System for determining insertion of artifact via medical fluoroscopy apparatus

Abstract

The present invention relates to a system for determining insertion of an artifact via a medical fluoroscopy apparatus, the system comprising: an insertion determination unit that analyzes, on the basis of artificial intelligence, the form of insertion of an artifact in the body from fluoroscopic images; a feedback unit that, when the insertion determination unit determines that the artifact has not been properly inserted, provides feedback through artificial intelligence; a learning unit in which, when a determination result of the insertion determination unit does not match a determination result of medical staff and correction content is input, artificial intelligence learns the correction content; and a storage unit that stores an activity history of the insertion determination unit, the feedback unit, and the learning unit. Thus, artificial intelligence may be used to determine the appropriateness of insertion of an artifact into the body, thereby reducing the number of uses of fluoroscopy equipment and radiation exposure time.

Description

Medical fluoroscopy device artifact insertion judgment system

[0001] The present invention relates to a system for determining whether an artificial object is properly inserted into a body by introducing artificial intelligence into a medical fluoroscopy device.

[0002]

[0003] In the medical field, radiological equipment is considered essential. In particular, the C-arm, a fluoroscopy device that assists in real-time visualization of the affected area during surgery or procedures, is essential in various fields, including orthopedics and neurosurgery.

[0004] Unlike therapeutic radiation equipment that requires high doses of radiation, C-arms are diagnostic devices, resulting in relatively low radiation exposure. However, for medical staff, the cumulative radiation exposure due to frequent use of these devices can be significant. This has raised concerns about radiation exposure among medical staff, necessitating urgent efforts to reduce their exposure.

[0005] Accordingly, as a way to reduce the radiation exposure of C-arm, a method has been proposed to minimize the area exposed to radiation by developing a device that exposes radiation only to the lesion area, as in Korean Patent No. 10-2314902.

[0006] Although there is a way to reduce the amount of radiation exposure by exposing only the necessary areas, it is also important to reduce the cumulative amount of radiation exposure by reducing the exposure time.

[0007] For example, in joint replacement surgery, medical staff may perform C-arm imaging to confirm proper placement of the prosthesis. While skilled staff can easily insert the prosthesis and assess its suitability from imaging, less experienced staff may require multiple attempts to properly position the prosthesis, or may lack confidence in the imaging assessment, leading to multiple attempts.

[0008] As the level of skill of the medical staff decreases, the C-arm usage time tends to increase, which also increases the time of exposure to radiation.

[0009] (Patent Document 0001) Korean Patent No. 10-2314902 (August 20, 2019, Dose control device mountable on a diagnostic radiation device and a dose control system including the same)

[0010]

[0011] The present invention aims to solve the above problems by introducing artificial intelligence into a C-arm device, thereby reducing the radiation exposure time of medical staff by having the artificial intelligence determine the appropriateness of inserting an artificial object.

[0012]

[0013] A medical fluoroscopy device's artificial object insertion judgment system according to an embodiment of the present invention may include an insertion judgment unit that uses artificial intelligence to analyze the shape of an artificial object inserted into a body from a fluoroscopy image; a feedback unit that uses artificial intelligence to provide feedback when the insertion judgment unit determines that the artificial object is not properly inserted; a learning unit that inputs correction content when the judgment result of the insertion judgment unit and the judgment result of a medical professional do not match, and the artificial intelligence learns the correction content; and a storage unit that stores activity histories of the insertion judgment unit, the feedback unit, and the learning unit.

[0014] In addition, the method may further include a prognosis judgment unit that determines inflammation or side effects occurring near an artificial object inserted into the body from a fluoroscopy image and uses artificial intelligence to determine the prognosis.

[0015] In addition, the learning unit includes a prognosis learning unit that learns the results of the prognosis judgment unit, and can learn by comparing the judgment of the prognosis judgment unit with the prognosis of an actual patient.

[0016] In addition, a data organization unit may be further included to organize the activity history stored in the storage unit after the surgery is completed and provide learning materials to medical staff.

[0017]

[0018] The present invention has the effect of reducing the number of uses of fluoroscopy equipment and radiation exposure time by allowing artificial intelligence to determine the appropriateness of inserting an artificial object into the body.

[0019] Additionally, by observing post-operative prognosis, artificial intelligence can learn about the outcome of the judgment.

[0020] Additionally, the activity history for determining the appropriateness of artificial implant insertion can be organized to provide learning materials to medical staff.

[0021]

[0022] FIG. 1 is a block diagram of an artificial object insertion judgment system of a medical fluoroscopy device according to an embodiment of the present invention.

[0023] Figure 2 is a block diagram of Figure 1 with a prognostic judgment unit added.

[0024] Figure 3 is a block diagram of Figure 1 with a data management section added.

[0025]

[0026] A medical fluoroscopy device's artificial object insertion judgment system according to an embodiment of the present invention may include an insertion judgment unit that uses artificial intelligence to analyze the shape of an artificial object inserted into a body from a fluoroscopy image; a feedback unit that uses artificial intelligence to provide feedback when the insertion judgment unit determines that the artificial object is not properly inserted; a learning unit that inputs correction content when the judgment result of the insertion judgment unit and the judgment result of a medical professional do not match, and the artificial intelligence learns the correction content; and a storage unit that stores activity histories of the insertion judgment unit, the feedback unit, and the learning unit.

[0027]

[0028] The following description of the present invention with reference to the drawings is not limited to specific embodiments, and various modifications and embodiments may be made. Furthermore, the following description should be understood to encompass all modifications, equivalents, and alternatives within the spirit and technical scope of the present invention.

[0029] In the following description, terms such as first, second, etc. are used to describe various components, and are not limited in meaning in themselves, but are used only for the purpose of distinguishing one component from another.

[0030] The same reference numbers used throughout this specification represent the same components.

[0031] As used herein, singular expressions include plural expressions unless the context clearly dictates otherwise. In addition, terms such as "comprise," "include," or "have" used herein should be interpreted to indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, and should be understood to not preclude the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0032] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by those of ordinary skill in the art to which this invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and will not be interpreted in an idealized or overly formal sense unless explicitly defined herein.

[0033] In addition, when describing with reference to the attached drawings, identical components will be assigned the same reference numerals regardless of the drawing numbers, and redundant descriptions thereof will be omitted. When describing the present invention, if a detailed description of a related known technology is judged to unnecessarily obscure the gist of the present invention, the detailed description will be omitted.

[0034] Hereinafter, an artificial object insertion judgment system of a medical fluoroscopy device according to an embodiment of the present invention will be described in detail with reference to FIGS. 1 to 3.

[0035]

[0036] FIG. 1 is a block diagram of an artificial object insertion judgment system of a medical fluoroscopy device according to an embodiment of the present invention, FIG. 2 is a block diagram to which a prognosis judgment unit is added to FIG. 1, and FIG. 3 is a block diagram to which a data management unit is added to FIG. 1.

[0037] Referring to FIG. 1, the artificial object insertion judgment system (1) of a medical fluoroscopy device according to an embodiment of the present invention may include an insertion judgment unit (10), a feedback unit (20), a learning unit (30), and a storage unit (40).

[0038] The above medical fluoroscopy device may be a fluoroscopy device that uses radiation, such as a C-arm, X-ray, or MRI, but the present invention will be described using a C-arm device as an example.

[0039] The insertion judgment unit (10) may analyze the shape of the artificial object inserted into the body from a fluoroscopy image using artificial intelligence.

[0040] Specifically, when artificial objects such as steel wires, artificial joints, screws, plates, and injection needles are inserted inside the body, it can help medical staff make decisions by determining whether the location of the artificial object is appropriate through artificial intelligence.

[0041] For example, by checking the images taken in the front-back direction through the video, it is possible to determine whether the location of the artificial insertion is appropriate, and the location of the artificial insertion can be determined according to various angles such as the left-right direction or the diagonal direction.

[0042] The feedback unit (20) may be an artificial intelligence that provides feedback when the insertion judgment unit (10) determines that the artifact has not been properly inserted.

[0043] Specifically, if the insertion of the artifact is not appropriate, the problem with the current artifact position and the appropriate position of the artifact, such as 'move 0.1 mm to the left', 'rotate 10° clockwise', or 'rotate 10° upward', can be presented, and feedback can be provided until the artifact is positioned in an appropriate position and shape.

[0044] If the judgment result of the insertion judgment unit (10) and the judgment result of the medical staff do not match, the learning unit (30) may input correction content, and the artificial intelligence may learn the correction content.

[0045] In detail, when skilled medical staff use equipment equipped with the system of the present invention, they may feel that the artificial intelligence's judgment results are different from their own judgment.

[0046] In this case, the medical staff can input correction information, and the learning unit (30) can learn the input correction information and use it for the judgment of the next insertion judgment unit (10).

[0047] For example, when the feedback unit (20) provides feedback to move the position of the artifact 0.1 mm to the left, if the medical staff determines that the movement is unnecessary, the correction that the movement is unnecessary can be input into the learning unit (30).

[0048] In addition, the reason why the feedback from the feedback unit (20) is judged to be inappropriate, such as a problem that may occur when the position of the artifact is changed according to the feedback from the feedback unit (20), can be input into the learning unit (30) and learned.

[0049] The storage unit (40) may store the activity history of the insertion judgment unit (10), feedback unit (20), and learning unit (30).

[0050] In detail, all records generated while the artificial insertion judgment system (1) of the medical fluoroscopy device of the present invention operates, such as image records taken during surgery, analysis results of the insertion judgment unit (10) for the taken images, feedback contents of the feedback unit (20), and correction contents entered by medical staff, can be stored.

[0051] Additionally, the activity history of the prognosis judgment unit (50) and data organization unit (60), which will be explained later, can also be stored in the storage unit (40).

[0052]

[0053] Referring to FIG. 2, the artificial object insertion judgment system of the medical fluoroscopy device according to the embodiment of the present invention may further include a prognosis judgment unit (50).

[0054] The prognosis judgment unit (50) may use artificial intelligence to determine the prognosis by determining inflammation or side effects occurring near an artificial object inserted into the body from a fluoroscopic image.

[0055] In detail, after a certain period of time has passed since the surgery, the patient can undergo additional X-ray imaging to check the results of the surgery, and the prognosis judgment unit (50) can determine whether problems such as inflammation, side effects, or misalignment of the artificial part have occurred at the surgery site.

[0056] At this time, the learning unit (30) includes a prognosis learning unit that learns the results of the prognosis judgment unit (50), and can learn by comparing the judgment of the prognosis judgment unit (50) with the prognosis of an actual patient.

[0057] In detail, if the prognosis judgment unit (50) determines that the patient's prognosis is good, the prognosis learning unit can learn that the judgment result of the insertion judgment unit (10) stored in the storage unit (40) was appropriate, and if the patient's prognosis is determined to be bad, the prognosis learning unit can learn that there was an error in the judgment of the insertion judgment unit (10) and use this for the judgment of the next insertion judgment unit (10).

[0058] In addition, if the judgment result of the prognosis judgment unit (50) and the judgment result of the medical staff are different, when the medical staff inputs correction information, the prognosis learning unit learns the correction information and can use it for the judgment of the next prognosis judgment unit (50) and insertion judgment unit (10).

[0059] In addition, if a correction is entered into the post-operative learning unit (30) that the insertion judgment unit (10) made an incorrect judgment, the prognosis learning unit can learn by comparing the prosthesis insertion position according to the correction and the patient prognosis.

[0060]

[0061] Referring to FIG. 3, the artificial object insertion judgment system of a medical fluoroscopy device according to an embodiment of the present invention may further include a data management unit (60).

[0062] The data management unit (60) may organize the activity history stored in the storage unit (40) after the surgery is completed and provide learning materials to medical staff.

[0063] Inexperienced medical staff may need post-operative training to understand the differences between their own judgment and that of the AI. In this case, the analysis results from the insertion judgment unit (10) stored in the storage unit (40) and the resulting feedback from the feedback unit (20) are organized by the data management unit (60) and provided to the medical staff, allowing them to review the surgical details.

[0064] Additionally, medical staff can receive additional data on the prognosis of a patient undergoing surgery, as determined by the prognosis assessment unit (50). This allows medical staff to learn through a comprehensive history of AI-generated prognosis, from the patient's surgical process to the prognosis itself.

[0065] In addition, in the case of a surgery where the judgment of the insertion judgment unit (10) and the medical staff differ, the analysis content of the insertion judgment unit (10), the feedback content of the feedback unit (20) based on this, and the correction content entered in the learning unit (30) are organized in the data organization unit (60) and provided to the medical staff, so that the data can be used as learning material for inexperienced medical staff.

[0066]

[0067] As described above, the present invention can effectively reduce radiation exposure of medical staff and patients by reducing the amount of radiation used by quickly determining the appropriateness of the location of artificial insertion through artificial intelligence learning.

[0068]

[0069] Although the embodiments of the present invention have been described above with reference to the attached drawings, those skilled in the art will understand that the present invention can be implemented in other specific forms without altering the technical spirit or essential features of the present invention. Therefore, the embodiments described above are illustrative in all respects and are not limiting.

[0070]

[0071] [Explanation of symbols]

[0072] 1: System for judging the insertion of artificial objects in medical fluoroscopy devices

[0073] 10: Insertion judgment section

[0074] 20: Feedback Department

[0075] 30: Learning Department

[0076] 40: Storage

[0077] 50: Prognosis Department

[0078] 60: Data Management Department

Claims

1. An insertion judgment unit that uses artificial intelligence to analyze the shape of an artificial object inserted into the body from a fluoroscopy image; A feedback unit in which artificial intelligence provides feedback when the above insertion judgment unit determines that the artifact has not been properly inserted; If the judgment result of the above insertion judgment unit and the judgment result of the medical staff do not match, a learning unit that inputs correction information and the artificial intelligence learns the correction information; and An artificial object insertion judgment system of a medical fluoroscopy device, comprising a storage unit that stores activity history of the insertion judgment unit, feedback unit, and learning unit.

2. In paragraph 1, A medical fluoroscopy device artificial implant insertion judgment system characterized by further including a prognosis judgment unit that determines inflammation or side effects occurring near an artificial implant inserted into the body from a fluoroscopy image and judges the prognosis using artificial intelligence.

3. In paragraph 2, The above learning department, A medical fluoroscopy device artificial insertion judgment system characterized in that it learns by comparing the judgment of the prognosis judgment unit with the prognosis of an actual patient, including a prognosis learning unit that learns the results of the prognosis judgment unit.

4. In paragraph 1, An artificial intelligence judgment system for medical fluoroscopy equipment, further comprising a data organization unit that organizes activity records stored in the storage unit after surgery and provides learning materials to medical staff.

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