Data processing device, data processing method, and data processing program

Abstract

A data processing device, a data processing method, and a program are provided that allow for easy evaluation of embryos obtained by in vitro fertilization. [Solution] The data processing device includes an acquisition unit that acquires microscopic image data of an embryo obtained by in vitro fertilization and request text data representing a request for evaluation of the embryo depicted in the microscopic image data, an evaluation unit that inputs the microscopic image data and the request text data into a data generation model and acquires evaluation data of the embryo depicted in the microscopic image data output from the data generation model, which evaluation data corresponds to the request text data, and an output unit that outputs the evaluation data of the embryo.

Description

Technical Field

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[0001] The technology of the present disclosure relates to a data processing apparatus, a data processing method, and a data processing program.

Background Art

[0002] Patent Document 1 discloses an apparatus, a method, and a system for image-based human embryo cell classification.

[0003] Patent Document 2 discloses an artificial intelligence (AI) computing system for generating an embryo viability score from a single image of an embryo to contribute to the selection of an embryo for implantation in the in vitro fertilization (IVF) method.

[0004] Patent Document 3 discloses a system for predicting the viability of one or more embryos. The system disclosed in Patent Document 3 may include receiving a single image of an embryo via a real-time communication link with an image capture device and generating a viability score for the embryo by classifying the single image via at least one convolutional neural network.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Patent Document 2

Patent Document 3

Summary of the Invention

Problems to be Solved by the Invention

[0006] Incidentally, when a system evaluates embryos obtained through in vitro fertilization, it is preferable that the evaluation be performed in a way that the user desires. For example, if the user wants to know the predicted implantation rate of the embryo, it is preferable that the system immediately output the implantation rate. Also, if the user wants to know the grade of the embryo, it is preferable that the system immediately output the grade of the embryo. Furthermore, if there is any supplementary information about the embryo being evaluated, it is preferable that the system also takes that supplementary information into account when evaluating the embryo. Such a system needs to interact with the user.

[0007] In this regard, there is room for improvement in the conventional technology. Specifically, the input data in the technologies disclosed in the above-mentioned Patent Documents 1 to 3 is limited to image data of embryos, and it is not possible to handle text data input by the user. Therefore, the technologies disclosed in the above-mentioned Patent Documents 1 to 3 have the problem that they cannot evaluate embryos obtained by in vitro fertilization while interacting with the user. [Means for solving the problem]

[0008] A first aspect of the technology of this disclosure is a data processing device comprising: an acquisition unit that acquires microscopic image data of an embryo obtained by in vitro fertilization and request text data representing an evaluation request for the embryo captured in the microscopic image data; an evaluation unit that inputs the microscopic image data and the request text data to a data generation model and acquires evaluation data of the embryo captured in the microscopic image data output from the data generation model, which corresponds to the request text data; and an output unit that outputs the evaluation data of the embryo.

[0009] A second aspect of the technology of this disclosure is a data processing method that includes acquiring microscopic image data of an embryo obtained by in vitro fertilization and request text data representing an evaluation request for the embryo shown in the microscopic image data, inputting the microscopic image data and the request text data into a data generation model, acquiring evaluation data of the embryo shown in the microscopic image data output from the data generation model that corresponds to the request text data, and outputting the evaluation data of the embryo.

[0010] A third aspect of the technology of this disclosure is a program for causing a computer to perform a process that includes acquiring microscopic image data of an embryo obtained by in vitro fertilization and request text data representing a request for evaluation of the embryo shown in the microscopic image data, inputting the microscopic image data and the request text data into a data generation model, acquiring evaluation data of the embryo shown in the microscopic image data output from the data generation model that corresponds to the request text data, and outputting the evaluation data of the embryo. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a user terminal. [Figure 3] This is a diagram illustrating embryos obtained through in vitro fertilization. [Figure 4] The functional configuration of a specific processing unit of a data processing device is shown in general terms. [Figure 5A] This is an example of a screen displayed on a user's terminal. [Figure 5B] This is an example of a screen displayed on a user's terminal. [Figure 5C] This is an example of a screen displayed on a user's terminal. [Figure 6] This diagram outlines an example of the operation flow of a specific process performed by a data processing device.

Best Mode for Carrying Out the Invention

[0012] Hereinafter, an example of an embodiment of a data processing apparatus, a data processing method, and a program according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0013] First, the terms used in the following description will be explained.

[0014] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), or an APU (Accelerated Processing Unit), etc.

[0015] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0017] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0019] FIG. 1 shows an example of the configuration of the data processing system 10 according to the embodiment.

[0020] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a user terminal 14. An example of the data processing device 12 is a server. Examples of the user terminal 14 include a personal computer or a smartphone. In this embodiment, the data processing device 12 is an example of the "data processing device" according to the technology of the present disclosure, and the user terminal 14 is an example of the "terminal" according to the technology of the present disclosure.

[0021] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0022] The user terminal 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0023] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0024] The output device 40 includes a display 40A and a speaker 40B, and presents data to the person 20 by outputting the data in a form perceptible to the person 20 (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs sound according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0025] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0026] Figure 2 shows an example of the main functions of the data processing device 12 and the user terminal 14.

[0027] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0028] The storage 32 stores the data generation model 58. The data generation model 58 is used by the specific processing unit 290.

[0029] At the user terminal 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 62. The reception output program 62 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 62 from the storage 50 and executes the read reception output program 62 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 62 executed on the RAM 48.

[0030] Next, we will describe the processing performed by the identification processing unit 290 when the data processing device 12 performs specific processing to evaluate embryos obtained by in vitro fertilization.

[0031] Figure 3 is a diagram illustrating embryos obtained through in vitro fertilization (IVF). As shown in Figure 3, embryos obtained through IVF progress through the 2-cell stage, 4-cell stage, and 8-cell stage to become morulas, and then blastocysts. The blastocysts are then transferred back into the uterus to encourage implantation. For example, the embryos shown in Figure 3 are visually inspected by a doctor or other medical professional, and only those in good condition are selected and transferred back into the uterus. However, the criteria for evaluating embryos through visual inspection are ambiguous, and evaluation results can vary. For example, one doctor may rate an embryo as "good" based on a microscopic image, while another doctor may rate the same embryo as "poor."

[0032] Therefore, in this embodiment, the data generation model 58, described later, is used to evaluate embryos obtained by in vitro fertilization. This reduces the variability in the evaluation results of embryos obtained by visual inspection. Furthermore, as will be described later, since the data generation model 58 can also handle textual data, it is possible to perform evaluations of the target embryos as desired by the user while interacting with the model.

[0033] As shown in Figure 4, the specific processing unit 290 includes an acquisition unit 292, an evaluation unit 294, and an output unit 296.

[0034] The acquisition unit 292 acquires user input received by the user terminal 14. Specifically, it acquires at least one of the user's text, voice, and image data received by the user terminal 14. In this embodiment, the user is, for example, a doctor.

[0035] Specifically, the acquisition unit 292 acquires microscopic image data of an embryo obtained by in vitro fertilization, which is input by the user, and request text data that represents a request for evaluation of the embryo shown in the microscopic image data.

[0036] Figures 5A to 5C show examples of screens displayed on the display 40A of the user terminal 14. The acquisition unit 292 of the data processing device 12 displays screens like those shown in Figures 5A to 5C on the display 40A of the user terminal 14.

[0037] On the left side of the screen shown in Figure 5A, the training data, which is the data used to train the data generation model 58, is displayed. On the right side of the screen shown in Figure 5A, there is a field for entering microscopic image data of the embryo to be analyzed (the "Upload Image" section in Figure 5A). In addition, on the right side of the screen shown in Figure 5A, there is a field for entering supplementary information about the embryo to be analyzed. This field can accept text data entered by the user.

[0038] As shown in Figure 5B, when the microscopic image data to be analyzed is input, the request text data "Analyze the implantation rate of this embryo" is entered in the field for inputting supplementary information, and the "Start Analysis" button is clicked, the acquisition unit 292 acquires the microscopic image data and the request text data. The text data "Analyze the implantation rate of this embryo" also serves as a prompt to the data generation model 58.

[0039] The evaluation unit 294 performs specific processing using the data generation model 58. Specifically, the evaluation unit 294 inputs the microscopic image data acquired by the acquisition unit 292 and the request text data to the data generation model 58 and obtains embryo evaluation data as the result. More specifically, the evaluation unit 294 acquires evaluation data of embryos captured in the microscopic image data output from the data generation model 58, and evaluation data that corresponds to the request text data.

[0040] The output unit 296 transmits evaluation data, which is the result of a specific process, to the user terminal 14. On the user terminal 14, the control unit 46A causes the output device 40 to output the evaluation data, which is the result of the specific process, to the display 40A.

[0041] Figure 5C shows an example of evaluation data displayed on the display 40A. The evaluation data shown in Figure 5C includes the implantation rate of embryos captured in the microscopic image data, the embryo grade, and text data representing the evaluation of the embryos.

[0042] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0043] Furthermore, users can further train and fine-tune the data generation model 58 by clicking the "Additional Training" button on the screen shown in Figure 5A. In this case, for example, the acquisition unit 292 acquires training data which is a combination of training microscopic image data showing a different embryo from the embryo shown in the microscopic image data to be analyzed, and training microscopic image data showing a different embryo provided by the patient who provided the embryo shown in the microscopic image data to be analyzed, and training evaluation data for said training microscopic image data.

[0044] Next, the evaluation unit 294 generates a new data generation model 58 for the patient by fine-tuning the data generation model 58 using a known machine learning algorithm based on the training data. Then, the evaluation unit 294 inputs the microscopic image data to be analyzed into the new data generation model 58 for the patient and obtains evaluation data of the embryos shown in the microscopic image data output from the new data generation model 58 for the patient. In this way, the evaluation unit 294 can generate evaluation data that is more tailored to the target patient by fine-tuning the data generation model 58 for the patient.

[0045] Furthermore, in the "Supplementary Information" field of the screen shown in Figure 5A, users can input various textual data as prompt request data. For example, they can input textual data regarding the specific circumstances of the patient who provided the embryo to be analyzed.

[0046] Furthermore, the user may upload time-series data (growth data) of microscopic image data representing the growth process of a single embryo, rather than a single microscopic image data, in the "Upload Image" field on the screen shown in Figure 5A. In this case, the acquisition unit 292 acquires growth data, which is time-series data of microscopic image data showing embryos provided by the same patient, and which represents the growth process of a single embryo. The evaluation unit 294 inputs the growth data acquired by the acquisition unit 292 and the request text data into the data generation model 58. The data generation model 58 outputs evaluation data corresponding to the input growth data. The evaluation unit 294 acquires the evaluation data output from the data generation model 58. The evaluation unit 294 may also extract feature data from the microscopic image data using known image processing techniques and input that feature data into the data generation model 58.

[0047] Furthermore, Figure 5C shows an example where the evaluation data includes the implantation rate of embryos captured in the microscopic image data, the embryo grade, and text data representing the evaluation of the embryos. However, it is also possible to output only the evaluation data corresponding to the requested text data. For example, if the requested text data is "Calculate only the implantation rate," the data generation model 58 will output only the implantation rate as evaluation data. Similarly, if the requested text data is "Output only the grade," the data generation model 58 will output only the embryo grade as evaluation data. In this way, by using the data generation model 58, which can handle text data, when evaluating embryos captured in microscopic image data, the evaluation desired by the user can be performed more flexibly.

[0048] Next, the operation of the data processing system 10 will be explained.

[0049] An example of the flow of a specific processing method will be explained with reference to Figure 6. Note that the flow of a specific processing method shown in Figure 6 is an example of a "data processing method" related to the technology disclosed herein.

[0050] In step S300, the acquisition unit 292 acquires the microscopic image data of the embryo to be analyzed and the request text data, which are input by the user.

[0051] In step S301, the evaluation unit 294 inputs the microscopic image data of the embryo acquired in step S300 and the request text data into the data generation model 58.

[0052] In step S302, the evaluation unit 294 acquires evaluation data of embryos captured in the microscope image data output from the data generation model 58, which corresponds to the requested text data.

[0053] In step S303, the output unit 296 outputs evaluation data to the user terminal 14 and terminates the specific processing.

[0054] As described above, the data processing device of this embodiment acquires microscopic image data of an embryo obtained by in vitro fertilization and request text data representing the evaluation request for the embryo shown in the microscopic image data. The data processing device inputs the microscopic image data and the request text data into a data generation model and acquires evaluation data for the embryo shown in the microscopic image data, which corresponds to the request text data, output from the data generation model. The data processing device outputs the embryo evaluation data. This makes it possible to easily evaluate embryos obtained by in vitro fertilization. It also reduces the variability in the evaluation results of embryos obtained by visual inspection by doctors, etc. Furthermore, by using a data generation model that can handle text data, it is possible to perform evaluations of the target embryo as desired by the user while interacting with the user.

[0055] The data processing device of this embodiment is realized through AI (Artificial Intelligence)-based embryo evaluation technology for in vitro fertilization. In this embodiment, the AI ​​analyzes microscopic images or embryo growth data of the embryo to identify embryos with a high probability of implantation. This can lead to improved treatment success rates and an increase in the birth rate of healthy babies. Furthermore, it can reduce the burden on infertile patients, improve their satisfaction, and enable the efficient use of medical resources. It can also enable the provision of individualized treatment plans and support to patients.

[0056] The above description primarily focuses on the functions of the data processing device 290 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer, or as an application that runs on a smartphone, etc. The method related to this disclosure may be provided to users in the form of SaaS (Software as a Service).

[0057] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0058] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0059] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0060] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0061] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0062] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0063] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0064] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0065] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0066] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. [Explanation of symbols]

[0067] 10 Data Processing Systems 12 Data Processing Devices 14 User terminals 290 Specific Processing Unit 292 Acquisition Department 294 Evaluation Department 296 Output section< / url:>

Claims

1. An acquisition unit that acquires microscopic image data of an embryo obtained by in vitro fertilization and request text data representing an evaluation request for the embryo shown in the microscopic image data, An evaluation unit inputs the aforementioned microscope image data and the aforementioned request text data into a data generation model, and acquires evaluation data of the embryo captured in the microscope image data output from the data generation model, which corresponds to the aforementioned request text data. An output unit that outputs the evaluation data of the embryo, Includes, The evaluation data includes the grade of the embryo corresponding to the evaluation of at least one of the embryo's blastomeres and embryo fragments as seen in the microscopic image data. Data processing device.

2. The acquisition unit acquires learning data which is a combination of learning microscopic image data showing a different embryo from the embryo shown in the microscopic image data, and learning microscopic image data showing a different embryo provided by the patient who provided the embryo shown in the microscopic image data, and learning evaluation data for the learning microscopic image data. The evaluation unit generates a new data generation model for the patient by fine-tuning the data generation model based on the training data. The microscopic image data is input to the new data generation model for the patient, and evaluation data of the embryos captured in the microscopic image data output from the new data generation model for the patient is obtained. The data processing device according to claim 1.

3. The evaluation data further includes at least one of the implantation rate of the embryos captured in the microscope image data and text data representing the evaluation of the embryos. A data processing device according to claim 1 or claim 2.

4. The acquisition unit acquires growth data, which is time-series data of microscopic image data showing embryos provided by the same patient, and which represents the process of growth of a single embryo. The evaluation unit inputs the growth data and the request document data into the data generation model and obtains the evaluation data output from the data generation model. A data processing device according to claim 1 or claim 2.

5. The data generation model is pre-trained based on microscopic image data of embryos that successfully implanted and microscopic image data of embryos that did not implant. A data processing device according to claim 1 or claim 2.

6. Microscopic image data of an embryo obtained by in vitro fertilization and request text data representing an evaluation request for the embryo shown in the microscopic image data are obtained. The microscope image data and the request text data are input to the data generation model, and evaluation data of the embryo captured in the microscope image data output from the data generation model, which corresponds to the request text data, is obtained. Output evaluation data of the aforementioned embryo. A data processing method in which a computer performs a process that includes the following: The evaluation data includes the grade of the embryo corresponding to the evaluation of at least one of the embryo's blastomeres and embryo fragments as seen in the microscopic image data. Data processing method.

7. Microscopic image data of an embryo obtained by in vitro fertilization and request text data representing an evaluation request for the embryo shown in the microscopic image data are obtained. The microscope image data and the request text data are input to the data generation model, and evaluation data of the embryo captured in the microscope image data output from the data generation model, which corresponds to the request text data, is obtained. Output evaluation data of the aforementioned embryo. A program that causes a computer to perform a process that includes the following: The evaluation data includes the grade of the embryo corresponding to the evaluation of at least one of the embryo's blastomeres and embryo fragments as seen in the microscopic image data. program.

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