plurality of count candidate cells is specified by a combination of the type of the test individual, the culture conditions of the test individual, and the bacterial species to be detected; a display control unit that displays the count table generated by the count table generation unit on a display unit; a cell identification unit that identifies one cell to which the count result is input from among the plurality of count candidate cells included in the count table displayed by the display control unit; an inspection execution unit that acquires an inspection image that is an image of the inspection individual based on the inspection settings and counts colonies included in the inspection image; a count table editing unit that assigns the colony count result counted by the inspection execution unit to the one cell identified by the cell identification unit; A colony counting device comprising:

24. a reading unit that reads a setting file having a type of test specimen, a culture condition of the test specimen, and a bacterial species to be detected as either row or column items, and having a first test setting corresponding to the arrangement determined by each item; a storage unit that stores second test settings corresponding to at least one of the types of test specimens or the types of bacteria to be detected, in order to identify individual test settings corresponding to each of the types of test specimens or the types of bacteria to be detected; a count table generator that generates a count table including a plurality of count candidate cells that store count results counted by a test based on the type of test individual, the culture conditions of the test individual, the bacterial species to be detected, a first test setting corresponding to an arrangement determined by a combination of the type of test individual, the culture conditions of the test individual, and the bacterial species to be detected, which are included in the setting file read by the reader, and a second test setting stored in the storage unit that corresponds to the first test setting, wherein each of the plurality of count candidate cells is specified by a combination of the type of the test individual, the culture conditions of the test individual, and the bacterial species to be detected; a display control unit that displays the count table generated by the count table generation unit on a display unit; a cell identification unit that identifies one cell to which the count result is input from among the plurality of count candidate cells included in the count table displayed by the display control unit; an inspection execution unit that acquires an inspection image that is an image of the inspection individual based on the second inspection setting and counts colonies included in the inspection image; a count table editing unit that assigns the colony count results counted by the inspection execution unit to the cells identified by the cell identification unit; A colony counting device comprising:

25. Obtaining an image of the colony occurring on the test specimen; an execution unit that executes first software and executes a process of counting the number of colonies from the image of the colonies, reading a user file that holds information in a matrix format and that is created by second software different from the first software in order to count the colonies that occur in the test individual or to manage the colony count results; creating a count table based on the user file for use in counting the colonies; A method for controlling a colony counting device having the above construction.

26. A program that causes a computer to execute the method for controlling a colony counting device according to claim 25.

Images