Bacterial colony counting device and control method

Abstract

The invention provides a bacterial colony counting device and a control method. And the burden of counting bacterial colonies by a user is reduced. The colony counting apparatus includes an acquisition section that acquires an image of a colony generated in a test individual, and an execution section that executes first software, the execution section performing a process of counting a number of colonies based on the image of the colony. The execution unit reads a user file that holds information in an array format created by second software different from the first software so as to count colonies generated in the test individual or to manage a result of counting the colonies. Further, the execution section creates a count table for counting colonies based on the user file.

Description

Technical Field

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

[0002] In a food production factory, a colony counter is used to test whether bacteria are mixed in a product. An inspector forms a culture medium in a Petri dish, places a food sample in the culture medium, and incubates the food sample in a culture container or the like for a predetermined period of time. Thereafter, the inspector takes out the Petri dish from the culture container and counts the colonies (bacterial colonies) using a colony counter. In this way, the counting accuracy of the colony counter is important for food hygiene management.

[0003] Japanese Patent Application Laid-Open No. 2015-171334 proposes counting the number of colonies from an image of a Petri dish obtained by a camera.

[0004] Meanwhile, a user creates a test list and a counting table using widely used spreadsheet software, prints the test list and the counting table on paper, and incubates fungi in a culture medium for each test individual (sample name) while referring to the test list, and visually or using a colony counter counts the colonies generated by the fungi. In addition, the user handwrites the counting results of the colonies in the counting table. Thereafter, the user opens the original counting table with the spreadsheet software and manually inputs the counting results from the paper counting table into an electronic file. At this time, errors may also occur in the transcription, and the burden on the user's transcription work is great.

[0005] On the other hand, if the counting table is created by a colony counter that can display an electronic counting table, the burden of transcription work will be reduced. In this case, the user must be familiar with the user interface of the colony counter to create the counting table, which is an obstacle to the introduction of the colony counter. In this case, if a counting table for the colony counter can be created using spreadsheet software with which the user is familiar, the obstacle to the introduction of the colony counter will be reduced. Summary of the Invention

[0006] Therefore, an object of the present invention is to reduce the burden on the user for colony counting.

[0007] For example, the present invention provides a colony counting device including:

[0008] an acquisition unit configured to acquire an image of colonies generated in a test individual; and

[0009] an execution unit configured to execute a first software, the execution unit being configured to perform a counting process of the number of colonies from the image of the colonies,

[0010] wherein the execution unit includes:

[0011] A reading unit for reading a user file to count colonies generated in the test subject or manage the counting results of the colonies, the user file storing information in an array format and created by a second software different from the first software; and

[0012] A creating unit for creating a counting table for counting the colonies based on the user file.

[0013] According to the present invention, the burden on the user for colony counting is reduced. Description of the Drawings

[0014] Figure 1 is a view showing a colony counting device;

[0015] Figure 2 is a diagram for explaining the electrical configuration of the head device;

[0016] Figure 3 is a diagram for explaining the electrical configuration of the control device;

[0017] Figure 4 is a view for explaining the user interface (UI);

[0018] Figure 5 is a view for explaining the UI for creating a counting table from a sample database;

[0019] Figure 6 is a view for explaining the UI for newly creating a counting table;

[0020] Figure 7 is a view for explaining the form of a spreadsheet software;

[0021] Figure 8 is a view for explaining the UI for adding column elements;

[0022] Figure 9 is a view for explaining the UI during testing;

[0023] Figure 10 is a view for explaining the UI indicating counting;

[0024] Figure 11 is a diagram showing the UI when registering the counting result in a cell;

[0025] Figure 12 is a view for explaining the UI showing the automatic recognition of a target cell;

[0026] Figure 13 is a diagram for explaining the UI for resetting counting conditions;

[0027] Figure 14is a flowchart showing the processing performed by the PC;

[0028] Figure 15 is a flowchart showing the editing of the sample database;

[0029] Figure 16 is a flowchart showing the colony counting method;

[0030] Figure 17 is a view for explaining the business document;

[0031] Figure 18 is a view for explaining the configuration file;

[0032] Figure 19 is a view for explaining the functions of each cell;

[0033] Figure 20 is a view for explaining the counting table;

[0034] Figure 21 is a view for explaining the counting table;

[0035] Figure 22 is a view for explaining the reflection of the counting result;

[0036] Figure 23 is a view for explaining the processing of blank cells;

[0037] Figure 24 is a view for explaining the petri dish with multiple accommodation areas;

[0038] Figure 25 is a view for explaining the configuration file related to the petri dish with multiple accommodation areas;

[0039] Figure 26 is a view for explaining the reference to the test settings included in the specimen DB;

[0040] Figure 27 is a view for explaining the labels related to the averaging process;

[0041] Figure 28 is a view for explaining the method of converting the configuration file into a counting table without using labels;

[0042] Figure 29 is a view for explaining the customization of the test settings;

[0043] Figure 30 is a flowchart showing the method of creating a counting table;

[0044] Figure 31 is a flowchart showing the method of obtaining the test column settings; and

[0045] Figure 32 is a flowchart showing a method of obtaining test settings. Detailed implementation mode

[0046] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the present invention according to the claims, and all combinations of the features described in the embodiments are not necessarily essential for the present invention. Two or more of the multiple features described in the embodiments can be arbitrarily combined. In addition, the same or similar configurations are denoted by the same reference numerals, and redundant descriptions will be omitted.

[0047] <First Embodiment>

[0048] [Colony counting device]

[0049] Figure 1 The colony counting device 1 is shown. Note that the colony counting device 1 includes a head device 1a and a control device (personal computer (PC)) 1b which will be described later. For example, the head device 1a and the PC 1b can be connected to each other in a wired manner via a universal serial bus (USB) cable, or can be connected to each other in a wireless manner.

[0050] The head device 1a includes 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 exists between the upper unit 2 and the lower unit 4 and supports the upper unit 2. A platform 5 is provided on the top surface of the lower unit 4. The platform 5 is provided with a transmission window 6 and a positioning member 7. A petri dish 15 is placed on the transmission window 6, and the positioning member 7 is used to position the petri dish 15 at the center of the transmission window 6. An operation unit 8 and a front camera 10 are provided in front of the lower unit 4. The operation unit 8 includes a plurality of switches (for example, a first hardware button 8a, a second hardware button 8b, and a third hardware button 8c) for a user to input instructions. The front camera 10 is optional and reads, for example, two-dimensional symbols (barcodes), etc. The front camera 10 is arranged in a recess 4a provided on the front surface of the housing of the head device 1. A power switch 9 is provided on the side surface of the lower unit 4.

[0051] Figure 2The electrical configuration of the head device 1a is shown. The MCU 20 is a processor that executes the control program 27 stored in the storage device 25 and controls the head device 1a according to the control program 27. Note that MCU is an abbreviation for micro - controller unit. The MCU 20 controls the main camera 11 and the front camera 10 via the imaging control unit 21 to acquire various types of image data. The imaging control unit 21 controls, for example, the exposure time of the main camera 11. The MCU 20 turns on or off the ring illumination device 12, the ring illumination device 13, and the coaxial illumination device 14 via the illumination control unit 22. The illumination control unit 22 controls the drive power supplied to the ring - shaped illumination device 12, the ring illumination device 13, and the coaxial illumination device 14. The MCU 20 receives user input entered from the operation unit 8 via the operation reception unit 23. The operation reception 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 Figure 3 PC 1b shown via the 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 the control program 27 and a random access memory (RAM) that serves as a work area. The storage device 25 may store, for example, the test conditions 28 set by the PC1b, the test images 29 acquired by the main camera 11, etc. The test conditions 28 may include, for example, illumination conditions, imaging conditions, counting conditions, etc. The test image 29 is an image of the petri dish 15 including the culture medium and the sample.

[0052] Figure 3The PC 1b that controls the head device 1a is shown. The MCU 30 is a processor that executes a program stored in the storage device 35 and controls the PC 1b and the head device 1a according to the program. The MCU 30 receives user instructions from the keyboard 32 and the pointing device 33 connected to the input / output circuit 31. The MCU 30 controls the printer 38 connected to the input / output circuit 31 to print forms and the like on paper. The MCU 30 displays various types of information on the display device 37 via a display control unit 36 such as a graphics tablet. The communication circuit 34 is a circuit that 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) that serves as a work area. In addition, the storage device 35 may include a hard disk drive (HDD) and a solid state drive (SSD). The storage device 35 can store application programs 39, test conditions 28, test images 29, sample DB 40, count table 55, etc. DB is an abbreviation for database (database). The application program 39 is responsible for, for example, the creation and editing of the sample DB 40 and the count table 55, the control of the head device 1, etc. The test conditions 28 are set by the MCU 30 according to the application program 39. The test image 29 is 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.

[0053] In the PC 1b, the communication circuit 34 can perform wireless communication with a terminal device 1c such as a smart phone or a tablet terminal. The terminal device 1c can display the count table 55 or can display a test list created from the count table 55. The test list includes petri dish numbers, sample names, bacterial species, culture media, dilution factors, culture times, etc., and is referred to when the user prepares test individuals in the petri dish 15.

[0054] The spreadsheet program 41 is an optional spreadsheet software that has been widely used. The business document 200 and the configuration file 210 created by the spreadsheet program 41 will be described in detail in the second embodiment.

[0055] [Test Process]

[0056] The general test process is as follows.

[0057] (1) The user creates a test list by hand. The test list includes multiple lines, and petri dish numbers, bacterial species, dilution factors, counts, and notes (such as sample product names) can be written in each line. Note that the petri dish numbers mentioned here are identification information pre-assigned according to a predetermined rule to specify culture conditions such as culture medium types or dilution factors.

[0058] (2) The user writes the number on the lid of the Petri dish according to the test list, or writes the number pre-written on the Petri dish into the test list.

[0059] (3) The user creates the culture medium according to the dilution factor written in the test list. If the dilution factor is not written in the test list, the user writes the actual dilution factor into the test list.

[0060] (4) The user puts the sample into the culture medium in each Petri dish (mixes). The user writes the name of the sample in the comment column of the test list.

[0061] (5) The user puts the Petri dish into the culture container.

[0062] (6) When the predetermined time has passed, the user takes out the Petri dish from the culture container and counts the number of colonies. For example, while observing the colonies through the bottom surface side of the Petri dish, the user gives a counting mark to the position of the colonies with an oil-based pen. The number of colonies is written into the test list. Note that the user can count the number of colonies of each bacterial species while visually confirming the bacterial species. In this case, the user writes the number of colonies of each bacterial species into the test list of each Petri dish.

[0063] (7) The user activates the PC, reads the values and characters written in the test list, and inputs them into the spreadsheet software. Use macro functions such as spreadsheet software to summarize the number of colonies.

[0064] In this way, the test list is created by handwriting during the regular test process, which is a very troublesome task for the user. In addition, if there is an incorrect input when transcribing the values written in the test list into the form of the spreadsheet software, there is a possibility that the summary result is also incorrect. Even if the number of colonies can be automatically obtained by a colony counter, there is still a possibility of incorrect writing and incorrect input because in the conventional technology, all the creation of the test list, writing the number of colonies into the test list, and transcribing from the test list to the form of the spreadsheet software are done by handwriting.

[0065] Therefore, in this example, it is proposed to create an electronic test list by the PC 1b, count the colonies according to the electronic test list, directly input the counting result into the electronic test list, and summarize the input numbers. Therefore, the burden on the user for the post-processing of the colony counting result can be reduced. In addition, since the user's handwriting or manual input is reduced, incorrect input can also be reduced, and the test accuracy can be improved.

[0066] [Creation of Test List (Counting Table)]

[0067] Figure 4 The UI 50 of the counting application displayed on the display device 37 of the PC 1b is shown. The counting application is stored in the storage device 35 and executed by the MCU 30. The UI 50 includes buttons, links, tabs, etc. for switching among a plurality of functions included in the counting application.

[0068] The UI 50 includes 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 the counting table 55. The title display section 52 receives and displays an input of the title (name) given to the counting table 55 from the keyboard 32. The button 53 is a button for switching the execution / non-execution of counting for each cell. The button 54 is a button for instructing to add a column to the counting table 55. The average setting section 56 includes a checkbox for indicating whether to perform averaging of the counting results, and a selection section (= number of iterations of counting) for the number of count values to be averaged.

[0069] The DB display area 61 displays a template list of pre-registered counting items (e.g., the sample DB 40). Here, a counting item corresponds to a row in the counting table 55. Counting items are generally distinguished by the name of the test target object (sample name). The name display section 62 displays the name (sample name) of the pre-registered template. The indicator 63 is an object that visually displays the classification label associated with the sample name. The classification label is a label indicating classification defined by the user (e.g., staple food, side dish, or dessert). For example, the indicator 63 can use differences in color to represent differences in classification labels. The indicator 63 can use differences in the shape of the indicator 63 to represent differences in classification labels. The button 67 is a button for expanding and displaying one or more sub-items having a parent-child relationship with respect to a specific sample name. The parent-child relationship refers to the relationship between a sample and the various components that make up the sample. For example, when a sandwich is used as the parent, the components that make up the sandwich (e.g., ham, lettuce, and egg) are the children. The button 64 is a button for instructing to add the corresponding template to the counting table 55. Since the sample DB 40 is prepared in this way, the user can easily create the counting table 55.

[0070] In Figure 4In the case shown, when the user presses the button 64 associated with the 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 for the sample name in the added row. The ID is an abbreviation for identification information. That is, the ID and the sample name are set based on the row and are "settings for the row". In addition, the MCU 30 reads the test conditions of the sandwich recorded 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 type of bacteria (e.g., general live bacteria or Escherichia coli), the dilution factor of the culture medium, the incubation time of the sample, etc. Each column includes cells for, for example, the type of bacteria, the dilution factor, the incubation time, and the count value. That is, the type of bacteria, the dilution factor, and the incubation time are set based on the column and are "settings for the column". In this example, since the test has not been performed yet and the count value has not been obtained, there is no input to the cell for the count value. The first test item for the sandwich is to use a culture medium with a dilution factor of 100 times for general live bacteria and apply an incubation time of 48 hours. The second test item for the sandwich is to use a culture medium with a dilution factor of 1000 times for general live bacteria and apply an incubation time of 48 hours. In this way, the MCU 30 adds columns according to the number of test items.

[0071] In Figure 5 , when the user presses the button 64 associated with kimchi, the MCU 30 reads the test conditions of the kimchi registered in the sample DB 40 from the storage device 35 and adds rows and columns corresponding to the read test conditions to the count table 55.

[0072] In this example, kimchi has two test items. The first test item for kimchi is to use a culture medium with a dilution factor of 100 times for general live bacteria and apply an incubation time of 48 hours. This also applies to the first test item for the sandwich. Therefore, the MCU 30 discards the first test item included in the template for kimchi and does not add the test item as a new column. The second test item for kimchi is to use a culture medium with a dilution factor of 100 times for Escherichia coli and apply an incubation time of 24 hours. The MCU 30 adds it as a new column to the count table 55.

[0073] Note that no Escherichia coli test is performed on the sandwich. Therefore, a character or image indicating "No test" can be displayed in the cell for the count value. Similarly, no test using a culture medium with a dilution factor of 1000 for general live bacteria is performed on kimchi. Therefore, a character or image indicating "No test" can be displayed in the cell for the count value.

[0074] Note that the execution / non-execution of counting can also be performed by operating the counting reverse button 53. For the sandwich, when the counting reverse button 53 is operated in the state where the cell corresponding to Escherichia coli is selected, the MCU 30 can switch between displaying a character or image indicating "no test" and leaving a blank for inputting the counting result.

[0075] As Figure 4 and Figure 5 shown, a search box 65 and a label search narrowing button 66 can be added. When the number of templates registered in the sample DB 40 increases, it becomes difficult to display all the templates at once in the DB display area 61. Therefore, the MCU 30 can search the storage device 35 based on the characters input to the search box 65 to extract templates and display the search results in the DB display area 61. In addition, when the label search narrowing button 66 is pressed, the MCU 30 can display only the sample products filtered by the specified classification label. For example, the same classification label can be given to multiple sample products. In this case, multiple sample products with the selected classification label are added to the counting table 55.

[0076] Figure 6 The UI 50 in the case of newly creating a counting table is shown. For example, the MCU 30 can start the spreadsheet software in parallel with the application 39.

[0077] Figure 7 The form 70 of the spreadsheet software is shown. The MCU 30 receives a copy and paste instruction of the selected form 70 or cell group in the spreadsheet software to the UI 50. Therefore, the MCU 30 can create Figure 5 the counting table 55 as shown.

[0078] Figure 8A dialog box 90 for adding columns is shown. When the button 54 provided 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 receives an input of the name of the bacterial species, which is the item name of the column. The column type setting unit 92 receives a setting regarding whether the column type is a count column or a free column. A count column is a column that includes cells to which count values are input. A free column is a column in which the user can freely input text, images, and other information such as remarks and comments. The dilution factor setting unit 93 receives an input of the dilution factor. The culture time setting unit 94 receives an input of the culture time. The algorithm setting unit 95 receives a setting of the image processing applied to the test image. Residue removal is a mode in which residues (e.g., dirt, stains, and handwriting) attached to the petri dish 15 or the like are reduced through image processing. The quick mode is a mode that emphasizes quick result confirmation and is a mode in which the petri dish 15 cultured for a culture time shorter than that in the related art is tested with higher sensitivity. The culture medium type setting unit 96 receives a selection of the culture medium type (e.g., general live bacteria (white) or general live bacteria (black)). It should be noted that when the list button 96a is pressed, the MCU 30 can read candidate culture medium types from the storage device 35 to create a list and display the list on the display device 37. The count setting unit 97 receives settings of the shooting conditions (e.g., exposure time) of the main camera 11, the lighting type (e.g., brightness and lighting device), the display processing type, the image processing type, etc. That is, the bacterial species, dilution factor, culture time, algorithm setting, culture medium type, or count setting received in the dialog box 90 is set as the default setting for each column.

[0079] [Counting process]

[0080] Figure 9 The UI 100 displayed on the display device 37 of the PC 1b during the execution of the counting process by controlling the head device 1a from the PC 1b is shown. The count table area 101 is an area for displaying the count table 55 edited through the UI 50. The result area 102 is an area for displaying the test image 103 acquired by the main camera 11 of the head device 1a. Note that the test image 103 can be a moving image or a still image. Generally, when adjusting the exposure time of the main camera 11, the brightness of each of the ring lighting device 12, the ring lighting device 13, and the coaxial lighting device 14, the selection of the light emitting element to be turned on, the selection of the image processing, etc., the MCU 30 acquires a moving image through the main camera 11 and displays the moving image in the result area 102. On the other hand, when the counting process is executed, the MCU 30 acquires a still image through the main camera 11 and displays the acquired still image in the result area 102.

[0081] The checkbox 106 is a control object for selecting whether 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 shooting instruction (shooting button) is assigned to the first software button 105a. The registration instruction (registration button) is assigned to the second software button 105b. In Figure 9 the second software button 105b is indicated by a dashed line, which means it is inoperable.

[0082] The user clicks and selects, using the pointer 57, a cell corresponding to the petri dish 15 set on the platform 5 from among the plurality of cells included in the count table displayed in the count table area 101. As Figure 9 shown, the cell selected by the pointer 57 can be displayed in an emphasized manner so that any cell selected by the user can be identified. Each cell is stored in the storage device 35 in advance in association with test conditions (sensitivity when binarizing colonies, type of lighting device, brightness, etc.). The MCU 30 reads the test conditions associated with the selected cell from the storage device 35 and sends the test conditions to the head device 1a. The MCU 20 of the head device 1a controls the main camera 11, the ring lighting device 12, the ring lighting device 13, and the coaxial lighting device 14 according to the received test conditions, acquires an image, and sends the image to the PC 1b. Note that when another cell is selected, the MCU 30 reads the test conditions associated with the selected cell from the storage device 35 and sends the test conditions to the head device 1a. The MCU 20 of the head device 1a controls the main camera 11, the ring lighting device 12, the ring lighting device 13, and the coaxial lighting device 14 according to the received test conditions, acquires an image, and sends the image to the PC 1b. In this way, the user can change the test conditions by selecting a cell.

[0083] Figure 10 Shown is the UI 100 displayed on the display device 37 by the MCU30 when the first software button 105a or the first hardware button 8a, which is the shooting 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 shooting button to a button indicating counting (counting button).

[0084] Figure 11Shows the UI 100 displayed on the display device 37 by the MCU 30 when the first software button 105a or the first hardware button 8a, which serves as a counting button, is pressed. When the counting button is pressed, the MCU 30 instructs the head device 1a to count colonies. The MCU 20 of the head device 1a counts the colonies in response to the counting instruction and transmits the count value to the PC1b. Note that the counting process can be executed by the MCU 30. The MCU 30 displays the count value in the count value area 104. At this time, the MCU 30 can convert the count value to CFU / mL (colony-forming units per unit volume (milliliter)) and display CFU / mL in the count value area 104. For example, whenever the count value area 104 is clicked with the pointer 57, the MCU 30 can switch the display in the order of only the count value, only CFU / mL, and count value + CFU / mL. Note that CFU is the abbreviation of colony forming unit. In addition, when the count value is obtained, the MCU 30 reassigns the first software button 105a from the counting button to the shooting button. In addition, the MCU 30 changes the second software button 105b and the second hardware button 8b assigned to the registration button from the inoperable state to the operable state.

[0085] Figure 12 Shows the state where the registration button is pressed. The MCU 30 can write the count value into the currently selected cell and change the next cell to the selected state (the cell of interest). In this example, the cell of interest (active cell) changes 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. Note that the MCU 30 returns the second software button 105b and the second hardware button 8b assigned to the registration button from the operable state to the inoperable state.

[0086] Figure 12 The shown UI 100 includes a cell display target change menu 109. In Figure 12 Since "count quantity" is selected in the change menu 109, "100" is displayed in the cell.

[0087] Figure 13 Shows the UI 100 displayed on the display device 37 by the MCU 30 when the cell in which the count value has been input is double-clicked. The setting screen 120 includes control objects for adjusting parameters related to the colony detection algorithm among the test conditions associated with the cell selected by double-clicking. The slider 121 is, for example, a control object for setting a threshold to remove small particles through image processing. The slider 122 is a control object for adjusting the colony detection sensitivity.

[0088] The MCU 30 can display marks such as circles to be superimposed on the portions detected as colonies in the image 103 displayed in the result area 102. Since the MCU 30 changes the algorithm according to the adjustment of each of the sliders 121 and 122, the position and number of the marks indicating the colonies also change. As a result, the user can easily find an appropriate adjustment amount.

[0089] [Flowchart]

[0090] (1)Main processing of the PC 1b

[0091] Figure 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 according to the counting application program stored in the storage device 35.

[0092] In S1, the MCU 30 edits the counting table. As described in references Figures 4 to 8 etc., the counting table is edited or created through the UI 50 or the like.

[0093] In S2, the MCU 30 stores the counting table in the storage device 35.

[0094] In S3, the MCU 30 identifies the counting table. The counting table can be identified using the front camera 10 and the test list or the user authentication label, or can be identified using the file dialog box.

[0095] In S4, the MCU 30 reads the identified counting table from the storage device 35. Therefore, Figure 9 the UI 100 shown is displayed on the display device 37.

[0096] In S5, the MCU 30 identifies the cell where the count value is to be written. First, the cell in the top row of the counting table can be selected, or the cell clicked by the pointer 57 can be selected.

[0097] In S6, the MCU 30 identifies the test conditions associated with the active cell. For example, when the counting table has been created, the MCU 30 reads the test conditions associated with each cell from the storage device 35.

[0098] In S7, the MCU 30 sets the test conditions associated with the active cell in the head device 1a. As described above, the sensitivity of the main camera 11, the lighting device to be turned on, the brightness, the number of light emitting elements to be turned on (irradiation direction), image processing (HDR or ring removal), the counting algorithm (parameters such as threshold), etc. are sent to the head device 1a.

[0099] In S8, the MCU 30 determines whether the test conditions have changed. As described above, even during the test, the test conditions associated with the cell can be changed at any time. Therefore, when the test conditions change, the MCU 30 returns to S7 and sends the changed test conditions to the head device 1a. When the test conditions have not changed, the MCU 30 proceeds to S9.

[0100] In S9, the MCU 30 determines whether the user has input a shooting instruction. The user can indicate shooting by pressing the first hardware button 8a of the head device 1a or the first software button 105a of the UI 100. When no shooting instruction is input, the MCU 30 returns from S9 to S8. When a shooting instruction is input, the MCU 30 proceeds from S9 to S10.

[0101] In S10, the MCU 30 sends an imaging instruction to the head device 1a.

[0102] In S11, the MCU 30 acquires an image (test image) of the petri dish image 103 obtained by the main camera 11 from the head device 1a and displays the test image in the result area 102 of the UI 100.

[0103] In S12, the MCU 30 determines whether a counting instruction has been input. The user can input a counting instruction by pressing the first hardware button 8a of the head device 1a assigned as the counting button or the first software button 105a of the UI 100. When no counting instruction is input, the MCU 30 returns from S12 to S8. When a counting instruction is input, the MCU 30 proceeds from S12 to S13.

[0104] In S13, the MCU 30 sends the counting instruction to the head device 1a. Note that in the case where the counting process is executed by the PC 1b, the MCU 30 performs the counting process instead of the MCU 20.

[0105] In S14, the MCU 30 receives the counting result from the head device 1a and displays the counting result in the count value area 104. Note that in the case where the MCU 30 performs the counting process in S14, the MCU 30 displays the counting result obtained by performing the counting process in the count value area 104.

[0106] In S15, the MCU 30 determines whether the test conditions, such as image processing and counting algorithms, have changed. When the test conditions change, the MCU 30 returns to S13. When the test conditions have not changed, the MCU 30 proceeds to S16. Note that a change in the test conditions in S8 is assumed to be a change in the test conditions that requires re-acquisition of the image. A change in the test conditions in S15 results in a change in the image processing of the acquired image, but it is assumed that re-acquisition of the image is unnecessary.

[0107] In S16, the MCU 30 determines whether the user has input a registration instruction. The user can input a registration instruction by pressing the second hardware button 8b of the head device 1a assigned as the registration button or the second software button 105b of the UI 100. When the registration instruction has not been input, the MCU 30 returns from S16 to S8 to perform re-shooting or change the test conditions. When the registration instruction is input, the MCU 30 proceeds from S16 to S17.

[0108] In S17, the MCU 30 registers the counting result in the active cell.

[0109] In S18, the MCU 30 determines whether all counting has ended. For example, when the counting results have been input to all cells existing in the counting table, the MCU 30 determines that the counting has ended. When there are still cells with no input, the MCU 30 advances from S18 to S5 and changes the active cell to the next cell (cell identification).

[0110] (3) Registration of Sample Database

[0111] The counting table has multiple rows and columns, and each cell is associated with test conditions. The counting table and test list can be re-created every day. At the same time, there are also cases where the same sample is tested every day. Therefore, when the counting table is pre-registered in the sample DB 40 for a sample with a high test frequency, the burden of the counting table creation process is reduced. Therefore, when the sample table has been created, the user can register the row elements corresponding to each sample in the sample DB 40.

[0112] Figure 15 It is a flowchart showing the edit process of the sample DB 40 executed by the MCU 30 of the PC 1b. The MCU 30 executes the following processes according to the application program 39 stored in the storage device 35.

[0113] In S41, the MCU 30 receives the selection of the row element to be registered in the sample DB 40 among the multiple row elements included in the counting table. For example, the MCU 30 can receive a click of the pointer 57 on any row element among the row elements included in the sample table.

[0114] In S42, the MCU 30 receives an addition instruction for the selected row element. For example, when a right click is performed by the pointer 57 in a state where a row element has been selected, an addition instruction can be input.

[0115] In S43, the MCU 30 obtains the sample name of the row element to be added and determines whether the same sample name has been registered in the sample DB 40 (duplication determination). When there is no row element to be added yet, the MCU 30 proceeds from S43 to S45. When a row element to be added exists in the sample DB 40, the MCU 30 proceeds from S43 to S44.

[0116] In S44, the MCU 30 asks the user whether to overwrite the row element in the sample DB 40. When a cancellation instruction is input, the MCU 30 cancels the addition of the row element. When an overwrite instruction is input, the MCU 30 proceeds from S44 to S45.

[0117] In S45, the MCU 30 obtains the item names (e.g., sample name, bacterial species, culture medium type, or dilution factor) that make up the row element to be added.

[0118] In S46, the MCU 30 obtains the test conditions associated with the unit of the row element from the storage device 35.

[0119] In S47, the MCU 30 registers the item names and test conditions in the sample DB 40.

[0120] In S48, the MCU 30 updates the display of the sample DB 40 in the UI 50.

[0121] (6) Colony counting

[0122] Figure 16 The colony counting process executed by the MCU 20 of the head device 1a according to the control program is shown. However, the image processing and counting processes can be executed by the MCU 30.

[0123] In S81, the MCU 20 obtains a counting algorithm according to the test conditions received from the PC 1b. Specifically, the image processing and threshold parameters (e.g., binarization threshold) used in the counting algorithm are obtained.

[0124] In S82, the MCU 20 applies the counting algorithm to the test image obtained by the main camera 11. For example, image processing such as HDR or ring removal is applied to the test image.

[0125] In S83, the MCU 20 counts the colonies included in the test image according to the test conditions (threshold parameters).

[0126] <Second Embodiment>

[0127] Meanwhile, among users, there are users who create test lists and count sheets by using widely used spreadsheet software (spreadsheet program 41). There are cases where such users are required to introduce the colony counter 1 and switch to an environment where test lists and count sheets are created by the application program 39. In such cases, users sometimes wish to transfer the test lists and count sheets created by the widely used spreadsheet software as assets. Or, sometimes they wish to create test lists and count sheets, or create a profile that serves as a source for test lists and count sheets, by continuously using the widely used spreadsheet software.

[0128] Therefore, in the second embodiment, a function of converting user files (profiles) created by widely used spreadsheet software into test lists and count sheets is proposed.

[0129] (1) Process

[0130] (i) The user creates a test list using the spreadsheet software that has been used. If a test list has already been created, this step is skipped. The format of the electronic file of the test list can be any one of CSV format, Excel (registered trademark) format of Microsoft Corporation, etc.

[0131] (ii) The user transfers the test list using the spreadsheet software to create a profile on the list to be read by the colony counter 1. For example, the user adds cells to the test list using the spreadsheet software and describes label information in the added cells. The user stores the test list with the label information embedded as a profile from the spreadsheet software.

[0132] (iii) The PC 1b performs colony counting based on the profile or by converting the profile into a count sheet for the colony counter 1.

[0133] (2) User files created by spreadsheet software

[0134] (2-1) Business files (count sheets also serve as test lists)

[0135] Figure 17Shows a business document 200 created by a user using a spreadsheet program 41. The business document 200 serves as a counting table, also serves as a test list, or simply serves as a counting table. The name of the sample (sample name) is described in the leftmost column (column). The manufacturing date and time of each sample are described in the second column. The third column describes that the white medium is for general live bacteria and the dilution factor is 1:10. The fourth column describes that the white medium is for general live bacteria and the dilution factor is 1:100. The fifth column describes that the white medium is for general live bacteria and the dilution factor is 1:1000. The sixth column describes that the dark medium is for the Escherichia coli group and the dilution factor is 1:10. The seventh column describes that the dilution factor for Staphylococcus aureus is 1:10. The batch information indicating the manufacturing batch is described in the eighth column. The notes (remarks) are described in the ninth column.

[0136] Users usually print such a business document 200 on paper using a printer and use the business document 200 as a counting table that also serves as a test list.

[0137] (2-2) User file (profile) created using spreadsheet software

[0138] Figure 18 Shows a profile 210 created by a user using a spreadsheet program 41. The profile 210 is created when the user adds tags and strings to the business document 200 using the spreadsheet program 41. For example, the user can create the profile 210 by copying and renaming the business document 200. In this case, both the business document 200 and the profile 210 are maintained in the storage device 35.

[0139] [START] The tag is a label that defines the starting position of the columns (column elements) and rows (row elements) required to create the counting table 55 in the profile 210. The starting position is expressed as the coordinates of a cell and can be expressed as, for example, (starting column, starting row). The tag is a label that defines the ending position of the columns and rows required to create the counting table 55 in the profile 210. The ending position is expressed as the coordinates of a cell and can be expressed as, for example, (ending column, ending row).

[0140] [DATE] The tag indicates the column that describes date and time information such as the manufacturing date and time. The [COUNT] tag indicates the column that includes the counting cells in which the count results of the colonies are entered. Note that Figure 18The two cells corresponding to the fourth and fifth columns from the left in the first row starting from the top are blank. This is an abbreviated description, meaning the label of the cell following the corresponding cell on the left. That is, it indicates that the fourth and fifth columns are also columns each including a count cell according to the [COUNT] label. The [COMMENT] label indicates the column in which the user can freely enter a string.

[0141] [MEDIUMTYPE] label indicates the type of culture medium and the name of the test setting. The test setting information indicates various parameters set in the colony counter 1 (e.g., shooting conditions and image processing conditions). The [FAVORITES] label indicates the name of the test setting pre-registered as the user's favorite among multiple test settings. The [NAME] label indicates the name of the column displayed in the count table 55 (such as the name of the bacterium). The [EARLY] label indicates whether the fast mode is effective. The fast mode is a mode that performs counting at the timing at the end of the culture period predefined by the rule and at an intermediate timing earlier than the end timing. The fast mode has the advantage of being able to identify samples to be discarded and replicated in the middle of a long culture period. The [DILUTION] label indicates the dilution factor. The [ON] label indicates that counting needs to be performed with the default test setting or indicates the effectiveness of the fast mode. For example, in Figure 18 it, the [ON] label is described in a row of the sandwich group. This means that the test setting with the name indicated by the [MEDIUMTYPE] label ("General viable bacteria [background: white]") needs to be applied to the count cell. Assume that "General viable bacteria [background: white]" is associated with General viable bacteria / Setting 1. Looking at the third column, instead of the [ON] label, "General viable bacteria / Setting 2", which is the name of the test setting, is entered as a string for the omelette rice. This indicates that "General viable bacteria / Setting 2" needs to be applied instead of "General viable bacteria [background: white]" (i.e., General viable bacteria / Setting 1, which is the default test setting).

[0142] For the omelette rice, there is no description in the column with a dilution factor of 1:100. This indicates that counting with a dilution factor of 1:100 is not performed for the omelette rice.

[0143] As Figure 18 shown, when performing colony counting for multiple culture conditions or bacterial species for one sample name, the [COUNT] label is described in each corresponding column.

[0144] Figure 19 is a view showing the cell group in the profile 210.

[0145] The cell group CG1 includes one or more cells in which the identification information (sample name) of the test individual is described.

[0146] The cell group CG2 includes cells in which the [DILUTION] label is described and one or more cells in which the actual dilution factor is described. Due to the preservation of the culture conditions, the cell group CG2 may also include cell groups CG4 and CG5.

[0147] The cell group CG3 includes cells corresponding to the respective counting cells in the counting table 55. In each cell of the cell group CG3, the [ON] label indicating that counting needs to be performed with the default test settings, any string indicating that counting needs to be performed with the test settings identified by the described string, a blank (null character) indicating that no counting is to be performed, etc. are described.

[0148] The cell group CG4 includes cells in which the [MEDIUMTYPE] label is described and cells in which a string indicating the name of the default test settings is entered. The blank cells in the cell group CG4 indicate that the test settings of the cells to their right are valid.

[0149] The cell group CG5 includes cells in which the [FAVORITES] label is described and cells in which a string indicating the name of the favorite test settings is entered. The blank cells in the cell group CG5 indicate that the default test settings specified by the [MEDIUMTYPE] label are valid.

[0150] (3) Counting Table

[0151] Figure 20 The counting table 55 created by converting or analyzing the profile 210 is shown in the counting table area 101. When comparing Figure 18 the profile 210 shown with Figure 20 the counting table 55 shown, it should be understood that the positional relationship between the cells of the two is basically preserved. Note that the MCU 30 stores and saves the relationship between the cells in the profile 210 and the corresponding cells in the counting table 55 in the storage device 35. In addition, the test settings are associated with the counting cells 224 among the cells in the counting table 55. The MCU 30 identifies the test settings based on the label information of the cells in the profile 210 and associates the identified test settings with the corresponding counting cells 224.

[0152] When Figure 18 the profile 210 shown with Figure 20When comparing with the counting table 55 shown, the MCU 30 copies the sample names described in the cell group CG1 of the profile 210 to the column of sample names in the counting table 55. The MCU 30 also copies the manufacturing date and time described in the cell specified by the [DATE] tag in the profile 210 to the column of manufacturing date and time in the counting table 55.

[0153] The MCU 30 also copies the dilution factors described in the cell group CG2 identified by the [DILUTION] tag as they are to the row of dilution factors in the counting table 55. In addition, the MCU 30 copies the column names specified by the [NAME] tag to the row that stores the column names in the counting table 55.

[0154] Note that the MCU 30 divides the columns in which the fast mode is enabled by the [EARLY] tag and the [ON] tag into two columns. The first column 227 stores the counting results at the first time (e.g., the time point of 24 h). The second column 228 stores the counting results at the second time (e.g., the time point of 48 h).

[0155] The MCU 30 provides counting cells 224 and 226 in the counting table 55 to correspond to each cell of the cell group CG3 in the profile 210. Here, the MCU 30 can display an icon 225 for confirming or editing the test settings associated with the counting cell 224 in the counting cell 224 where counting is to be performed. For example, the icon 225 is clicked by the pointer 57. The MCU 30 grays out the counting cell 226 where counting is not performed.

[0156] In this way, in the second embodiment, the business file 200 and the profile 210 can be created using the spreadsheet program 41 that is usually used by the user. In addition, the MCU 30 can convert the profile 210 into the counting table 55 of the colony counter 1 according to the conversion or import function installed in the application 39. Therefore, the burden of creating the counting table 55 is reduced.

[0157] (4) Another example of the counting table

[0158] Figure 21 Another example of the counting table 55 created from the profile 210 is shown. In Figure 20 the counting table 55 shown, for one sample name, multiple counting cells 224 and 226 are arranged in a row. However, this is only an example. As Figure 21 shown, rows for inputting counting results can be created for each combination of sample name and dilution factor. In Figure 21In the case where there are three combinations of sample names and dilution factors, the number of rows of the input count results is also three. In this way, the arrangement of cells in the configuration file 210 and the arrangement of cells in the count table 55 do not necessarily coincide with each other.

[0159] (5) Reflection of count results from the count table to the configuration file

[0160] Figure 22 FIG. shows the process in which the count results input to the count cells 224a, 224b, and 224c of the count table 55 are reflected to the configuration file 210 and the service file 200 by the colony counter 1. The MCU 30 stores in the storage device 35 the relationship among the count cells 224a, 224b, and 224c of the count table 55, the cells 237a, 237b, and 237c corresponding to the above count cells in the configuration file 210, and the cells 238a, 238b, and 238c corresponding to the above count cells in the service file 200. For example, the storage device 35 stores cell-interrelationship information indicating that the count cell 224a, the cell 237a, and the cell 238a are related to each other and form a cell group. Similarly, the storage device 35 stores cell-interrelationship information indicating that the count cell 224b, the cell 237b, and the cell 238b are related to each other and form a cell group. In addition, the storage device 35 also stores cell-interrelationship information indicating that the count cell 224c, the cell 237c, and the cell 238c are related to each other and form a cell group. The MCU 30 reflects the count results from the count table 55 to the configuration file 210 and the service file 200 while referring to this relationship. That is, the count results input to the count cells 224a, 224b, and 224c are respectively reflected to the cells 237a, 237b, and 237c and the cells 238a, 238b, and 238c. Note that the reflection of the count results to the configuration file 210 has been described here as an example. However, this is merely an example. The MCU 30 can output the count results as a new file in a format conforming to the data structure stored in the application.

[0161] At the same time, both the configuration file 210 and the service file 200 are created using the spreadsheet program 41. A spreadsheet program 41 such as Excel (registered trademark) of Microsoft Corporation has a cell reference function. For example, a reference to the cell 237a of the configuration file 210 can be described in the cell 238a of the service file 200 (for example, = [configurationfile.xlsx] worksheet name!cell coordinates). Therefore, the count results copied from the count table 55 to the configuration file 210 can be further input to the service file 200.

[0162] (6) Allow blank lines (blank cells)

[0163] Figure 23 Fig. 4 shows the process of converting the profile 210 with blank cells in the cell group CG1 that stores the sample names into the count table 55. Sometimes, users copy the previously created profile 210 to create a new profile 210. Usually, the number of samples to be tested is constant, but there are cases where some samples are lost and excluded from the test target. In such cases, it would be convenient for users if they could easily exclude some of the missing samples from the test target.

[0164] Therefore, as Figure 23 shown, the user deletes the sample names excluded from the test target to obtain blank cells. At this time, it is not necessary to delete the content in the test-specifying cells such as the cell group CG3. The MCU 30 analyzes the profile 210 and, when a blank cell is found in the cell group CG1, ignores all the test-specifying cells in the same row (blank row) as the blank cell and creates the count table 55.

[0165] As Figure 23 shown, the count table 55 does not provide a count row (a row including count cells) corresponding to the blank row that is the same as the blank cell in the cell group CG1 in the profile 210. Therefore, in the count table 55, after the count row of the sandwich group, the count row of the salad bowl is arranged, and the count row of the scrambled egg sandwich is arranged below the count row of the omelette rice.

[0166] In this way, the MCU 30 creates the count table 55 while ignoring blank cells according to the conversion function of the application 39. This makes it possible to easily exclude some of the missing samples from the test target, which is convenient for users.

[0167] Note that even if left, the strings in the test-specifying cells are only ignored, but this is advantageous when restarting the production of some of the missing samples. This is because the test settings of the sample names (enabling the strings in the test-specifying cells) can be restored only by rewriting the sample names in the blank cells.

[0168] (7) Partitioning of Petri dishes

[0169] Sometimes, users use Petri dishes divided into multiple accommodation chambers by partition walls. This is convenient for obtaining multiple count results for different culture conditions (e.g., dilution factors) of the same sample.

[0170] Figure 24The petri dish 15 divided into M (e.g., M = 4) effective regions 231 to 234 by a partition wall is shown. In this case, the MCU 30 needs to divide the effective regions to be counted in the image of the petri dish 15 into M effective regions and perform counting for each of the M effective regions. In order for the colony counting device 1 to perform the above operations, it is complex and troublesome for the user to perform the setting work.

[0171] Figure 25 A method of specifying customized test settings for each sample is shown. In this example, strings "Upper left detection", "Lower left detection", "Upper right detection", and "Lower right detection" indicating the names of test settings pre-registered as preferences are described in the cell group CG3. When a test specification cell including a string indicating the name of a test setting is found in the cell group CG3, the MCU 30 scans the profile 210 and associates the name of the test setting with the corresponding counting cell 224 in the counting table 55. When the user presses the icon 225 displayed in the counting cell 224, the MCU 30 reads the test setting from the storage device 35 based on the name of the test setting associated with the counting cell 224, applies the test setting to the colony counting device 1, and performs counting. By pre-creating test settings named "Upper left detection", "Lower left detection", "Upper right detection", and "Lower right detection", even for a test using the petri dish 15 divided into four effective regions 231 to 234, the user can easily create the counting table 55.

[0172] In this way, any string for specifying the name of a test setting can be described in the test specification cells in the cell group CG3. That is, the user can directly describe the names of test settings in each test specification cell, not limited to the already divided petri dish 15. For example, the user can pre-store in the storage device 35 multiple test settings and shooting settings (e.g., lighting settings, brightness settings, enabling / disabling of anti-glare, enabling / disabling of resolution enhancement, etc.) with different combinations of binarization sensitivity, threshold for small particle removal, degree of shape segmentation, degree of lint removal, sample information (e.g., type of culture medium, diameter of the petri dish, name of bacteria, and amount of sample solution), and describe the names of these test settings in the test specification cells. Therefore, the test settings can be associated with the counting cell 224.

[0173] (8) Refer to the sample DB

[0174] There are cases where a user wishes to constantly associate the same test settings with samples having the same name. If the user remembers the name of a specific test setting as described above, it is sufficient to describe that name in the test designation cell. However, it may be difficult to remember the names of all test settings. At the same time, the test settings are associated with the sample names in the sample DB 40. Therefore, it would be convenient for the user if the test settings for each sample name stored in the sample DB 40 could be associated with the counting cell 224 via the configuration file 210.

[0175] Figure 26 It is a view representing the [SAMPLEDB] tag. The [SAMPLEDB] tag is a tag that can be described in the test designation cell. When the [SAMPLEDB] tag is found during the scan of the configuration file 210, the MCU 30 refers to the sample DB 40 based on the sample name present in the row where the [SAMPLEDB] tag exists, and associates the test settings (the name thereof) associated with the sample name with the test designation cell that describes the [SAMPLEDB] tag. More specifically, the MCU 30 associates the test settings saved in the sample DB 40 with the counting cell 224 of the counting table 55 corresponding to that test designation cell. Therefore, even if the user does not remember the name of a specific test setting associated with the sample name, the test settings can be associated with the counting cell 224.

[0176] (9) Manufacturing date and time, and lot number

[0177] As Figure 18 shown, etc., in the second embodiment, a [COMMENT] tag is prepared. The reason will be described.

[0178] There are cases where a user expects to distinguish multiple samples having the same sample name by the manufacturing date and time and the lot number. For example, when conducting a series of tests in the "Comment" column of the counting table 55, the user can collectively describe the context (e.g., manufacturing date and time, and lot number). Generally, it is necessary to input the information into the comment column of each petri dish. Therefore, it is not easy to effectively input the context information managed by the user into the comment column.

[0179] Therefore, in the second embodiment, it is allowed to add column information corresponding to the context to the configuration file 210. Thus, the addition of data of the type expected by the user is achieved for each sample.

[0180] For the manufacturing date and time, prepare a [DATE] tag dedicated to date and time attributes. The [DATE] tag means that the input string is regarded as date and time information (date and time attributes). The [DATE] tag enables searching using the manufacturing date and time as a key. In addition, when exporting the counting result to a spreadsheet file under the control of the spreadsheet program 41, the MCU 30 can assign a time attribute to the columns of the manufacturing date and time in the spreadsheet file. This can facilitate the user's data management.

[0181] [COMMENT] tag is a tag used to implement the comment column in the counting table 55. In Figure 18 illustrations such as, the name "Lot" can be assigned to the comment column by further combining the use of the [NAME] tag. The MCU 30 can recognize the string "Lot" as an attribute indicating a lot number or the like.

[0182] As Figure 18 shown, by using the [COMMENT] tag and the [DATE] tag, not only the test settings such as the dilution factor are reflected in the counting table 55, but also the lot and the manufacturing date and time of the sample are reflected, and can be managed by the application program 39.

[0183] (10) Average processing

[0184] There are cases where it is desired to culture fungi on multiple petri dishes 15, apply the same test settings (e.g., bacterial species and dilution factor) to the same test target, obtain the counting results in the multiple petri dishes 15, and perform an average process on the multiple counting results. Therefore, the [REPEAT:n] tag is adopted in the second embodiment. When the [REPEAT:n] tag is found during the scanning of the configuration file 210, the MCU 30 recognizes that the same test settings are applied and performs counting n times, and arranges n counting rows with the same test settings in the counting table 55.

[0185] Figure 27 Shows the conversion result (counting table 55) of the configuration file 210 describing the [REPEAT:n] tag. In this example, the [REPEAT:2] tag is described, and the MCU 30 recognizes that counting is performed twice using the default test settings (general live bacteria [background: white]) for the sample names "rice ball" and "fish-shaped bread", and obtains the average value of the two counting results. In the counting table 55, the MCU 30 arranges three counting cells for each of "rice ball" and "fish-shaped bread". The first counting cell stores the first counting result. The second counting cell stores the second counting result. The third counting cell stores the average value of the first counting result and the second counting result.

[0186] In this way, when the [REPEAT:n] tag is found during the scanning of the configuration file 210, the MCU 30 arranges n counting rows in the counting table 55 for the sample names described above the cell with the [REPEAT:n] tag in the cell group CG1. In addition, the MCU 30 also arranges a counting row for storing the average value in the counting table 55.

[0187] Note that, as Figure 27 shown, the MCU 30 can arrange a times column for indicating names such as the first time, the second time, and the average value between the column for storing the sample name and the column for storing the counting result.

[0188] (11) Configuration file without tags

[0189] In the above configuration file 210, the MCU 30 creates the counting table 55 by reading tags such as [START], , [COUNT], or [COMMENT], and associates the predetermined test settings with the counting cells 224. However, the tags can be omitted in the second embodiment.

[0190] Figure 28 A method for creating the counting table 55 according to the configuration file 210 that does not include tags is shown. The storage device 35 pre-stores conversion rules. For example, the conversion rules describe that the sample names are described in column A, the names of the test settings are described in the first row, the names of the fungi are described in the third row, the dilution factors are described in the fifth row, etc. In addition, the conversion rules include copying the sample names described in column A to the column of the sample names in the counting table 55, associating the test settings identified by the names in the first row with the counting cells in the counting table 55, copying the string described in the third row to the cell of the fungi name in the counting table 55, and copying the string described in the fifth row to the cell of the dilution factor in the counting table 55.

[0191] In this way, the conversion rules have rules indicating which cell coordinates in the counting table 55 the strings described in the cells at specific coordinates in the configuration file 210 are copied to. In addition, the conversion rules also have rules indicating the association between the test settings identified by the strings described in the cells at specific coordinates in the configuration file 210 and the corresponding counting cells 224 in the counting table 55. The MCU 30 scans the cells in the configuration file 210 according to the conversion rules, interprets the strings described in the cells at specific coordinates according to the conversion rules, and reflects the strings in the counting table 55.

[0192] Since the conversion rules are pre-stored in the storage device 35 in this way, the MCU 30 can convert the profile 210 into the count table 55 without using tags. Or, it can be said that the user needs to know the conversion rules and then input the string into the predetermined cells in the profile 210 according to the conversion rules.

[0193] (12)Partial customization of test settings

[0194] In Figure 18 , the test settings are specified by the combination of the [ON] tag and the [MEDIUMTYPE] tag, the [FAVORITES] tag, the [SAMPLEDB] tag, or the direct input of the name of the test settings. However, this is only an example. The content of the test settings can be directly described in the test specification cell. For example, if the default test settings have J parameters, all J parameters can be described in the test specification cell. This means that the default test settings are basically not used. Or, K parameters (J > K >= 1) of the J parameters can be described in the test specification cell. In this case, the default test settings are applied to (J - K) of the J parameters, and the test settings described in the test specification cell are applied to K parameters. That is to say, a part of the default test settings can be customized.

[0195] Figure 29 An example of the profile 210 is shown, in which the default test settings can be partially or fully customized. In this embodiment, the set value of the sensitivity and the threshold of small particle removal are directly described in the test name cell of the sample name "sausage". That is to say, in the test settings named "General live bacteria [Background: white]" specified by the [MEDIUMTYPE] tag, only the sensitivity and the threshold of small particle removal are customized to the values specified in the test specification cell. The shooting brightness is directly described in the test name cell of the sample name "frozen pizza". That is to say, in the test environment named "General live bacteria [Background: white]" specified by the [MEDIUMTYPE] tag, only the shooting brightness is customized to the value specified in the test specification cell.

[0196] In this way, the default test settings can be partially or fully customized by directly describing the test parameters in the test specification cell.

[0197] (13)Flowchart

[0198] (13-1)Main flowchart

[0199] Figure 30 Shows the process of converting the profile 210 created by the user using the spreadsheet program 41 into the count table 55 by the application program 39.

[0200] In S91, the MCU 30 reads the configuration file 210 from the storage device 35. The configuration file 210 can be specified through a UI such as a file dialog. Note that the MCU 30 functions as a file reading unit.

[0201] In S92, the MCU 30 searches for the [START] tag in the configuration file 210 and sets the coordinates of the cell where the [START] tag is described as the starting coordinates of the conversion process. In this way, the MCU 30 functions as a tag search unit and a starting coordinate setting unit.

[0202] In S93, the MCU 30 searches for the tag in the configuration file 210 and sets the coordinates of the cell where the tag is described as the ending coordinates of the conversion process. In this way, the MCU 30 functions as a tag search unit and an ending coordinate setting unit.

[0203] In S94, the MCU 30 starts scanning to the right from the cell where the [START] tag is described and searches for cells that describe any tag. In this way, the MCU 30 functions as a cell scanning unit and a tag search unit.

[0204] In S95, the MCU 30 obtains the test column settings corresponding to the found tag. Here, the test column settings are the set of information (e.g., column name, etc.) required to set the corresponding column in the count table 55. According to Figure 18 , the [DATE] tag, [COUNT] tag, and [COMMENT] tag are found. Details of S95 will be referred to later Figure 31 . In this way, the MCU 30 functions as an obtaining unit for obtaining test column settings.

[0205] In S96, the MCU 30 determines whether the scanning position has reached the end column (the column where the tag is described). When 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 tags. When the scanning position reaches the end column, the MCU 30 proceeds from S96 to S97. In this way, the MCU 30 functions as a determining unit. )

[0206] In S97, the MCU 30 starts scanning downward from the cell where the [START] tag is described and searches for cells that describe any tag or sample name.

[0207] In S98, the MCU 30 obtains the test settings for each sample. Details of S98 will be referred to later Figure 32 . In this way, the MCU 30 functions as a test setting obtaining unit.

[0208] In S99, the MCU 30 determines whether the scanning position has reached the end row (the row where the tag is described). When the scanning position is not the end row, the MCU 30 returns to S97, moves the scanning position down one row, and searches for tags. When the scanning position reaches the end row, the MCU 30 proceeds from S96 to S97.

[0209] In S100, when the MCU finds the [REPEAT] tag, the MCU 30 reflects the average setting in the count table 55. In this way, the MCU 30 serves as a tag reflection unit or an average setting reflection unit.

[0210] (13 - 2) Sub - flowchart

[0211] Figure 31 Shows the details of S95.

[0212] In S101, the MCU 30 determines whether the [COUNT] tag has been found. When the [COUNT] tag is found, the MCU 30 proceeds from S101 to S102. Note that when the cell to the right of the cell in which the [COUNT] tag is described is a blank cell, the MCU 30 also proceeds to S102.

[0213] In S102, the MCU 30 identifies the column including the cell in which the [COUNT] tag is described as the count execution column, and obtains the test column settings (e.g., the name of the default test setting, the column name (name of the bacterial species), the dilution factor, and other test settings) from this column.

[0214] In S103, the MCU 30 reflects the obtained test column settings in the count table 55.

[0215] In S101, when the found tag is not the [COUNT] tag, the MCU 30 proceeds from S101 to S104.

[0216] In S104, the MCU 30 determines whether the found tag is the [DATE] tag. When the [DATE] tag is found, the MCU 30 proceeds from S104 to S105.

[0217] In S105, the MCU 30 identifies the column including the cell in which the [DATE] tag is described as the column for managing the manufacturing date and time. Thereafter, 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 described in the column are copied to the corresponding column in the count table 55.

[0218] In S104, when the found tag is not the [DATE] tag, the MCU 30 proceeds from S104 to S106.

[0219] In S106, the MCU 30 determines whether the found tag is the [COMMENT] tag. When the [COMMENT] tag is found, the MCU 30 proceeds from S106 to S107.

[0220] In S107, the MCU 30 identifies the column including the cell in which the [COMMENT] tag is described as a comment column, and obtains the string described in the column (for example, a column name such as "lot number" or "comment"). Thereafter, the MCU 30 proceeds from S106 to S103 and reflects the comment column in the count table 55. For example, the string obtained from the comment column of the configuration file 210 (for example, a column name such as "lot number") is copied to the corresponding column in the count table 55.

[0221] (13 - 3) Sub - flowchart

[0222] Figure 32 Shows the details of S98.

[0223] In S111, the MCU 30 obtains the name of the sample from the configuration file 210. Note that blank cells are skipped.

[0224] In S112, the MCU 30 determines the column type. When the tag indicating the column type is the [COUNT] tag, the MCU 30 proceeds from S112 to S113.

[0225] In S113, the MCU 30 searches for the dilution factor. For example, the dilution factor is obtained from the cell that is the intersection of the [COUNT] tag or a blank cell and the [DILUTION] tag.

[0226] In S114, the MCU 30 moves down from the cell of the dilution factor and branches the process according to the value of the cell. When the value of the cell is [ON], the MCU 30 proceeds from S114 to S115.

[0227] In S115, the MCU 30 identifies the cell in which the [ON] tag is described as a counting cell (test - specified cell), and associates the counting cell with the default test setting specified by the [MEDIUMTYPE] tag. Thus, the default test setting is associated with the counting cell corresponding to the test - specified cell in the configuration file 210 in the count table 55. In this way, the MCU 30 serves as an association unit.

[0228] In S116, it is determined whether the search for the dilution factor has been completed. When there are multiple dilution factors for a sample name, the MCU 30 returns from S116 to S113.

[0229] When the value of the cell in S114 is any string, the MCU 30 proceeds from S114 to S119.

[0230] In S119, the MCU 30 identifies the cell as a test specification cell and associates the count cell 224 corresponding to the test specification cell with the test settings indicated by the string described in the test specification cell. Thus, the test settings specified by the name in the test specification cell in the profile 210 are associated with the count cell 224 corresponding to the test specification cell in the count table 55. Thereafter, the MCU 30 proceeds from S119 to S116.

[0231] When the value of the cell in S114 is [SAMPLEDB], the MCU 30 proceeds from S114 to S120.

[0232] In S120, the MCU 30 identifies the cell as a test specification cell, obtains the test settings corresponding to the sample name from the sample DB 40, and associates the count cell 224 corresponding to the test specification cell with the obtained test settings. Thus, the test settings obtained from the sample DB 40 based on the sample name are associated with the count cell 224 corresponding to the test specification cell in the count table 55. Thereafter, the MCU 30 proceeds from S120 to S116.

[0233] When the value of the cell in S114 is blank, the MCU 30 proceeds from S114 to S121.

[0234] In S121, the MCU 30 identifies the cell as a non-count cell. For example, the MCU 30 can gray out the non-count cell 226 corresponding to the blank test specification cell in the count table 55. Thereafter, the MCU 30 proceeds from S121 to S116.

[0235] When it is determined in S112 that the label indicating the column type is a [DATE] label, the MCU 30 proceeds from S112 to S117.

[0236] 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. Thereafter, the MCU 30 proceeds from S117 to S116.

[0237] When it is determined in S112 that the tag indicating the column type is the [COMMENT] tag, the MCU 30 proceeds from S112 to S118.

[0238] In S118, the MCU 30 acquires the value of the cell as comment information and copies the comment information to the corresponding counting cell 224 in the counting table 55. Thereafter, the MCU 30 proceeds from S118 to S116.

[0239] <Summary>

[0240] [Viewpoint 1]

[0241] The head device 1a is an example of an acquisition unit that acquires an image of colonies generated in a test subject. Note that the MCU 30 can be used as the acquisition unit by reading an image file of colonies specified by the user. The MCU 30 functions as an execution unit that executes the first software (e.g., application program 39), and the execution unit performs a process of counting the number of colonies from the colony image. The MCU 30 functions as a reading unit that reads a user file (e.g., configuration file 210) that stores information in an array format and is created by a second software (e.g., spreadsheet program 4) different from the first software, in order to count the colonies generated in the test subject or manage the counting results of the colonies. In addition, the MCU 30 functions as a creation unit that creates a counting table 55 for counting colonies based on the user file. In this way, since the configuration file 210 created by the spreadsheet program 41 different from the application program 39 that controls the colony counting device 1 is converted into the counting table 55, the burden on the user to create the counting table 55 is reduced. Therefore, the burden on the user for colony counting is reduced.

[0242] [Viewpoint 2]

[0243] The storage device 35 functions as a storage unit that stores a plurality of test settings applied to the test subject (e.g., general viable bacteria [background: white], general viable bacteria / setting 2, Escherichia coli group / dark medium). As Figure 20 shown, the counting table 55 includes a first cell indicating the type of the test subject, a second cell indicating the culture conditions (e.g., dilution factor) applied to the test subject, and a third cell (e.g., counting cell 224) that stores the counting result of the colonies counted by applying the culture conditions indicated by the second cell to the test subject indicated by the first cell. The MCU 30 functioning as a creation unit associates the third cell with any one of the plurality of test settings based on the information described at the position corresponding to the third cell (e.g., the test specification cell in the cell group CG3) in the user file. Therefore, the counting cell 224 can be associated with the test settings using the configuration file 210.

[0244] [Viewpoint 3]

[0245] As Figure 19 shown, the user file may include: a first cell group (e.g., CG1, etc.) that stores type information indicating the type of the test individual; a second cell group (e.g., CG2, etc.) that indicates the culture conditions to be applied to the test individual; and a third cell group (e.g., CG3, etc.) that stores setting information identified by the combination of the type of the test individual and the culture conditions, and is associated with the imaging conditions for acquiring the image to be applied to the test individual or the settings for image processing to be applied to the image. The MCU 30 serving as the creation unit can create the count table 55 by using the type information (e.g., sandwich group) stored in the first cell group as the test individual name in the count table 55 and using the name of the culture conditions (e.g., 1:10, 1:100, etc.) stored in the second cell group as the culture conditions in the count table 55. In this way, since the cells of the profile 210 correspond to the cells of the count table 55, the user can create the profile 210 while understanding the count table 55.

[0246] [Viewpoint 4]

[0247] The settings for image processing may include a detection threshold (e.g., binary sensitivity) for detecting colonies as the counting target from the image, or an exclusion threshold (e.g., a threshold for removing small particles) for particle images to be excluded from the counting target in the image.

[0248] [Viewpoint 5]

[0249] The storage device 35 can serve as a storage unit that stores multiple pieces of pre-prepared setting information. Each cell of the third cell group can be associated with any of the multiple pieces of setting information stored in the storage unit based on the input value of the cell (e.g., a combination of the name assigned to the test setting, [SAMPLEDB] tag, [ON] tag, and [MEDIUMTYPE] tag, etc.). In this way, since there is freedom in the method of specifying the test settings, the user can easily specify the test settings.

[0250] [Viewpoint 6]

[0251] In the counting table 55, the counting result of each combination of the test individual and the culture condition input to the counting cell 224 can be associated with the setting information associated with the cell corresponding to the counting cell in the third cell group of the user file. The MCU 30 clicks the icon 225 of the counting cell 224 in the counting table 55 to apply the test settings associated with the counting cell 224 and cause the colony counting device 1 to perform counting. Here, the association between the counting cell 224 and the test settings can be direct or indirect. In the former case, when creating the counting table 55, the test settings can be identified by the test designation cells of the cell group CG3 in the configuration file 210, and the identified test settings can be associated with the counting cell 224. In the latter case, the counting cell 224 can refer to the test designation cells of the cell group CG3 in the configuration file 210, and when the icon 225 is pressed, the MCU 30 can identify the test designation cell associated with the counting cell 224 and further identify the test settings associated with the test designation cell.

[0252] [Viewpoint 7]

[0253] The third cell group in the user file has test designation cells corresponding to the counting cells 224 in the counting table 55. The test designation cells can store the first string (e.g., [ON]). As Figure 19 shown, the fourth cell group (e.g., CG4) included in the user file can include cells associated with any of the multiple test settings. For example, the cell is a cell corresponding to the first string (e.g., [ON]) described in the test designation cell (e.g., the cell in the row with the [MEDIUMTYPE] label or the [FAVORITES] label). A string (the name of the test setting (e.g., general live bacteria [background: white])) can be described in the cell. The test settings associated with the string described in the cell (e.g., general live bacteria / setting 1) can be associated with the counting cell 224. In this way, a string (e.g., [ON]) indicating that the default test setting is specified can be described in the test designation cell.

[0254] [Viewpoint 8]

[0255] Multiple test settings can include test settings uniquely created or selected by the user according to the culture conditions. As described above, the user can register some of the multiple test settings as preferences. The test designation cell corresponding to the count cell 224 in the fifth cell group in the user file can store a second string (e.g., [ON]). In this case, refer to the fifth cell group (e.g., CG5) included in the user file. The fifth cell group also includes cells associated with any one of the multiple test settings (e.g., the cell in which the string of Escherichia coli group / dark medium is described). The MCU 30 associates the count cell 224 with the test setting (e.g., Escherichia coli group / dark medium) associated with the cell corresponding to the second string. Note that in Figure 19 the case of, the name of the default test setting is described in the cell group CG4, and the name of the test setting registered as a preference is described in the cell group CG5. In Figure 19 the case of, the name of the test setting is described only in the cell group CG4 or CG5. Therefore, when the [ON] tag is described in the cell group CG3, identify the name of the test setting described in the cell group CG4 or CG5. When the name of the test setting is described in both the cell group CG4 and the cell group CG5, the name of the test setting described in the cell group CG5 can be preferentially adopted.

[0256] [Viewpoint 9]

[0257] As Figure 26 shown, the test designation cell corresponding to the count cell 224 in the third cell group can store a third string (e.g., [SAMPLEDB]). In this case, the MCU 30 associates the count cell 224 with the test setting among the multiple test settings that is associated with the test individual (e.g., sample name) corresponding to the test designation cell of the count cell 224. In this way, the count cell 224 can be associated with the test setting stored in the sample DB 40 etc. using the configuration file 210.

[0258] [Viewpoint 10]

[0259] Test settings can be provided for each type of bacteria that forms colonies (e.g., general viable bacteria, Escherichia coli group, and Staphylococcus aureus). The culture conditions applied to the test individual can include the type of bacteria.

[0260] [Viewpoint 11]

[0261] The culture conditions applied to the test individual can include a combination of the type of bacteria and the dilution factor.

[0262] [Viewpoint 12]

[0263] As Figure 19 shown in the figure, in the user file, the third cell group (e.g., CG3) may include multiple cells with different dilution factors for a type of test individual. Each of the multiple cells may include a string indicating the test settings associated with the combination of the type of test individual and the dilution factor. In Figure 19 , it should be specified that for the sandwich group, counting is performed with three dilution factors (1:10, 1:100, and 1:1000). In this case, there are three test - specified cells for each of the three combinations. In Figure 19 , [ON] is described in each of the three test - specified cells, but the name of the test settings such as general live bacteria / setting 2 can be specified. In addition, the strings described in the three test - specified cells are not necessarily the same. That is, the three combinations can specify different test settings from each other.

[0264] [Viewpoint 13]

[0265] The user file may include a cultivation condition in which a multiple - counting mode (e.g., fast mode) is set to be valid. The multiple - counting mode performs a first count at a predetermined time shorter than the specified cultivation time and a second count at the specified cultivation time. In Figure 19 , the fast mode is set to be valid through the [EARLY] tag and the [ON] tag.

[0266] As Figure 20 shown, the creation unit (MCU 30) may create a counting table 55, which includes a first - counting cell in column 227 that stores the result of the first count and a second - counting cell in column 228 that stores the result of the second count for the same test individual. In this way, by creating only one column in the configuration file 210, multiple columns according to the mode are automatically arranged in the counting table 55.

[0267] [Viewpoint 14]

[0268] The acquisition unit may include an imaging unit (e.g., the main camera 11) that captures a test individual and generates a test image of the test individual. The MCU 30 may include a setting unit that sets a first detection parameter for detecting colonies from a first test image of a test individual cultured for a predetermined time and a second detection parameter for detecting colonies from a second test image of a test individual cultured for a specified culture time. Here, the detection sensitivity of the first detection parameter is higher than that of the second detection parameter. The MCU 30 may count the colonies by applying the first detection parameter to the first test image, input the intermediate result into the first counting cell in column 227, and count the colonies by applying the second detection parameter to the second test image, and input the final result into the second counting cell in column 228.

[0269] [Viewpoint 15]

[0270] As Figure 24 shown, the test individual may be accommodated in a test container (Petri dish 15) divided into a plurality of accommodation regions by a separation wall. As Figure 25 shown, the third cell group in the user file may include cells for each accommodation region, which are identified by the combination of the type of test individual, culture conditions, and accommodation region. The cell for each accommodation region may include a string (e.g., "upper left detection") indicating the test settings applied to each accommodation region.

[0271] [Viewpoint 16]

[0272] As described in the reference Figure 25 the test settings indicated by the string (e.g., "upper left detection") stored in the cell associated with the first accommodation region (e.g., the upper left valid region 231) among the plurality of accommodation regions in the third cell group of the user file include: excluding the remaining regions (e.g., valid regions 232 to 234) other than the first accommodation region from the counting target among the plurality of accommodation regions. In the third cell group of the user file, the test settings indicated by the string (e.g., "lower left detection") stored in the cell associated with the second accommodation region (e.g., the lower left valid region 234) among the plurality of accommodation regions include: excluding the remaining regions (e.g., valid regions 231 to 233) other than the second accommodation region from the counting target among the plurality of accommodation regions.

[0273] [Viewpoint 17]

[0274] As described in the reference Figure 22As described, the MCU 30 can be used as a copying unit that copies the count result to the test designated cell corresponding to the count cell 224 in the count table 55 in the profile 210 when the count result is input into the count cell 224 included in the count table 55. In addition, the MCU 30 can copy the count result to the service file 200.

[0275] [Viewpoint 18]

[0276] As referenced Figure 23 described, when a blank cell is found in the first cell group (e.g., CG1), the creating unit (MCU 30) can create the count table 55 while ignoring the row including the blank cell.

[0277] [Viewpoint 19]

[0278] As referenced Figure 27 described, there is a case where the creating unit (MCU 30) finds a label (e.g., [REPEAT: n] label) in the profile 210 that specifies to execute n counts for the same test individual and obtain n count results and a statistical value (e.g., average or standard deviation). In this case, the MCU 30 can arrange n cells for storing n count results and a cell for storing the statistical value in the count table 55.

[0279] [Viewpoint 20]

[0280] As referenced Figure 28 described, the creating unit (MCU 30) can associate the test settings with the count cell 224 in the count table 55 where the count result is stored based on the string described in the cell located at a predetermined coordinate (e.g., B1, C1, B3, C3, B5, C5, or A6 to A7) in the profile 210.

[0281] [Viewpoint 21]

[0282] As referenced Figure 29 described, at least one parameter (e.g., sensitivity: 5.5, small particle removal: 0.3, shooting brightness: 150, etc.) of the multiple parameters constituting the test settings can be described in the cell included in the third cell group. In this case, the creating unit (MCU 30) can customize a part of the test settings associated with the cell to the parameter specified in the cell, and then associate the test settings with the count cell 224 corresponding to the cell in the count table 55.

[0283] [Viewpoint 22]

[0284] The user file can be a CSV format file created using a spreadsheet software (e.g., spreadsheet program 41) as the second software, or a file in the proprietary table format of the spreadsheet software (e.g., xslx format). In particular, the xslx format has become widespread in the market, and there are many users familiar with it. Therefore, users can easily create a configuration file 210 that serves as the basis for the counting table 55 using familiar spreadsheet software.

[0285] [Viewpoint 23]

[0286] As Figure 19As shown, the configuration file 210 is an example of a configuration file that stores information in multiple cells of N rows × M columns. The configuration file 210 may include a first cell that stores the type of the test individual (e.g., sample name), a second cell that stores the culture conditions of the test individual (e.g., dilution factor), a third cell that stores the type of bacteria to be detected (e.g., the cell in the row including the [NAME] tag), and a fourth cell that identifies and indicates the test settings by the combination of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected. For example, the fourth cell may be a test designation cell included in the cell group CG3, the cell in the row including the [MEDIUMTYPE] tag, or the cell in the row including the [FAVORITES] tag. The MCU 30 serves as a reading unit that reads the configuration file 210. The storage device 35 may store a plurality of test settings corresponding to at least one of the type of the test individual and the type of bacteria to be detected, so as to identify the individual test settings corresponding to at least one of the type of the test individual and the type of bacteria to be detected. The MCU 30 serves as a count table generation unit that generates a count table 55 including a plurality of candidate count cells (e.g., count cell 224) in which the count results will be stored, the count results being obtained by counting through a test based on the type of the test individual, the culture conditions of the test individual, the type of bacteria to be detected, and the test settings, the test settings being among the plurality of test settings included in the configuration file 210 read by the reading unit and defined by the combination of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected and indicated by the fourth cell. Here, each of the plurality of candidate count cells is identified by the combination of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected. The display control unit 36 serves as a display control unit that displays the count table 55 generated by the count table generation unit (MCU 30) on a display unit (e.g., display device 37). The pointing device 33 serves as a cell identification unit that identifies a cell for inputting the count result from among the plurality of candidate count cells included in the count table 55 displayed by the display control unit 36. The MCU 30 serves as a test execution unit that acquires a test image that is an image of the test individual based on the test settings and counts the colonies included in the test image. In addition, the MCU 30 serves as a count table editing unit that assigns the count result of the colonies counted by the test execution unit to the cell identified by the cell identification unit.

[0287] [Viewpoint 24]

[0288] The MCU 30 serves as a reading unit for reading a configuration file, which has items such as the type of the test individual, the culture conditions of the test individual, and the types of bacteria to be detected as rows or columns, and has a first test setting corresponding to an array defined by each item. The storage device 35 stores a second test setting corresponding to at least one of the type of the test individual and the types of bacteria to be detected, so as to identify individual test settings corresponding to each of the types of multiple test individuals and each of the types of bacteria to be detected. The MCU 30 can serve as a count table generation unit for generating a count table 55, which includes a plurality of candidate count cells in which count results are to be stored. The count results are obtained by counting through a test based on the type of the test individual, the culture conditions of the test individual, the types of bacteria to be detected, and the first test setting (for example, the information for specifying the test setting stored in the cell group CG3), and the second test setting. The first test setting corresponds to an array defined by a combination of the type of the test individual, the culture conditions of the test individual, and the types of bacteria to be detected included in the configuration file read by the reading unit, and the second test setting corresponds to the first test setting and is stored in the storage unit.

[0289] The present invention is not limited to the above embodiments, and various modifications and changes can be made within the scope of the gist of the present invention.

Claims

1. A colony counting device, comprising: An acquisition unit configured to acquire an image of colonies generated in a test subject; And An execution unit configured to execute a first software, the execution unit being configured to perform a counting process of the number of colonies based on the image of the colonies, Wherein, the execution unit includes: A reading unit configured to read a user file that stores information in an array format and is created by a second software different from the first software, so as to count the colonies generated in the test subject or manage the counting results of the colonies; and A creation unit configured to create a counting table for counting the colonies based on the user file.

2. The colony counting device according to claim 1, further comprising a storage unit configured to store a plurality of test settings applied to the test subject, Among them, The counting table includes: a first cell indicating the type of the test subject; a second cell indicating the culture conditions applied to the test subject; and a third cell, the third cell storing the counting result of the colonies counted by applying the culture conditions indicated by the second cell to the test subject indicated by the first cell, and The creation unit associates the third cell with any one of the plurality of test settings based on the information described at the position corresponding to the third cell in the user file.

3. The colony counting device according to claim 1, wherein, The user file includes: A first cell group storing type information indicating the type of the test subject; A second cell group indicating the culture conditions applied to the test subject; and A third cell group storing test settings identified by a combination of the type of the test subject and the culture conditions, the test settings being associated with imaging conditions for acquiring an image applied to the test subject or settings for image processing applied to the image, and 4. The colony counting device according to claim 3, wherein, The creation unit creates the counting table by using the type information stored in the first cell group as the name of the test subject in the counting table and using the name of the culture conditions stored in the second cell group as the culture conditions in the counting table. The settings for image processing include a detection threshold for detecting colonies as counting targets from the image, or an exclusion threshold for excluding particle images from the counting targets in the image. Among them, 5. The colony counting device according to claim 3, further comprising a storage section configured to store a plurality of test settings prepared in advance, 6. The colony counting device according to claim 5, wherein, Each cell in the third cell group is associated with any test setting stored in the storage section based on the input value of each cell. In the counting table, the counting cell into which the counting result for each combination of the test subject and the culture conditions is input is associated with the test setting associated with the cell in the third cell group of the user file corresponding to the counting cell.

7. The colony counting device according to claim 6, wherein, When the cell in the third cell group of the user file corresponding to the counting cell in the counting table stores a first string, the counting cell is associated with a test setting associated with a cell in a fourth cell group corresponding to the first string. The fourth cell group includes cells associated with any of the plurality of test settings, and the fourth cell group is included in the user file.

8. The colony counting device according to claim 6, wherein the plurality of test settings include test settings created or selected by a user according to the culture conditions, and when the cell in the third cell group of the user file corresponding to the counting cell in the counting table stores a second string, the counting cell is associated with a test setting associated with a cell in a fifth cell group corresponding to the second string. The fifth cell group includes cells associated with any of the plurality of test settings, and the fifth cell group is included in the user file.

9. The colony counting device according to claim 6, wherein, When the cell in the third cell group corresponding to the counting cell stores a third string, the counting cell is associated with a test setting associated with a test individual corresponding to the cell in the plurality of test settings.

10. The colony counting device according to claim 1, wherein, When the user file includes culture conditions in which a multiple counting mode is set to be valid, the creating unit creates a counting table. The multiple counting mode is to perform a first count when a predetermined time shorter than a specified culture time has elapsed and to perform a second count when the specified culture time has elapsed. The counting table includes a first counting cell that stores the result of the first count for the same test individual and a second counting cell that stores the result of the second count.

11. The colony counting device according to claim 10, wherein the obtaining unit includes an imaging unit that is configured to photograph the test individual and generate a test image of the test individual, the executing unit includes a setting unit that is configured to set a first detection parameter and a second detection parameter. The first detection parameter is used to detect the colonies from a first test image of the test individual cultured for the predetermined time, and the second detection parameter is used to detect the colonies from a second test image of the test individual 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, and the executing unit further counts the colonies by applying the first detection parameter to the first test image and inputs an intermediate result into the first counting cell, and counts the colonies by applying the second detection parameter to the second test image and inputs a final result into the second counting cell.

12. The colony counting device according to claim 3, wherein the test individual is accommodated in a test container that is divided into a plurality of accommodation regions by partition walls, and The third cell group of the user file includes cells for each accommodation area in the accommodation areas. The cells are identified by a combination of the type of the test individual, the culture conditions, and the accommodation area, and the cells for each accommodation area in the accommodation areas include a string indicating the test settings applied to each accommodation area in the accommodation areas.

13. The colony counting device according to claim 12, wherein In the third cell group of the user file, the test settings indicated by the string stored in the cell associated with the first accommodation area among the plurality of accommodation areas include: excluding the remaining areas other than the first accommodation area among the plurality of accommodation areas from the counting target, and In the third cell group of the user file, the test settings indicated by the string stored in the cell associated with the second accommodation area among the plurality of accommodation areas include: excluding the remaining areas other than the second accommodation area among the plurality of accommodation areas from the counting target.

14. The colony counting device according to claim 3, wherein, It further includes a copying unit for copying the counting result to the cell corresponding to the counting cell in the user file when the counting result is input into the counting cell included in the counting table.

15. The colony counting device according to claim 1, wherein, When a tag specifying a statistical value obtained by performing n counts on the same test individual and obtaining n counting results is found in the user file, the creating unit arranges n cells for storing n counting results and a cell for storing the statistical value in the counting table.

16. The colony counting device according to claim 1, wherein, The creating unit associates the test settings with the counting cells in the counting table where the counting results are stored based on the string described in the cell located at a predetermined coordinate in the user file.

17. The colony counting device according to claim 3, wherein, When at least one parameter among the plurality of parameters constituting the test settings is described in the cell included in the third cell group, the creating unit customizes a part of the test settings associated with the cell to the at least one parameter, and then associates the test settings with the counting cell corresponding to the cell in the counting table.

18. The colony counting device according to claim 1, wherein, The user file is a CSV format file created using a spreadsheet software as the second software or a file in a specific table format of the spreadsheet software.

19. A colony counting device, comprising: A reading unit for reading a configuration file that stores information in a plurality of cells of N rows × M columns. The configuration file includes a first cell storing the type of the test individual, a second cell storing the culture conditions of the test individual, a third cell storing the type of bacteria to be detected, and a fourth cell identified by a combination of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected and indicating the test settings. A storage unit for storing a plurality of test settings corresponding to at least one of the type of the test individual and the type of bacteria to be detected, to identify individual test settings corresponding to at least one of the type of the test individual and the type of bacteria to be detected. A count table generation unit for generating a count table, the count table including a plurality of candidate count cells in which count results are to be stored, the count results being based on a combination of the type of the test individual, the culture conditions of the test individual, the type of bacteria to be detected, and a plurality of test settings included in the configuration file read by the reading unit, the combination being defined by the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected and indicated by the fourth cell, and being obtained by counting through a test, wherein each of the plurality of candidate count cells is identified by a combination of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected; A display control unit for displaying the count table generated by the count table generation unit on a display unit; A cell identification unit for identifying, from the plurality of candidate count cells included in the count table displayed by the display control unit, a cell for inputting the count result; A test execution unit for obtaining a test image that is an image of the test individual based on the test settings and counting colonies included in the test image; and A count table editing unit for assigning the count result of the colonies counted by the test execution unit to a cell identified by the cell identification unit.

20. A colony counting device, comprising: A reading unit for reading a configuration file, the configuration file having items of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected as rows or columns, and having a first test setting corresponding to an array defined by the items; A storage unit for storing a second test setting corresponding to at least one of the type of the test individual and the type of bacteria to be detected to identify an individual test setting corresponding to each of a plurality of types of the test individuals or each of a plurality of types of the bacteria to be detected; A count table generation unit for generating a count table, the count table including a plurality of candidate count cells storing count results, the count results being obtained by counting through a test based on the type of the test individual, the culture conditions of the test individual, the type of bacteria to be detected, the first test setting, and the second test setting, the first test setting corresponding to an array defined by a combination of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected included in the configuration file read by the reading unit, the second test setting corresponding to the first test setting and stored in the storage unit, and each of the plurality of candidate count cells being identified by a combination of the type of the test individual, the culture conditions of the test individual, and the type of bacteria to be detected; A display control unit for displaying the count table generated by the count table generation unit on a display unit; A cell identification unit for identifying, from the plurality of candidate count cells included in the count table displayed by the display control unit, a cell for inputting the count result; A test execution unit, configured to obtain a test image that is an image of the test individual based on the second test setting, and count colonies included in the test image; and A count table editing unit, configured to assign the count result of the colonies counted by the test execution unit to the cells identified by the cell identification unit.

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