Ophthalmic system and operative eye identification method

Abstract

To provide an ophthalmic system and an operative eye determination method capable of efficiently suppressing a mistake of mistaking an operative eye which is an eye of a patient to be operated.SOLUTION: An ophthalmic system includes an imaging device configured to acquire a body image including at least an upper body of a patient in a state where a face of the patient is covered with a cover sheet having an opening for an operative eye which is an eyeball to be operated on, a processor configured to determine the operative eye based on operative eye determination information obtained from the body image and preliminary examination operative eye data of the patient registered as a result of a preliminary examination, and a notification device configured to notify an operator of a determination result of the operative eye.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present disclosure relates to an ophthalmic system and a method for identifying a patient's eye. [Background technology]

[0002] Surgeries for inserting intraocular medical devices (e.g., intraocular lenses) have been known for some time. In such surgeries, there is a possibility that mistakes may occur, such as mistaking the patient's eye for the surgery. To prevent such mistakes, for example, Patent Document 1 discloses an ophthalmologic information processing device that processes information about the patient's eye into which an intraocular medical device is to be inserted.

[0003] This ophthalmologic information processing device acquires patient eye information, which is information created before surgery is performed and is information in which a plurality of pieces of information are associated with each patient's eye, including planned-to-be-inserted medical instrument information identifying the intraocular medical instrument to be inserted into the patient's eye and pre-operative image information, which is image information of the anterior segment of the patient's eye before surgery. The ophthalmologic information processing device acquires intra-operative image information, which is image information of the anterior segment of the patient's eye at the time of surgery, and acquires prepared medical instrument information, which identifies the intraocular medical instrument prepared for the surgery. The ophthalmologic information processing device identifies the patient's eye on which surgery is to be performed by comparing the planned-to-be-inserted medical instrument information associated with the patient's eye with the prepared medical instrument information, and determines whether surgery preparations for the patient's eye are appropriate by comparing the planned-to-be-inserted medical instrument information and the prepared medical instrument information, which are associated with the patient's eye. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6805581 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the ophthalmologic information processing device described in Patent Document 1 has the following problems.

[0006] In order to obtain intraoperative image information, which is image information of the anterior segment of a patient's eye during surgery, a special imaging device is required to capture an image of the patient's anterior segment immediately before the start of surgery. Furthermore, capturing the image is time-consuming, and the captured image must be subjected to predetermined image processing to extract characteristic features, which creates a challenge for medical professionals. This can result in a certain amount of time being required before surgery can begin, potentially increasing the burden on the patient.

[0007] The present disclosure has been made in consideration of the above circumstances, and aims to provide an ophthalmologic system and a method for identifying the surgical eye that can efficiently prevent mistakes in identifying the surgical eye, which is the patient's eye that will undergo surgery. [Means for solving the problem]

[0008] One aspect of the ophthalmologic system of the present disclosure provides an ophthalmologic system comprising: an imaging device that captures a body image including at least the upper body of a patient while the patient's face is covered with a covering sheet having an opening through which the surgical eye, which is the eyeball to be operated on, can be exposed; a processor that judges the surgical eye based on surgical eye judgment information obtained from the body image and the patient's pre-examination surgical eye data registered as a result of the pre-examination; and an alarm device that notifies the surgeon of the judgment result of the surgical eye.

[0009] In the ophthalmologic system, a determination is made as to whether the patient's surgical eye is the left or right eye based on preoperative assessment information obtained from a body image captured by an imaging device, for example, before the start of surgery, and preoperative examination data on the patient's surgical eye, which is registered as a result of a preoperative examination. The determination result is then notified to the surgeon by a notification device. This makes it possible to efficiently prevent mistakes in identifying the patient's surgical eye.

[0010] In another aspect of the ophthalmologic system of the present disclosure, the processor inputs an image of the cover sheet covering the patient's face and determines the patient's eye by referring to a machine learning model that has been trained to output whether the patient's left or right eyeball is exposed through the opening in the cover sheet.

[0011] In the ophthalmology system, the processor determines the operated eye by referring to a machine learning model. This machine learning model is generated by machine learning so that an image of a patient's face covered with a cover sheet is input and the model outputs whether the patient's left or right eye is exposed through the opening in the cover sheet. This makes it possible for the ophthalmology system to accurately determine whether the patient's operated eye is the left eye or the right eye using the machine learning model generated by machine learning before surgery.

[0012] In another aspect of the ophthalmologic system of the present disclosure, the machine learning model is generated by machine learning using images of multiple types of the covering sheets and images of multiple types of the covering sheets covering a patient's face as training data.

[0013] Furthermore, in the ophthalmologic system, as learning data for the machine learning model, not only images of multiple types of cover sheets but also images of multiple types of cover sheets covering the patient's face are used. As a result, the ophthalmologic system allows the machine learning model to accurately detect the cover sheet to be placed on the patient before surgery, and enables the surgeon to accurately determine whether the patient's eye to be operated on is the left or right eye through the opening in the cover sheet.

[0014] In another aspect of the ophthalmologic system of the present disclosure, the imaging device is an operating room camera placed in an operating room where surgery is performed or a worn camera worn by the surgeon for surgery.

[0015] In addition, in the ophthalmology system, the imaging device can be a general-purpose operating room camera that is pre-installed in the operating room where the surgery will be performed, or a camera already in use for surgery that the surgeon is already wearing. Because such a general-purpose camera can be used, there is no need for a special imaging device to capture images of the patient's surgical eye before the surgery. Furthermore, there is no need to perform image analysis processing on the images captured by such an imaging device, so the patient does not have to wait longer than necessary for the surgery to begin, and the surgery can be carried out quickly.

[0016] In addition, one aspect of the terminal device of the present disclosure further includes a communication unit that communicates data with a server device that stores past surgical eye data, which is data on the surgical eye previously acquired for the patient, and the processor compares the pre-examination surgical eye data with the past surgical eye data acquired from the server device via the communication unit for the surgical eye of the same patient.

[0017] In the ophthalmologic system, the processor compares the pre-examination surgical eye data with the past surgical eye data acquired from a server device that stores past surgical eye data, which is data on the patient's surgical eye previously acquired. This makes it possible to determine before surgery whether the patient's surgical eye indicated by the pre-examination surgical eye data matches the patient's surgical eye indicated by the past surgical eye data.

[0018] In another aspect of the terminal device of the present disclosure, when the pre-examination surgical eye data and the past surgical eye data match as a result of the comparison, the processor makes a judgment on the surgical eye using the surgical eye judgment information and the pre-examination surgical eye data.

[0019] Furthermore, in the ophthalmologic system, when the pre-examination surgical eye data and the past surgical eye data match, the processor determines the patient's surgical eye using the surgical eye judgment information and the pre-examination surgical eye data. This makes it possible to effectively prevent mistakes about the patient's surgical eye before surgery by performing a double check, with the pre-examination surgical eye data and the past surgical eye data being matched as a primary match and the surgical eye judgment information and the pre-examination surgical eye data being matched as a secondary match.

[0020] In another aspect of the terminal device of the present disclosure, the processor issues a pre-operative warning via the alarm device when the surgical eye of the patient indicated by the surgical eye judgment information obtained from the body image does not match the surgical eye of the patient indicated by the patient's pre-examination surgical eye data registered as a result of the pre-examination.

[0021] In addition, in the ophthalmology system, if the patient's surgical eye indicated by the surgical eye judgment information obtained from the body image does not match the patient's surgical eye indicated by the patient's pre-examination surgical eye data registered as a result of the pre-examination, the processor issues a pre-operative warning using the notification device. As a result, according to the ophthalmology system, if the surgeon mistakenly identifies the patient's surgical eye, which should not occur, the pre-operative warning can prompt the surgeon to redo the pre-operative preparations.

[0022] In another aspect of the terminal device of the present disclosure, the processor notifies the patient of permission for surgery via the notification device when the patient's surgical eye indicated by the surgical eye judgment information obtained from the body image matches the patient's surgical eye indicated by the patient's pre-examination surgical eye data registered as a result of the pre-examination.

[0023] In addition, in the ophthalmologic system, when the patient's surgical eye indicated by the surgical eye judgment information obtained from the body image matches the patient's surgical eye indicated by the patient's pre-examination surgical eye data registered as a result of the pre-examination, the processor issues permission for surgery via the notification device. As a result, according to the ophthalmologic system, the surgeon correctly recognizes whether the patient's surgical eye is the left eye, the right eye, or both eyes based on the judgment of the pre-examination surgical eye data and the surgical eye judgment information obtained immediately before surgery, allowing the start of surgery to be carried out safely.

[0024] Another aspect of the terminal device of the present disclosure provides a surgical eye discrimination method, which includes: confirming the surgical eye, which is the eyeball to be operated on, by comparing the patient's pre-examination surgical eye data obtained as a result of a pre-examination with past surgical eye data, which is data related to the patient's surgical eye in the past; capturing a body image including at least the upper body of the patient with the patient's face covered by a covering sheet having an opening; determining the surgical eye based on surgical eye judgment information obtained from the body image and the patient's pre-examination surgical eye data that is determined to match the past surgical eye data as a result of the comparison; and notifying the surgeon of the determination result of the surgical eye.

[0025] In the surgical eye identification method, when a patient's surgical eye data for the pre-examination, registered as a result of a pre-surgery examination, matches with previous surgical eye data for the same patient previously acquired, the patient's surgical eye is identified using the surgical eye determination information and the pre-examination surgical eye data. This determination determines whether the surgical eye is the left eye or the right eye, and the result of this determination is notified to the surgeon. Thus, the surgical eye identification method effectively prevents misidentification of a patient's surgical eye before surgery by performing a double check, with the pre-examination surgical eye data being compared with the previous surgical eye data as a primary comparison and the pre-examination surgical eye determination information and the pre-examination surgical eye data being compared as a secondary comparison. [Effects of the Invention]

[0026] According to the present disclosure, mistakes in mixing up the patient's eye to be operated on can be efficiently prevented. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is an overall view of an ophthalmologic system according to an embodiment of the present invention. [Figure 2] 2 is a block diagram showing an example of the hardware configuration of each of a server device and a terminal device according to the present embodiment. FIG. [Figure 3] FIG. 10 is a diagram showing an example of the arrangement of an operating field camera and an operating field monitor. [Figure 4] FIG. 1 shows an example of a drape used to cover a patient before surgery. [Figure 5] FIG. 1 is a diagram illustrating an example of learning data used in machine learning. [Figure 6] 10 is a flowchart showing an example of an operation procedure of a terminal device according to the present embodiment in chronological order. DETAILED DESCRIPTION OF THE INVENTION

[0028] An example of the present disclosure will be described below using the drawings, but the scope of the present disclosure is not limited to the embodiment described here, and various modifications can be made without departing from the spirit of the present disclosure.

[0029] 1. Ophthalmology system configuration First, with reference to FIG. 1, an example of the configuration of an ophthalmologic system 1 according to the present embodiment will be described.

[0030] FIG. 1 is an overall view of an ophthalmologic system 1 according to this embodiment. The ophthalmologic system 1 is composed of a plurality of ophthalmologic apparatuses, a server device 20, and a plurality of terminal devices 30A, 30B, 30C, and 30D. The server device 20 and each of the terminal devices 30A to 30D are connected via a network, and the server device 20 and each of the ophthalmologic apparatuses or communication devices connected to the ophthalmologic apparatuses are connected via a network. For example, examination results obtained by the ophthalmologic apparatuses are stored in the server device 20 via the network, so that an examiner using a terminal device (for example, terminal device 30A) can confirm the examination results. Note that the numbers of ophthalmologic apparatuses and terminal devices are merely examples and are not limited thereto.

[0031] 1, the ophthalmic devices include a slit lamp 10A, an OCT device 10B, a fundus camera 10C, a refractometer 10D, and a phoropter 10E. Each ophthalmic device may be owned by a different medical institution (e.g., a general hospital, an ophthalmology clinic, a university hospital, etc.), or a specific medical institution may own multiple ophthalmic devices.

[0032] For example, the fundus camera 10C is a device owned by many medical institutions, and therefore each institution introduces a model with different manufacturers and functions. However, in the ophthalmologic system 1, regardless of the manufacturer, model, etc., the examiner can check the examination results, including information obtained at other medical institutions, on at least one of the terminal devices 30A to 30D.

[0033] Here, the features of each ophthalmic apparatus will be briefly described.

[0034] The slit lamp 10A, also known as a slit lamp microscope, is a device that captures an anterior segment image, which is a cross-sectional image of the cornea, by irradiating a long, thin slit of illumination light onto the subject's eyeball from an oblique angle. The slit lamp 10A is used for various anterior segment examinations, such as corneal shape, corneal endothelial cells, and meibomian glands.

[0035] The OCT device 10B splits low-coherence light into two beams, irradiates one beam onto the fundus, and causes the backscattered light to interfere with the other beam, which is then received by a CCD image sensor or the like to obtain a tomographic image of the fundus (retina). This tomographic image is used to diagnose eye diseases such as glaucoma, diabetic retinopathy, and retinitis pigmentosa. The OCT device 10B may be any device using a Fourier domain system, a time domain system, a swept source system, or the like.

[0036] The fundus camera 10C is a device that irradiates illumination light onto the fundus of the subject's eye and receives the reflected light from the fundus with a light-receiving element such as a CCD (Charge Coupled Device) image sensor to obtain fundus image data. Fundus images are used to diagnose eye diseases such as glaucoma, diabetic retinopathy, and age-related macular degeneration.

[0037] The refractometer 10D is an examination device capable of measuring various eye characteristics such as the intraocular pressure, ocular refractive power, and corneal curvature of the subject's eye.

[0038] The Phoropter 10E, also known as a vision tester, is an examination device used to select lenses that fit the subject's eyes. The Phoropter 10E is equipped with multiple lenses, and by inserting one or more of these lenses onto the optical axis, it can measure the eye refractive power and binocular vision function, such as myopia, hyperopia, and astigmatism.

[0039] The ophthalmologic apparatus 10 may include devices other than those described above. For example, a scanning laser ophthalmoscope may be used, which scans a light beam to irradiate the fundus and receives reflected light or fluorescence at a predetermined location using a CCD or the like to obtain image data of the fundus image. Another example is a specular microscope, which can capture images of corneal endothelial cells, measure their density, and measure the corneal thickness.

[0040] As will be described later with reference to Fig. 2, the server device 20 includes an internal server storage unit 22 that stores test results and image data from the ophthalmologic apparatus (see above) transmitted via the network. Furthermore, each of the terminal devices 30A to 30D is connected to the server device 20, and therefore can constantly access the test results and the like stored in the server storage unit 22 of the server device 20. There are no particular limitations on the type of the server device 20, and it may be, for example, a cloud-type server or an on-premise server located in a medical institution or the like.

[0041] Each of the terminal devices 30A to 30D is a PC, a notebook PC, a tablet terminal, or the like, owned by each medical institution. Software for using the ophthalmologic system 1 is installed in each of these terminal devices 30A to 30D. Therefore, the examiner can check the examination results and image data stored in the server device 20 on each of the terminal devices 30A to 30D. Furthermore, the examiner can check the records of the electronic medical record in addition to the examination results, etc. obtained at other medical institutions, and therefore determines the presence or absence of a disease in the examined eye, etc., taking each piece of information into consideration.

[0042] Next, an example of the hardware configuration of the server device 20 and the terminal device 30 constituting the ophthalmologic system 1 according to this embodiment will be described with reference to Fig. 2 and Fig. 3. Fig. 2 is a block diagram showing an example of the hardware configuration of the server device 20 and the terminal device 30 according to this embodiment. Fig. 3 is a diagram showing an example of the arrangement of the surgical site camera 40 and the surgical site monitor 50. The terminal device 30 has an example of a hardware configuration that can be applied to any of the multiple terminal devices 30A to 30D constituting the ophthalmologic system 1 shown in Fig. 1.

[0043] The server device 20 is composed of a server communication unit 21, a server storage unit 22, and a server processor 23. The server device 20 is located outside the medical institution (outside the hospital) and is configured as, for example, a cloud-type server device. Note that the server device 20 may be configured as an on-premise server device located inside the medical institution (inside the hospital) instead of a cloud-type server device.

[0044] The server communication unit 21 is connected to an ophthalmic device (see FIG. 1) or a terminal device 30 located inside a medical institution via a network (not shown), and is configured using a communication circuit that performs data communication with the ophthalmic device or the terminal device 30. The server communication unit 21 performs data communication with the ophthalmic device or the terminal device 30, receives various data sent from the ophthalmic device or the terminal device 30, and transmits various data to the ophthalmic device or the terminal device 30.

[0045] The server storage unit 22 is configured using, for example, RAM (Random Access Memory) and ROM (Read Only Memory), and temporarily stores programs necessary for the operation of the server device 20 and data acquired or generated during operation. The RAM is, for example, a work memory used during operation of the server device 20. The ROM, for example, stores and holds in advance programs for controlling the server device 20.

[0046] The server processor 23 is configured by at least one of, for example, a CPU (Central Processing Unit), a DSP (Digital Signal Processor), a GPU (Graphical Processing Unit), or an FPGA (Field Programmable Gate Array). The server processor 23 functions as a controller that manages the overall operation of the server device 20. The server processor 23 performs control processing for overseeing the operation of each part of the server device 20, data input / output processing between each part of the server device 20, data arithmetic processing, and data storage processing. The server processor 23 operates according to a program stored in the server storage unit 22. The server processor 23 uses the server storage unit 22 during operation, and temporarily stores data generated or acquired by the server processor 23 in the server storage unit 22.

[0047] The terminal device 30 is composed of a terminal communication unit 31, a terminal display unit 32, a terminal storage unit 33, and a terminal processor 34. The terminal device 30 is placed, for example, in an examination room inside (inside) a medical institution, but the placement location is not limited depending on the operational policy of the medical institution, etc. The terminal device 30 is connectable to an external storage medium (e.g., an SD card) that stores a machine learning model 36, and can refer to and execute the machine learning model 36 via this external storage medium. Details of this machine learning model 36 will be described later, and although the machine learning model 36 is shown as being stored in an external storage medium, it may also be stored in the terminal storage unit 33 of the terminal device 30 so as to be able to be referenced.

[0048] The terminal communication unit 31 is an example of a communication unit, and is configured using a communication circuit that is connected to the server device 20 via a network (not shown) and performs data communication with the server device 20. The terminal communication unit 31 performs data communication with the server device 20, receives various types of data sent from the server device 20, and transmits various types of data to the server device 20.

[0049] The terminal display unit 32 is an example of an informing device, and displays the processing results by the terminal processor 34. The terminal display unit 32 is, for example, a display such as an LCD (Liquid Crystal Display) or an organic EL display. The terminal display unit 32 and an input device (not shown) that accepts operations by a user (for example, a doctor in charge of a patient undergoing surgery) may be configured as an integrated unit, in which case the input device and the terminal display unit 32 are configured as a touch panel display.

[0050] The terminal storage unit 33 is configured using, for example, RAM and ROM, and temporarily stores programs necessary for the operation of the terminal device 30 and data acquired or generated during operation. The RAM is, for example, a work memory used during the operation of the terminal device 30. The ROM, for example, stores and holds in advance programs for controlling the terminal device 30.

[0051] The terminal processor 34 is an example of a processor and is composed of at least one of a CPU, a DSP, a GPU, or an FPGA, for example. The terminal processor 34 functions as a controller that manages the overall operation of the terminal device 30. The terminal processor 34 performs control processing for overseeing the operation of each unit of the terminal device 30, data input / output processing between each unit of the terminal device 30, data arithmetic processing, and data storage processing. The terminal processor 34 operates according to a program stored in the terminal storage unit 33. The terminal processor 34 uses the terminal storage unit 33 during operation, and temporarily stores data generated or acquired by the terminal processor 34 in the terminal storage unit 33. In the terminal device 30, the terminal processor 34 cooperates with the terminal storage unit 33 to execute various processes (for example, the processes of the flowchart shown in FIG. 6). The terminal processor 34 implements the function of the determination unit 35 by cooperating with the terminal storage unit 33.

[0052] The determination unit 35 receives a patient's body image captured by the surgical site camera 40 or the wearable camera 41 immediately before the start of surgery and performs a process of identifying surgical eye determination information from the received patient body image by referring to the machine learning model 36. This surgical eye determination information includes not only identification information such as the patient's name, but also information identifying whether the patient's target eye (i.e., the surgical eye) is the left eye, the right eye, or both eyes. The determination unit 35 acquires the patient's pre-examination surgical eye data, which is registered as a result of a pre-examination conducted in an examination room or the like before surgery, from the server device 20. The determination unit 35 performs a process of identifying the patient's surgical eye based on the acquired pre-examination surgical eye data and the identified surgical eye determination information. Here, determining the patient's surgical eye refers to, for example, determining whether the surgical eye indicated by the surgical eye determination information matches the surgical eye indicated by the patient's pre-examination surgical eye data, which is registered as a result of the pre-examination, for a patient who is covered with a drape 60 (see FIG. 4 ) immediately before the start of surgery. The determination unit 35 may display the determination result of the patient's eye on the terminal display unit 32.

[0053] The machine learning model 36 receives an image of the patient's body taken by the operating room camera 40 or the wearable camera 41 immediately before the start of surgery, and performs processing to identify and output surgical eye judgment information from the image of the patient's body. The machine learning model 36 is stored in advance in an external storage medium such as an SD card, and is referenced and used by the judgment unit 35 after this external storage medium is connected to the terminal device 30 so as to enable data input and output.

[0054] Here, machine learning of the machine learning model 36 will be described with reference to FIGS. 4 and 5. FIG. 4 is a diagram showing an example of a drape used to cover a patient before surgery. FIG. 5 is a diagram showing an example of training data used in machine learning. The machine learning model 36 is generated by machine learning using images of multiple types of dressing sheets and images of multiple types of dressing sheets covering the patient's face as training data. The dressing sheet is, for example, a drape 60 or gauze used to cover a patient when an operator 62 performs surgery on the patient, as shown in FIG. 4. Whether a drape or gauze is used as the dressing sheet may be determined based on the regional characteristics of the medical institution.

[0055] 4 has an opening 61 through which the surgical eye, which is the patient's eye to be operated on, can be exposed. By providing this opening 61, a surgeon 62 can perform appropriate surgery on the surgical eye with at least the upper half of the patient's body or the entire body covered by the drape 60. Note that the drape 60 during surgery has the opening 61 on either the left or right side. In other words, there are no drapes that have openings that expose both the left and right eyes or that have an opening that connects the left and right eyes.

[0056] As shown in FIG. 5, input images PIC1, PIC2, ​​PIC3, PIC4, and PIC5 correspond to the input images that serve as learning data, but it goes without saying that the input images are not limited to these.

[0057] Input image PIC1 shows a state in which at least the patient's face is covered with a drape that can expose the patient's left eye, and this drape has an opening that exposes the patient's left eye. Input image PIC2 shows a state in which a drape is placed over the operating table 63 with the patient resting on it, and the operating table 63 and the patient are covered, and this drape has an opening that exposes the patient's right eye. Input image PIC3 shows a state in which at least the patient's face is covered with a drape that can expose the patient's left eye during surgery, and this drape has an opening that exposes the patient's left eye. Input image PIC4 shows the drape itself, which has an opening that exposes the patient's left eye. Input image PIC5 shows a state in which the entire patient's body, including at least the patient's face, is covered with a drape that can expose the patient's right eye just before surgery, and this drape has an opening that exposes the patient's right eye.

[0058] Machine learning is performed using these many input images PIC1 to PIC5 as learning data, and a machine learning model 36 is generated. This machine learning model 36 is referenced and executed as appropriate by a determination unit 35 of a terminal processor 34 of the terminal device 30. It is assumed that during surgery, the patient is lying supine on an operating table 63 (see FIG. 3) installed in an operating room. If the upper side of the patient's head can be recognized, it can be determined whether the patient's exposed eyeball is left or right.

[0059] The operating room camera 40 is an example of an imaging device, and is placed, for example, in an operating room inside a medical institution (hospital) (see FIG. 3 ), and is connected to the terminal device 30 so that data communication can be performed between the operating room camera 40 and the terminal device 30. The operating room camera 40 captures images of the atmosphere, mainly focusing on the operating table 63. For example, just before surgery, when a patient is placed on the operating table 63 with at least the upper half of their body or the entire body covered with a covering sheet such as a drape 60, the operating room camera 40 captures a body image including at least the upper half of the patient's body. The operating room camera 40 sends the captured body image of the patient to the terminal device 30.

[0060] The wearable camera 41 is an example of an imaging device, and is a small camera worn by an operator, such as a doctor or assistant, performing surgery in an operating room. It is connected to the terminal device 30 for data communication, similar to the operating room camera 40. The wearable camera 41 mainly captures images of the operating table 63. For example, just before surgery, a patient is placed on the operating table 63 with at least the upper half of their body or the entire body covered with a covering sheet such as a drape 60. The wearable camera 41 captures a body image including at least the upper half of the patient's body as seen from the operator's position. The wearable camera 41 sends the captured body image of the patient to the terminal device 30.

[0061] The operating room monitor 50 is an example of an information device, and is placed, for example, in an operating room inside a medical institution (hospital) (see FIG. 3), and displays various information or data required for surgery. For example, the operating room monitor 50 may display the results of a series of processes (see FIG. 6) performed by the terminal device 30. By visually checking the information or data displayed on the operating room monitor 50, the surgeon can grasp various information about the patient and information about the patient's surgical eye.

[0062] 2. Ophthalmology system operating procedure (surgery eye identification method) Next, an example of an operation procedure of the ophthalmologic system 1 according to this embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of an operation procedure of the terminal device 30 according to this embodiment in chronological order. The series of processes shown in Fig. 6 is mainly executed by the terminal processor 34 of the terminal device 30. As shown in Fig. 6, in the ophthalmologic system 1 according to this embodiment, the terminal device 30 performs a double check to determine whether the left and right eyes of the patient match each other twice: a first determination in step S02 and a second determination in step S06.

[0063] 6, the terminal processor 34 acquires pre-examination surgical eye data, which is data on the surgical eye acquired during a pre-examination conducted before surgery, from the server device 20 or by reading it from the terminal storage unit 33 (S01). The terminal processor 34 acquires previous surgical eye data, which is data on the surgical eye acquired in the past and associated with the same patient and stored in the server device 20, from the server device 20 (S01). The terminal processor 34 compares the acquired pre-examination surgical eye data with the previous surgical eye data (S01). The pre-examination surgical eye data and the previous surgical eye data are likely to reveal some kind of disease in the surgical eye, and may be at least one of, for example, an anterior segment image, which is an image of a cross section of the cornea, a tomographic image of the fundus (retina), a fundus image showing the retina, optic nerve, and blood vessels, and an optical coherence tomographic vascular image for evaluating the state of blood vessels in the retina and macula.

[0064] In this comparison, the terminal processor 34 may display the acquired pre-examination surgical eye data and past surgical eye data on the terminal display unit 32 so as to be comparable, and may prompt the surgeon, such as the doctor in charge of the surgery, to input data and then accept the input. Alternatively, the terminal processor 34 may perform an automatic comparison, which does not require input by the surgeon, by performing image analysis on each of the acquired pre-examination surgical eye data and past surgical eye data, and determining whether the similarity of feature points on the images of both data is equal to or greater than a predetermined threshold.

[0065] When the terminal processor 34 determines that the patient's operative eye indicated by the pre-examination operative eye data and the patient's operative eye indicated by the past operative eye data do not match in terms of the left eye, the right eye, or both eyes (S02, NO), it generates a warning screen (not shown) for the surgeon and notifies it on the terminal display unit 32 (S08). This warning notifies the surgeon that the patient's operative eye indicated by the pre-examination operative eye data and the past operative eye data do not match for the left eye or the right eye, for example, and also notifies the surgeon that it is better not to start surgery.

[0066] On the other hand, if the terminal processor 34 determines that the patient's surgical eye indicated by the pre-examination surgical eye data and the patient's surgical eye indicated by the past surgical eye data match in terms of the left eye, the right eye, or both eyes (S02, YES), it registers the pre-examination surgical eye data as official surgical eye data before surgery (S03). After the processing of this step S03, it is officially determined whether the surgical eye is the left eye or the right eye, so a covering sheet (e.g., drape 60) is placed over the patient to be operated on, and the patient is carried to the operating room with the drape 60 placed over him / her.

[0067] The terminal processor 34 acquires a body image, which is an image of the patient's upper body or entire body including at least the face, captured by the operating room camera 40 arranged in the operating room (S04). The terminal processor 34 inputs the body image of the patient acquired in step S04 immediately before the start of surgery, and performs processing to identify surgical eye judgment information from the input body image of the patient by referring to the machine learning model 36 (S05). Furthermore, the terminal processor 34 acquires the patient's pre-examination surgical eye data registered as a result of the pre-examination registered in step S03, and performs processing to judge the patient's surgical eye based on a comparison between the acquired pre-examination surgical eye data of the patient and the surgical eye judgment information identified in step S05 (S06).

[0068] When the terminal processor 34 determines that the patient's surgical eye indicated by the pre-examination surgical eye data and the patient's surgical eye indicated by the identified surgical eye judgment information do not match in terms of the left eye, the right eye, or both eyes (S06, NO), it generates a warning screen (not shown) for the surgeon and notifies it to the terminal display unit 32 (S08). This warning is displayed at least on the surgical site monitor 50, so that the surgeon in the operating room can confirm the warning.

[0069] On the other hand, if the terminal processor 34 determines that the patient's surgical eye indicated by the pre-examination surgical eye data matches the patient's surgical eye indicated by the identified surgical eye determination information in terms of the left eye, the right eye, or both eyes (S06, YES), it displays a notice on the terminal display unit 32 or the surgical site monitor 50 notifying the surgeon that surgery is permitted to begin (S07). This allows the surgeon to confirm that the patient's surgical eye exposed through the opening in the drape 60 is correct, allowing the surgeon to begin surgery appropriately. In other words, the ophthalmologic system 1 can efficiently prevent mistakes in identifying the patient's surgical eye, which is the eye to be operated on.

[0070] The present disclosure is not limited to the above-described embodiments, and can be implemented in various forms without departing from the spirit and scope of the present disclosure. [Explanation of symbols]

[0071] 1. Ophthalmology System 10A Slit Lamp 10B OCT device 10C Fundus Camera 10D Refractometer 10E Phoropter 20 Server device 21 Server Communication Department 22 Server storage unit 23 Server Processors 30 Terminal Equipment 30A Terminal Equipment 30B Terminal Equipment 30C Terminal Equipment 30D Terminal Equipment 31 Terminal communication unit 32 Terminal display 33 Terminal memory section 34 Terminal Processor 35 Judgment section 36 Machine Learning Models 40 Operating Room Camera 41 Body-worn camera 50 Surgical site monitor 60 Drape 61 Aperture 62 Surgeon 63 Operating table

Claims

1. an imaging device that captures a body image including at least the upper body of a patient in a state where the face of the patient is covered with a covering sheet having an opening through which the surgical eye, which is the eyeball of the surgical target, can be exposed; a processor that determines the surgical eye based on surgical eye determination information obtained from the body image and pre-examination surgical eye data of the patient that is registered as a result of the pre-examination; and a notification device that notifies the surgeon of the evaluation result of the patient's eye. Ophthalmology system.

2. the processor inputs an image of the patient's face covered with the covering sheet, and determines the surgical eye by referring to a machine learning model that has been trained to output whether the patient's left or right eyeball is exposed through the opening in the covering sheet. The ophthalmic system of claim 1 .

3. the machine learning model is generated by machine learning using, as training data, images of the plurality of types of covering sheets and images of the plurality of types of covering sheets covering the patient's face. The ophthalmic system of claim 2 .

4. The imaging device is an operating room camera placed in an operating room where the surgery is performed or a wearable camera worn by the surgeon for surgery. The ophthalmic system of claim 1 .

5. a communication unit that communicates data with a server device that stores past surgical data, which is data on the surgical eye previously acquired by the patient; the processor compares the pre-examination surgical eye data with the past surgical eye data acquired from the server device via the communication unit for the surgical eye of the patient who is the same person. The ophthalmic system of claim 1 .

6. when the pre-examination surgical eye data and the past surgical eye data match as a result of the comparison, the processor performs a judgment of the surgical eye using the surgical eye judgment information and the pre-examination surgical eye data. The ophthalmology system of claim 5 .

7. The processor issues a pre-surgery warning by the notification device when the surgical eye of the patient indicated by the surgical eye judgment information obtained from the body image does not match the surgical eye of the patient indicated by the pre-examination surgical eye data of the patient registered as a result of the pre-examination. The ophthalmic system of claim 1 .

8. The processor notifies the patient of permission for surgery by the notification device when the patient's surgical eye indicated by the surgical eye judgment information obtained from the body image matches the patient's surgical eye indicated by the patient's pre-examination surgical eye data registered as a result of the pre-examination. The ophthalmic system of claim 1 .

9. Regarding the surgical eye, which is the eyeball to be operated on, confirming the surgical eye by comparing the patient's pre-examination surgical eye data obtained as a result of the pre-examination with past surgical eye data, which is data related to the patient's surgical eye in the past; capturing a body image including at least the upper body of the patient while the face of the patient is covered with a covering sheet having an opening; determining the surgical eye based on surgical eye determination information obtained from the body image and the patient's pre-examination surgical eye data that is determined to match the past surgical eye data as a result of the comparison; and notifying the surgeon of the judgment result of the patient's eye. How to identify surgical eyes.

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