JP2022089206A - Radiography learning device, radiography learning program, and radiography learning system - Google Patents

Abstract

To perform a practical training of positioning for radiography that uses an actual human body and a clinical image.SOLUTION: A radiography learning device according to the present invention includes: image reading means for reading clinical image data including a predetermined site taken by a radiography device; image display control means for displaying, in a display device, a 3D model image rendered on the basis of the clinical image data; posture information reception means for receiving posture information on an amount of rotation in a space of a predetermined site of a human body caused by change of a posture of the site from a motion sensor equipped to the site. The image display control means rotates the site in the 3D model image displayed in the display device, in relation to the amount of rotation in the space.SELECTED DRAWING: Figure 4

Description

The present invention relates to an X-ray photography learning device, an X-ray photography learning program, and an X-ray photography learning system.

The simple X-ray examination has the longest history in the field of medical imaging and is a basic examination for radiological technologists. For this reason, most radiological technologists working in medical facilities engage in this X-ray examination as a clinical task.

In order to carry out an appropriate X-ray examination, it is necessary to set optimal imaging conditions and a positioning technique based on anatomical information. For this reason, new engineers will learn many radiography methods in X-ray photography lectures after understanding basic anatomy knowledge, and will accurately reproduce the positioning based on each radiography method in technical training. Mastering the technique is essential.

In the technical training, since the training of irradiating a simulated patient with X-rays involves unnecessary exposure, training using a human body model (human body phantom) that reproduces the tissue of the human body with high accuracy has been performed conventionally. .. It is a training to learn proper positioning while irradiating the phantom with X-rays and checking the captured image.

Here, since the phantom used for X-ray examination training is very expensive, it is difficult for each medical institution or educational institution to own many phantoms. In addition, since equipment for actually irradiating X-rays and equipment for constructing images are also required, the current situation is that the places where new engineers can train are limited to only a small part such as the shooting room of a hospital. be.

As a technique related to this, for example, in Patent Document 1, simulated X-ray photography is performed using a human body phantom, and X-ray photography is learned to learn the technique of X-ray photography by determining whether or not the desired X-ray photography has been performed. An X-ray image database and one or more motion sensors, which is a learning system obtained by scanning a human body phantom with a skeleton in advance and in which information on the position and orientation of the human body phantom at the time of shooting and imaging information are linked. The closest data among the data stored in the database is extracted from the information on the position and orientation of the human body phantom mounted at the predetermined position and the motion sensor, and the obtained image is acquired as a pseudo image. Described is an X-ray imaging learning system including an image acquisition unit and a determination unit for determining whether or not the pseudo-image is a desired image.

Japanese Unexamined Patent Publication No. 2016-145978

However, in the X-ray imaging learning system described in Patent Document 1, the human body phantom with a skeleton is still indispensable, and the medical image used for learning is a phantom image within the range prepared by scanning in advance. There was a problem that it was limited to learning limited and uniform cases.

The present invention has been proposed in view of the above points, and one aspect of the present invention is to enable practical X-ray imaging positioning training using an actual human body and clinical images.

In order to solve the above problems, the X-ray imaging learning apparatus according to the present disclosure is an X-ray imaging learning apparatus for learning an X-ray imaging technique, and includes a predetermined portion imaged by the X-ray imaging apparatus. From an image reading means for reading clinical image data, an image display control means for displaying a 3D model image rendered based on the clinical image data on a display device, and a motion sensor mounted on the predetermined part of the human body. The image display control means has a posture information receiving means for receiving posture information regarding the amount of spatial rotation of the portion due to a change in the posture of the portion, and the image display control means displays the portion of the 3D model image displayed on the display device. It is rotated according to the amount of space rotation.

According to the embodiments of the present disclosure, practical X-ray imaging positioning training using an actual human body and clinical images can be performed.

It is a figure which shows the configuration example of the X-ray photography learning system which concerns on this embodiment. It is a figure which shows the hardware configuration example of the X-ray photography learning server and the wearable motion sensor which concerns on this embodiment. It is a figure which shows the software configuration example of the X-ray photography learning server and the wearable motion sensor which concerns on this embodiment. It is a figure which shows the learning example 1 using the X-ray photography learning system which concerns on this embodiment. It is a figure which shows the learning example 2 using the X-ray photography learning system which concerns on this embodiment. It is a figure which shows the learning example 3 using the X-ray photography learning system which concerns on this embodiment. It is a flowchart which shows the image display control processing of the X-ray photography learning server which concerns on this embodiment. It is a figure which shows the task screen which used the X-ray photography learning system which concerns on this embodiment.

Hereinafter, this embodiment will be described with reference to the drawings. The same configuration will be described with the same reference numerals. It should be noted that the following embodiments do not limit the techniques of the present disclosure, and not all combinations of features described in the present embodiments are essential for solving the above problems.

<System configuration>
(Network configuration)
FIG. 1 is a diagram showing a configuration example of an X-ray imaging learning system according to the present embodiment. The X-ray photography learning system 100 of FIG. 1 has an X-ray photography learning server 10 and a wearable motion sensor 20.

The X-ray imaging learning server 10 is an information processing device that displays DICOM images (mainly clinical images) for learning X-ray imaging techniques on an attached medical high-resolution display. DICOM (Digital Imaging and Communications in Medicine) is known as a standard that defines the format of medical images taken by image generators (so-called modalities) such as CT, MRI, and CR, and the communication protocol between the modality devices that handle them. Has been done.

The wearable motion sensor 20 is a sensor that can be attached to a predetermined portion (imaging portion) of the human body, and is a motion sensor that detects the posture (positioning) of the human body portion. The wearable motion sensor 20 is communicably connected to the X-ray photography learning server 10 via a communication network including wired communication such as COM communication and wireless communication such as Bluetooth (registered trademark) and WiFi (registered trademark), and the detected human body. The posture information of the part is transmitted to the X-ray photography learning server 10.

(Hardware configuration)
FIG. 2 is a diagram showing a hardware configuration example of the X-ray imaging learning server and the wearable motion sensor according to the present embodiment. As shown in FIG. 2A, the X-ray photography learning server 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, and an HDD (Hard Disk Drive) 14. , Communication device 15, and display device 16.

The CPU 11 executes various programs and performs arithmetic processing. The ROM 12 stores programs and the like required at startup. The RAM 13 is a work area for temporarily storing the processing in the CPU 11 and storing the data. The HDD 14 stores various data and programs. The communication device 15 communicates with the wearable motion sensor 20. The display device 16 is a medical high-resolution display that displays a medical image related to X-ray imaging learning.

As shown in FIG. 2B, the wearable motion sensor 20 includes a 9-axis motion sensor 21, a microcomputer board 22, and a communication device 23.

The 9-axis motion sensor 21 is a 3-axis acceleration sensor for detecting acceleration with a change in the motion speed of the object and determining the direction of the object, and detects how fast the object is rotating. It is a sensor consisting of a small sensor module equipped with a 3-axis gyro sensor (angular velocity sensor) for this purpose and a 3-axis geomagnetic sensor that detects geomagnetism in the vertical direction in addition to the front-back and left-right directions.

The microcomputer board 22 is a control device that analyzes the sensing information (acceleration, angular velocity, geomagnetism) of the 9-axis motion sensor 21 and calculates a quaternion (quaternion) representing rotation. The communication device 23 transmits a quaternion (quaternion) as posture information of the human body equipped with the 9-axis motion sensor 21 to the X-ray photography learning server 10.

The purpose of using the 9-axis motion sensor 21 is to determine the posture of the human body, but the posture can be grasped as how much it is rotated from the reference position (for example, the state of being horizontal to the ground and facing north). .. Therefore, the microcomputer board 22 can calculate, for example, a quaternion (quaternion) indicating the amount of spatial rotation of the sensor as the posture information of the human body based on the sensing information of the 9-axis motion sensor 21.

(Software configuration)
FIG. 3 is a diagram showing a software configuration example of the X-ray imaging learning server and the wearable motion sensor according to the present embodiment. As shown in FIG. 3A, the X-ray imaging learning server 10 has, as main functional units, an image reading unit 101, an image display control unit 102, a posture information receiving unit 103, a matching degree determination unit 104, and a storage unit. It has a part 107.

The image reading unit 101 has a function of reading DICOM image data (DICOM volume image data) of a clinical image including a predetermined portion (imaging site) previously imaged by an X-ray imaging device from the storage unit 107.

The image display control unit 102 has a function of displaying the volume-rendered 3D model image based on the DICOM image data of the clinical image on the display device 16. Further, as the posture information is received from the wearable motion sensor 20, the image display control unit 102 makes the part of the 3D model image displayed on the display device 16 correspond to the amount of spatial rotation accompanying the posture change of the human body part (following). Let) rotate.

The posture information receiving unit 103 has a function of receiving posture information regarding the amount of spatial rotation of the portion due to a change in the posture of the portion from a wearable motion sensor 20 mounted on a predetermined portion of the human body.

The matching degree determination unit 104 has a function of determining the degree of matching between the posture information received by the posture information receiving unit 103 and the model posture information associated with each problem related to the X-ray imaging technique. Further, the matching degree determination unit 104 outputs a natural language sentence based on the difference between the received posture information and the model posture.

The storage unit 107 has a function of storing the clinical image DB (Data Base) 107a. The clinical image DB 107a is a DB that stores radiographic image data of an actual patient taken in a clinical setting, that is, a slice image of an actual patient's body in a CT scan, for example, in DICOM format. DICOM image data consists of tag data and binary data. The tag data stores information such as image type, modality, examination information, imaging date and time, photographer, patient information, examination site, imaging conditions (exposure amount, etc.). However, from the viewpoint of personal information protection, it is desirable that the patient information (personal information) is deleted from the DICOM tag data in the clinical image data of the clinical image DB 107a.

The invention described in Patent Document 1 is obtained by scanning a human body phantom containing a skeleton in advance, and constructs an X-ray image database in which information on the position and orientation of the human body phantom at the time of photographing and imaging information are linked. On the other hand, in the case of the X-ray imaging learning system according to the present embodiment, it is not necessary to perform any construction work or information processing work on the DICOM image data of the clinical image DB 107a in advance. This means that there are no restrictions on the DICOM image data used for learning the positioning technique, and therefore it is possible to practically use the DICOM image data of the clinical image.

An X-ray photography learning program is pre-installed in the X-ray photography learning server 10, and the X-ray photography learning program is installed on hardware resources such as the CPU, ROM, and RAM of the computer constituting the X-ray photography learning server 10. By being executed, each of the above functional parts is realized. Further, these functional units may be read as "means", "module", "unit", or "circuit".

As shown in FIG. 3B, the wearable motion sensor 20 has a posture information acquisition unit 201 and a posture information transmission unit 202 as main functional units. The posture information acquisition unit 201 analyzes the sensing information of the 9-axis motion sensor 21 and calculates and acquires the posture information accompanying the posture change of the human body part. The posture information transmission unit 202 transmits the posture information to the X-ray imaging learning server 10 each time the posture information is acquired.

<Learning example>
FIG. 4 is a diagram showing a learning example 1 using the X-ray imaging learning system according to the present embodiment. First, as a preparation for the X-ray imaging learning server 10, the learner 31 selects a clinical image including an imaging site from which he / she wants to learn the positioning technique of X-ray imaging from the DICOM list on the screen of the display device 16, and screens it. The 3D model image is displayed above. At the time of 3D initial display on the screen of the display device 16, basically, the 3D model image is in a state where the front of the human body (or human body part) is displayed on the display screen as the "initial posture" (initial position), so to speak, "straight front". Is displayed facing. The 3D model image is a simulated display of the DICOM volume image data taken by X-ray on the display screen, but the "state in which the front of the human body is displayed" and the "straight front" image are viewed on the screen. An image or image that is displayed facing the person so that it is easy for the person to see, and is usually an image of the back of the human body viewed from directly above (see, for example, Fig. 4), or an upright state of the human body. It becomes an image seen from the front.

However, the DICOM image data that is the source of the 3D model image is not a "straight front" image at the time of the actual X-ray photography, and is oriented slightly in the vertical and horizontal directions, for example, from the straight front. In some cases, such as when the 3D initial display is performed, the front is straight and not displayed. Therefore, in such a case, the instructor, teacher, etc. or the auto-correction function adjusts the angle so that the 3D model image becomes the image of the initial posture of "straight front" as the initial adjustment, for example, by setting the correction value. It can be performed. The angle can be adjusted, for example, by rotating the 3D model image (or DICOM image) vertically and horizontally with the 3D coordinate system XYZ coordinate axis as the origin.

Next, in preparation for the wearable motion sensor 20, the learner 31 attaches the wearable motion sensor 20 to the same part of the learning collaborator (human body) 32, and the posture of the learning collaborator 32 is predetermined as a “reference posture” ( For example, it is placed on a horizontal table 30 in a posture in which it is laid down while facing straight up. More specifically, since the "straight front" image is displayed as the initial posture of the 3D model image on the screen, the "initial posture" (for example, "front") on the screen when the learning collaborator 32 is X-rayed. The position of the learning collaborator 32 and the mounting position of the wearable motion sensor 20 are adjusted to the posture (referred to as the reference posture) in which "straight") can be photographed.

In order to complete the above preparations and start learning the positioning technique for X-ray photography, the learner 31 starts learning by pressing the learning start button or the like on the X-ray photography learning server 10 side.

FIG. 5 is a diagram showing a learning example 2 using the X-ray imaging learning system according to the present embodiment. When the "reference posture" of the wearable motion sensor 20 is associated with the "initial posture" (initial position of the 3D coordinate system) of the 3D model image displayed on the screen triggered by the pressing operation of the learning start button, it is it. After that, the initial posture of the 3D model image displayed on the screen is set to x, y, z on the 3D coordinate system according to the posture information (rotation of the spatial coordinate system) sequentially sent from the wearable motion sensor 20. Start rotation in each of the axial directions. That is, every time the learning collaborator 32 causes a posture change, the posture change can be similarly expressed by real-time rotation for the 3D model image on the screen of the X-ray imaging learning server 10.

FIG. 6 is a diagram showing a learning example 3 using the X-ray imaging learning system according to the present embodiment. When the learner 31 moves the posture of the learning collaborator 32, the posture information accompanying the posture change of the human body part is sequentially sent from the wearable motion sensor 20 to the X-ray imaging learning server 10. For example, when the learner 31 positions the head of the learning collaborator 32 in the leftward direction from the reference posture, the 3D model image displayed on the screen is also displayed while rotating in the leftward direction as if synchronized. That is, the learner 31 can search for the optimum positioning of the imaging site while moving the posture of the learning collaborator 32, and can monitor on the screen what kind of radiographic image can be captured by real-time rotation. can.

As described above, in the X-ray photography learning system according to the present embodiment, training for learning the positioning technique can be performed without actually performing X-ray photography. In addition, since training can be performed using actual clinical images while using the actual human body, training using not only uniform cases using conventional phantoms but also many anatomically different cases is practiced. Can be done.

<Information processing>
FIG. 7 is a flowchart showing an image display control process of the X-ray imaging learning server according to the present embodiment. Each step (hereinafter referred to as "S") can be realized by the CPU 11 reading and executing a program that can realize this flowchart.

S1: The X-ray imaging learning server 10 displays a 3D model image on the screen of the display device 16 according to a predetermined operation of the learner 31. The X-ray imaging learning server 10 has a DICOM image-compatible 3D viewer function, and has a 3D volume for DICOM volume image data of the selected clinical image (for example, 512 sliced DICOM images of the human body in a CT scan). A 3D model image can be displayed on the screen by performing a rendering process.

In order to make the mounting position of the wearable motion sensor 20 appropriate, the rotation angle γ of the z-axis rotation is Yaw (yaw angle), the rotation angle β of the y-axis rotation is Pitch (pitch angle), and the rotation of the x-axis rotation. While moving the angle α around Roll (roll angle), manually fine-tune the mounting position while checking the output of the rotation information of the wearable motion sensor 20, or the X-ray photography learning server so that the assumed rotation information is output. Coordinate conversion is performed in advance at 10.

S2: The X-ray imaging learning server 10 determines whether or not there is a learning start operation of the learner 31. As described above, at the start of learning the positioning technique for X-ray photography, a 3D model image is displayed in the "initial posture" (for example, facing "straight front") on the screen of the display device 16, and learning cooperation is performed. The wearable motion sensor 20 is attached to the same part as the imaged part of S1 of the person 32, and the posture of the learning collaborator 32 is set to the "reference posture" (the "initial posture" on the screen when the learning collaborator 32 is X-rayed. Perform the learning start operation after placing it in the posture that will allow you to take a picture. If there is a learning start operation, the process proceeds to S3.

S3: The X-ray imaging learning server 10 sets the "initial posture" of the 3D model image on the screen (for example, a state facing "straight front") as the rotation start position of the 3D model image. As a result, the initial positions of the spatial coordinate system of the wearable motion sensor 20 and the 3D coordinate system of the 3D model image displayed on the screen in S1 can be matched with each other.

S4: The X-ray photography learning server 10 receives posture information (attitude information from the wearable motion sensor 20).
For example, it is determined whether or not a quaternion) has been received. As described above, when the learner moves the posture of the learning collaborator in order to learn the positioning technique of X-ray photography, the posture information accompanying the change in the posture of the human body part is sequentially transmitted from the wearable motion sensor 20 to the X-ray photography learning server 10. Will be sent to. When the posture information is received, the process proceeds to S5.

S5: When the X-ray photography learning server 10 receives the posture information from the wearable motion sensor 20 in S5, the X-ray photography learning server 10 rotates and displays the 3D model image from the "initial posture" by following the rotation amount indicated by the received posture information. ..

More specifically, the radiography learning server 10 generates a rotation matrix (DCM) from a quaternion. When the object is rotated by the angles γ, β, and α in the order of the z-axis, y-axis, and x-axis together with the spatial coordinate system, the rotation angle γ of the z-axis rotation is set to Yaw (yaw angle) in the rotation matrix. The rotation angle β of y-axis rotation is called Pitch (pitch angle), and the rotation angle α of x-axis rotation is called Roll (roll angle). The X-ray imaging learning server 10 rotates and displays the 3D model image on the screen in the x, y, and z directions on the 3D coordinate system by the amount of rotation indicated by Yaw, Pitch, and Roll from the "initial posture".

As a result, every time the human body part of the learning collaborator 32 changes its posture, the posture change can be similarly expressed in real time for the 3D model image on the screen of the X-ray imaging learning server 10. .. For example, when the learner 31 positions the head of the learning collaborator 32 in the leftward direction, the 3D model image displayed on the screen is also displayed while rotating in the leftward direction as if synchronized.

S6: The X-ray imaging learning server 10 determines whether or not the learner has performed a learning end operation. If there is a learning end operation, the process proceeds to END. On the other hand, if there is no learning end operation (learning continuation), the process proceeds to S4 again.

<Problem function>
(Textbook database)
The task function (test function) of the X-ray photography learning server 10 according to the present embodiment will be described. The X-ray photography learning server 10 has a textbook database in advance, for example, a task name provided for each positioning technique to be learned, a model 3D image corresponding to the task, and a posture model posture information (for the task). The combination with the Roll / Pitch / Yaw angle information, which is a model in the positioning of the X-ray method, is stored in advance in the HDD 14 or the like.

The textbook database can be created by the instructor / teacher or the like in advance by performing the learning of the learner 31 described with reference to FIGS. 4 to 6 in the same manner. Specifically, the instructor etc. first creates the task name. Next, the instructor or the like displays a 3D model image related to the task in the "initial posture" on the screen of the display device 16, and also attaches the wearable motion sensor 20 to the part related to the task of the learning collaborator 32 to be a learning collaborator. After setting the posture of 32 to the "reference posture" (the posture in which the "initial posture" on the screen can be photographed), the textbook database creation start operation is performed.

The instructor or the like moves the posture of the learning collaborator 32 and takes a position that serves as a model for the task. At this time, posture information (quaternion) indicating this model positioning is sent from the wearable motion sensor 20 to the X-ray imaging learning server 10. The X-ray photography learning server 10 generates a rotation matrix from a quaternion, and displays a 3D model image on the screen from its "initial posture" by the amount of rotation indicated by Yaw, Pitch, and Roll, and x, y, on the 3D coordinate system. Rotate and display in the z direction. When the instructor or the like performs an operation for completing the textbook database creation, the X-ray photography learning server 10 uses the captured still image of the 3D model image on the screen obtained at this time as a model 3D image corresponding to the problem, Yaw. Pitch and Roll are stored in the textbook database as posture model posture information.

(Problem learning)
The learner 31 first selects one task from the textbook database, and then starts task learning by pressing the task learning start button or the like. The learner 31 physically rotates (positions) the posture of the learning collaborator 32 to the posture state required by the task, and performs a predetermined scoring execution operation.

When the scoring execution operation is performed, the X-ray photography learning server 10 first captures the 3D model image displayed on the screen and saves it as a still image. In addition, the posture information from the wearable motion sensor 20 when the 3D model image is captured (angle information of Roll, Pitch, Yaw related to the learner 31) and the model posture information corresponding to the selected task (to the instructor, etc.). It is compared with the relevant Roll / Pitch / Yaw angle information), and scoring processing is performed according to the degree of matching. In the scoring process, the higher the degree of matching between the posture information from the wearable motion sensor 20 and the model posture information corresponding to the selected task, the higher the scoring value (score) is calculated, but the value itself indicating the degree of matching. May be used as the scoring value.

FIG. 8 is a diagram showing a task screen using the X-ray photography learning system according to the present embodiment. When the scoring execution operation is performed, the task 80, the model 3D image 81 corresponding to the task, the 3D model image 82 captured and saved as a still image, the degree of matching 83, and the advice 84 are displayed on the task screen showing the scoring result. Will be done.

Specifically, the model 3D image 81, which is a model (correct answer) so that the learner 31 can make a mutual comparison and aim for a shooting positioning closer to the model 3D image, and the 3D model image 82 captured by the learner 31. Are displayed side by side, and a matching degree 83 indicating how close to the model 3D image is displayed is displayed.

Further, the advice 84 is based on the degree of agreement (or difference) between the angle information of Roll / Pitch / Yaw of the posture information from the wearable motion sensor 20 and the angle information of Roll / Pitch / Yaw of the model posture information according to each task. You can view the estimated advice. For example, when the task is the front of the head, the chin of the subject becomes higher than the model posture due to the angle difference between the Pitch indicated by the posture information from the wearable motion sensor 20 and the Pitch indicated by the model posture information. If it is determined that it is closed, the predetermined advice associated with the determination result is "Pull the chin and make the OM line perpendicular to the image receiving surface. For example, if you put a pillow under the chest, pull the jaw. It is easy to display. ”In natural language. If the scoring result is not good, the learner 31 specifically grasps what was wrong (difference from the model posture) and how to improve (how to improve the difference) by using advice 84. At the same time, you can learn the model posture.

According to the task function according to the present embodiment, it is possible to test to what extent the learner 31 has correctly adjusted the learning collaborator 32, which is the subject, to the model posture according to the predetermined task.

<Summary>
According to the X-ray photography learning system 100 according to the present embodiment, training for learning the positioning technique can be performed without actual X-ray photography. In addition, since training can be performed using actual clinical images while using the actual human body, training using not only uniform cases using conventional phantoms but also many anatomically different cases is practiced. Can be done. Human phantoms and radiography equipment are not essential.

As a result, the X-ray imaging learning system 100 according to the present embodiment can be expected to be utilized in the education of radiological technologist training schools nationwide. In addition to being used in lectures and practical training, it can also be used as an active learning tool for students to learn by themselves. This system promotes active learning related to X-ray photography, which was difficult to practice without facilities and equipment related to X-ray equipment. Needless to say, it can be used not only as a tool for student education but also as a tool for postgraduate education for radiological technologists in medical institutions. It is expected to contribute to the improvement and improvement of medical services.

Although the present invention has been described above with reference to specific specific examples according to the preferred embodiments of the present invention, these specific embodiments are not deviated from the broad purpose and scope of the present invention defined in the claims. It is clear that various modifications and changes can be made to the example. That is, it should not be construed that the present invention is limited by the details of the specific examples and the accompanying drawings.

It should be noted that the present invention supplies a program that realizes one or more functions of the above-described embodiment to a system or an apparatus via a network or a recording medium, and one or more processors in the computer of the system or the apparatus are a program. It can also be realized by the process of reading and operating.

10 X-ray photography learning server 20 Wearable motion sensor 100 X-ray photography learning system 101 Image reading unit 102 Image display control unit 103 Attitude information receiving unit 104 Matching degree determination unit 107 Storage unit 201 Attitude information acquisition unit 202 Attitude information transmitting unit

FIG. 6 is a diagram showing a learning example 3 using the X-ray imaging learning system according to the present embodiment. When the learner 31 moves the posture of the learning collaborator 32, the posture information accompanying the posture change of the human body part is sequentially sent from the wearable motion sensor 20 to the X-ray imaging learning server 10. For example, when the learner 31 positions the head of the learning collaborator 32 in the leftward direction from the reference posture, the 3D model image displayed on the screen is also displayed while rotating in the leftward direction as if synchronized. That is, the learner 31 can search for the optimum positioning of the imaging site while moving the posture of the learning collaborator 32, and can monitor what kind of radiographic image can be captured by the positioning on the screen in real time rotation. ..

Claims (7)

An X-ray photography learning device for learning X-ray photography techniques.
An image reading means for reading clinical image data including a predetermined site imaged by an X-ray imaging device, and
An image display control means for displaying a 3D model image rendered based on the clinical image data on a display device, and an image display control means.
It has a posture information receiving means for receiving posture information regarding the amount of spatial rotation of the portion due to a posture change of the portion from a motion sensor mounted on the predetermined portion of the human body.
The image display control means rotates the portion of the 3D model image displayed on the display device in accordance with the amount of spatial rotation.
An X-ray photography learning device characterized by. A storage means that stores problems related to X-ray photography technology in association with posture information that serves as a model for each problem.
A matching degree determining means for determining the degree of matching between the posture information received by the posture information receiving means and the model posture information, and a matching degree determining means.
The X-ray photographing learning apparatus according to claim 1. The matching degree determining means outputs a natural language sentence based on the difference between the posture information received by the posture information receiving means and the model posture information.
The X-ray imaging learning apparatus according to claim 2. The human body includes a human body model,
The X-ray imaging learning apparatus according to any one of claims 1 to 3. An X-ray photography learning device for learning X-ray photography techniques.
An image reading means for reading clinical image data including a predetermined site imaged by an X-ray imaging device, and
An image display control means for displaying the clinical image data on a display device,
It has a posture information receiving means for receiving posture information indicating the posture of the portion from a motion sensor mounted on the predetermined portion of the human body.
The image display control means displays a clinical image displayed on the display device in correspondence with the posture information.
An X-ray photography learning device characterized by. An X-ray photography learning program for causing a computer to function as the X-ray photography learning device according to any one of claims 1 to 5. An X-ray photography learning system that includes an X-ray photography learning program for learning X-ray photography techniques and a motion sensor mounted on a predetermined part of the human body.
The X-ray photography learning program is
Computer,
An image reading means for reading clinical image data including the site imaged by an X-ray imaging device, and
An image display control means for displaying a 3D model image rendered based on the clinical image data on a display device, and an image display control means.
The motion sensor is made to function as a posture information receiving means for receiving posture information regarding the amount of spatial rotation of the part due to a change in the posture of the part.
The image display control means rotates the portion of the 3D model image displayed on the display device in accordance with the amount of spatial rotation.
X-ray photography learning system featuring.

Images