X-ray device

Abstract

This invention provides an X-ray apparatus that can perform X-ray fluoroscopy or X-ray radiography more reliably and quickly under appropriate conditions. The X-ray apparatus includes: an X-ray tube that irradiates X-rays; an X-ray detector that detects X-rays; an image processing unit that generates an X-ray image by performing image processing using the detection signal output by the X-ray detector; a condition storage unit that stores image acquisition conditions corresponding to part information of a subject in association with the part information; an operation table that can input an instruction for selecting a part of the subject to be irradiated with X-rays as part information; a condition readout unit that reads out the image acquisition conditions associated with the selected part information; a reference image generation unit that performs image processing on the most recently generated X-ray image based on the read-out image acquisition conditions to generate a reference image; and a reference image display unit that displays the reference image.

Description

Technical Field

[0001] This invention relates to an X-ray device for irradiating a subject with X-rays to perform X-ray fluoroscopy or X-ray photography. Background Technology

[0002] In medical settings, when using X-ray devices to obtain X-ray images of a subject through fluoroscopy or radiography, it is crucial to set appropriate X-ray exposure conditions or image processing conditions based on the area being imaged or the type of examination being performed. In recent years, X-ray devices equipped with anatomical procedures (APR) have become increasingly common as a means of setting appropriate X-ray exposure or image processing conditions.

[0003] An autopsy procedure is a data structure that pre-associates a series of X-ray irradiation conditions (e.g., tube voltage and tube current) and a series of image processing conditions (e.g., contrast processing conditions) with the radiographic location of the subject or the type of examination. Regarding autopsy procedures, multiple programs are pre-set and stored according to the radiographic location of the subject or the type of examination. For example, in the case of a conventional chest X-ray, information on the X-ray irradiation conditions and image processing conditions suitable for a conventional chest X-ray is stored in association with the conventional chest X-ray.

[0004] When performing X-ray fluoroscopy on the subject, multiple dissection procedures are displayed on the display unit, such as an LCD panel, and the operator selects the appropriate dissection procedure from the multiple dissection procedures (for example, see Patent Documents 1 and 2).

[0005] As an example, in the case of endoscopic retrograde cholangiopancreatography (ERCP) performed on the abdomen of a patient, the operator selects the "Abdomen / ERCP" program from a list of anatomical programs displayed on the monitor, such as "Chest / Routine Radiography," "Abdomen / Routine Radiography," and "Abdomen / ERCP," corresponding to the examination site and type of examination. By making this selection, the X-ray irradiation conditions and image processing parameters, pre-associated with "Abdomen / ERCP" and suitable for abdominal ERCP, are read out and displayed on the monitor. After confirming the displayed X-ray irradiation conditions, the operator begins the examination of the patient.

[0006] Existing technical documents

[0007] Patent documents

[0008] Patent Document 1: Japanese Patent Application Publication No. 2012-143443

[0009] Patent Document 2: Japanese Patent Application Publication No. 2018-191983 Summary of the Invention

[0010] The problem the invention aims to solve

[0011] However, in the case of existing examples with this structure, the following problems exist.

[0012] In the existing structure, after the operator selects the appropriate procedure, the information displayed on the screen is the numerical information of the X-ray irradiation conditions and image processing conditions. Therefore, by simply confirming these numerical parameters, it is difficult for the operator to accurately imagine in advance the X-ray image generated using those parameters. Consequently, there is a particular concern, especially for inexperienced operators, that inappropriate X-ray irradiation and image processing conditions might be selected, resulting in an unsuitable X-ray image for examination. This leads to problems such as the need for repeated X-ray irradiation, unnecessary radiation exposure, and prolonged examinations.

[0013] The present invention was made in view of this situation, and its object is to provide an X-ray apparatus capable of performing X-ray fluoroscopy or X-ray imaging more reliably and quickly under appropriate conditions.

[0014] Solution for solving the problem

[0015] To achieve this objective, the present invention employs the following structure.

[0016] That is, the X-ray apparatus according to the first aspect of the present invention comprises: an X-ray tube that irradiates an object with X-rays; an X-ray detector disposed opposite to the X-ray tube for detecting X-rays that have passed through the object; an image processing unit that generates an X-ray image by performing image processing using a detection signal output by the X-ray detector; and a condition storage unit that stores image acquisition conditions corresponding to multiple parts of the object in association with part information, wherein the image acquisition conditions include at least one of X-ray irradiation conditions and image processing conditions, and the part information is used to determine the part. The system includes: a part information; an input unit capable of inputting an indication for selecting the part of the subject to be irradiated with X-rays from multiple parts of the subject as part information; a condition readout unit that reads out the image acquisition conditions associated with the part information stored in the condition storage unit based on the part information selected by the input unit; a reference image generation unit that performs image processing on the most recently generated X-ray image based on the image acquisition conditions read out by the condition readout unit to generate a reference image; and a reference image display unit that displays the reference image generated by the reference image generation unit.

[0017] Furthermore, the X-ray apparatus according to the second aspect of the present invention includes: an X-ray tube that irradiates an examination subject with X-rays; an X-ray detector disposed opposite to the X-ray tube for detecting X-rays that have passed through the examination subject; an image processing unit that generates an X-ray image by performing image processing using a detection signal output by the X-ray detector; a condition storage unit that stores image acquisition conditions corresponding to multiple examination items of the examination subject in association with the examination items, the image acquisition conditions including at least one of X-ray irradiation conditions and image processing conditions; an input unit that can input an indication for selecting the type of examination to be performed on the examination subject from multiple examination items of the examination subject as an indication for the examination item; a condition readout unit that reads out the image acquisition conditions stored in the condition storage unit in association with the examination item based on the examination item selected by the input unit; a reference image generation unit that generates a reference image by performing image processing on the most recently generated X-ray image based on the image acquisition conditions read out by the condition readout unit; and a reference image display unit that displays the reference image generated by the reference image generation unit.

[0018] The effects of the invention

[0019] According to the X-ray apparatus of the first aspect of the present invention, the part of the subject to be irradiated with X-rays is selected as part information, and image acquisition conditions associated with the part information are read out, and a reference image is generated and displayed on a reference image display unit. The reference image is an image obtained by applying the read-out image acquisition conditions to a recently generated X-ray image for image processing. Therefore, by visually recognizing the reference image, the operator can have a general idea in advance how the generated X-ray image will look when the image acquisition conditions corresponding to the part information selected by the input unit are applied. That is, by visually recognizing the reference image, the degree of various conditions such as brightness and contrast of the X-ray image can be predicted, and thus the situation where the image acquisition conditions are actually executed with inappropriate parameters and the image acquisition conditions need to be reset can be avoided more reliably. Therefore, appropriate image acquisition conditions can be set more reliably and quickly to perform X-ray fluoroscopy or X-ray radiography.

[0020] According to the second aspect of the present invention, the X-ray apparatus selects the type of examination to be performed on the subject as the examination item, thereby reading out the image acquisition conditions associated with the examination item, generating a reference image, and displaying the reference image on the reference image display unit. The reference image is an image obtained by applying the read-out image acquisition conditions to a recently generated X-ray image for image processing. Therefore, by visually recognizing the reference image, the operator can anticipate how the generated X-ray image will look when the image acquisition conditions corresponding to the object selected using the input unit are applied. That is, by visually recognizing the reference image, the degree of various conditions such as brightness and contrast of the X-ray image can be predicted, thus more reliably avoiding situations where the image acquisition conditions are actually executed with inappropriate parameters and the image acquisition conditions need to be reset. Therefore, it is possible to more reliably and quickly set appropriate image acquisition conditions to perform X-ray fluoroscopy or X-ray radiography. Attached Figure Description

[0021] Figure 1 This is a front view illustrating the overall structure of the X-ray device involved in Embodiment 1.

[0022] Figure 2 This is a right-side view illustrating the overall structure of the X-ray apparatus involved in Embodiment 1.

[0023] Figure 3 This is a functional block diagram illustrating the general outline of the X-ray apparatus involved in Embodiment 1.

[0024] Figure 4 These are diagrams illustrating the APR of Example 1. (a) is a diagram showing the relationship between part information and image acquisition conditions associated with the part information, and (b) is a diagram showing examples of part information involved in each part and specific parameters of image acquisition conditions associated with that part information.

[0025] Figure 5 These are diagrams illustrating the various tables used in Example 1. (a) is a diagram showing an example of a standard body thickness table T1, (b) is a diagram showing an example of a body thickness correction value table T2, (c) is a diagram showing a plurality of average brightness tables T3 stored in the table storage section, and (d) is a diagram showing an example of an average brightness table T3b among the average brightness tables T3.

[0026] Figure 6 This is a flowchart illustrating a series of steps in the operation of the X-ray apparatus involved in Embodiment 1. (a) is a flowchart illustrating the general outline of the operation, and (b) is a flowchart illustrating the details of step S5.

[0027] Figure 7 This is a diagram showing the APR selection screen in step S1 of Embodiment 1.

[0028] Figure 8 This is a diagram illustrating step S2 of Example 1.

[0029] Figure 9 This is a diagram illustrating step S5 of Example 1.

[0030] Figure 10 This is a diagram illustrating the reference image display unit involved in step S5 of Embodiment 1.

[0031] Figure 11 This is a diagram illustrating the display unit involved in step S7 of Embodiment 1.

[0032] Figure 12 This is a diagram illustrating the reference image display unit used to display multiple reference images in Embodiment 1.

[0033] Figure 13 This is a diagram showing the APR selection screen of Embodiment 2.

[0034] Figure 14 The diagram illustrates the APR of Example 2. (a) is a diagram showing the relationship between inspection items and image acquisition conditions associated with the inspection items, and (b) is a diagram showing examples of specific parameters of each inspection item and the image acquisition conditions associated with that inspection item.

[0035] Figure 15 This is a diagram illustrating the reference image display unit involved in step S5 of Embodiment 2.

[0036] Figure 16 This is a diagram illustrating the display unit involved in step S7 of Embodiment 2.

[0037] Figure 17 This is a functional block diagram illustrating the general outline of the X-ray device involved in Embodiment 3.

[0038] Figure 18 This is a schematic diagram illustrating a series of steps in Example 3 using a learning model and APR readout image acquisition conditions.

[0039] Figure 19 This is a flowchart illustrating a series of procedures for operating the X-ray device involved in Embodiment 3.

[0040] Figure 20 This is a schematic diagram illustrating a series of steps for acquiring readout images in Example 3 when the chest is the irradiation field.

[0041] Figure 21 This is a diagram illustrating the reference image display unit involved in Embodiment 3. Detailed Implementation

[0042] Embodiment 1 of the present invention will now be described with reference to the accompanying drawings.

[0043] <Description of the Overall Structure>

[0044] like Figure 1 and Figure 2 As shown, in Embodiment 1, the X-ray device 1 has an X-ray tube 5 and an X-ray detector 7 arranged facing each other across a top plate 3 for supporting a supine subject M. The top plate 3 is mounted on the upper part of a top plate support 4 configured to be movable vertically. The X-ray tube 5 irradiates the subject M with X-rays. The X-ray detector 7 detects the X-rays that have irradiated the subject M from the X-ray tube 5 and passed through it, converting them into electrical signals for output as X-ray detection signals. An example of the X-ray detector 7 is an FPD (Flat Panel Detector).

[0045] X-ray tube 5 and X-ray detector 7 are respectively disposed at one end and the other end of C-arm 9. C-arm 9 is held by arm holding member 11 and configured to rotate along the arc path of C-arm 9 indicated by reference numeral RA. That is, C-arm 9 rotates along the arc path RA about the axis in the y direction (the direction of the long side of the top plate 3).

[0046] The arm holding member 11 is disposed on the side of the support column 13 and is configured to rotate about an axis (along an arc path RB) parallel to the horizontal axis P parallel to the x-direction (the direction of the short side of the top plate 3). The C-arm 9, held in the arm holding member 11, rotates about the axis in the x-direction along with the arm holding member 11. By configuring the C-arm 9 to rotate freely about two orthogonal axes along the arc paths RA and RB, X-rays can be irradiated onto the subject M from any direction.

[0047] The support column 13 is supported by a support base 15 disposed on the ground, and is configured to be horizontally movable along the upper surface of the support base 15 in both the x and y directions. The arm holding member 11 and C-arm 9, supported by the support column 13, move horizontally in either the x or y direction as the support column 13 moves horizontally. A collimator 17 is disposed on the X-ray tube 5 to confine the X-rays irradiated from the X-ray tube 5 into a predetermined shape. As an example of confining the shape of X-rays, a pyramidal shape is cited.

[0048] like Figure 3 As shown, the X-ray apparatus 1 also includes an image processing unit 19, a display unit 21, a storage unit 23, a main control unit 25, and an operating table 27.

[0049] The image processing unit 19 is located after the X-ray detector 7 and generates an X-ray image based on the X-ray detection signal output from the X-ray detector 7. The display unit 21 displays the X-ray image generated by the image processing unit 19 and various information related to the X-ray apparatus 1. Examples of display units 21 include liquid crystal monitors or high-precision displays. Examples of structures in which the display unit 21 is installed include structures suspended from the ceiling, structures mounted on a mobile trolley, and structures installed on the operating table 27.

[0050] Storage unit 23 stores various X-ray images generated by image processing unit 19, as well as various information related to the operation of X-ray device 1. As an example of storage unit 23, a non-volatile memory is provided. Storage unit 23 includes condition storage unit 29 and table storage unit 31. Condition storage unit 29 stores anatomy program 33 (APR 33). Table storage unit 31 stores various tables, including standard body thickness table T1, body thickness correction value table T2, and average brightness table T3.

[0051] Here, APR 33 related to Example 1 will be described. For example... Figure 4 As shown in (a), APR 33 is a program that is associated with image acquisition conditions 43 corresponding to the location information 41. The location information 41 is information used to determine the location of the human body to be irradiated by X-rays. Examples of locations include the shoulder, chest, abdomen, hip joint, knee, and foot. The image acquisition conditions 43 are a series of conditions related to the acquisition of X-ray images, including X-ray irradiation conditions 45 and image processing conditions 47.

[0052] X-ray irradiation conditions 45 include various parameters related to X-ray irradiation. Examples of X-ray irradiation-related parameters include the tube voltage and current applied to the X-ray tube 5, the X-ray irradiation time, and the X-ray irradiation period. Image processing conditions 47 include parameters related to image processing of the electrical signals detected by the X-ray detector 7. Examples include contrast processing values, sharpening processing values, and edge processing values. Furthermore, image acquisition conditions 43 may also include setting conditions for the X-ray detector 7, such as frame rate and gain value.

[0053] Figure 4(b) illustrates the specific content of the image acquisition condition 43 associated with the location information 41 in the APR 33 involved in Embodiment 1. As an example, the location information 41a for determining the hip joint in the location information 41 is pre-associated with the image acquisition condition 43a, which includes X-ray irradiation condition 45a and image processing condition 47a. Regarding the image acquisition condition 43a, the image processing condition 47a includes parameters such as a contrast processing value of 10 and a sharpening processing value of 7. The X-ray irradiation condition 45a includes parameters such as a tube voltage of 30kV and a tube current of 2.0mA.

[0054] Similarly, the location information 41b for determining the abdomen in the location information 41 is pre-associated with the image acquisition condition 43b, which includes X-ray irradiation condition 45b and image processing condition 47b. The location information 41c for the chest in the location information 41 is pre-associated with the image acquisition condition 43c, which includes X-ray irradiation condition 45c and image processing condition 47c. The location information 41d for the shoulder in the location information 41 is pre-associated with the image acquisition condition 43d, which includes X-ray irradiation condition 45d and image processing condition 47d. In this way, an APR 33 is pre-set to associate appropriate image acquisition conditions 43 with multiple location information 41, and the APR 33 is stored in the condition storage unit 29.

[0055] As an example, the main control unit 25 includes information processing units such as a central processing unit (CPU). The main control unit 25 uniformly controls various structures of the X-ray device 1, taking the X-ray tube 5, X-ray detector 7, C-arm 9, and image processing unit 19 as examples.

[0056] The main control unit 25 includes a condition readout unit 35 and a reference image generation unit 37. The condition readout unit 35 reads image acquisition conditions 43 associated with part information 41 corresponding to the part selected by the operator from the condition storage unit 29 by referring to APR 33. Then, the condition readout unit 35 sends the read image acquisition conditions 43 to the X-ray tube 5 or the image processing unit 19, thereby performing X-ray irradiation from the X-ray tube 5 and generating an X-ray image by the image processing unit 19 according to the sent conditions.

[0057] The image generation unit 37 generates a reference image Fs using the most recently read image acquisition condition 43 from the condition readout unit 35. The reference image Fs is an X-ray image generated by the image processing unit 19 assuming that a portion of the subject M shown in the most recently generated X-ray image has been irradiated with X-rays according to the most recently read image acquisition condition 43. The reference image Fs generated by the image generation unit 37 is displayed in the reference image display unit 39 included in the display unit 21. In this embodiment, the display unit 21 is provided with multiple image display monitors, and one of these monitors is used as the reference image display unit 39.

[0058] The operating console 27 is used to input operator instructions related to the operation of the X-ray device 1, and the main control unit 25 performs unified control according to the instructions input by the surgical operator to the operating console 27. Examples of operating devices provided with the operating console 27 include a keyboard input panel, a touch input panel, a mouse, a dial, a toggle switch, and a push-button switch. Examples of locations where the operating console 27 is located include the side of the top plate 3, the upper part of the support column 13, or a mobile trolley (not shown). In Embodiment 1, the operating console 27 is provided with a touch panel TP, and the APR 33 selection operation is performed using the touch panel TP.

[0059] The reference image generation unit 37 includes a thickness estimation unit 51, a brightness correction value calculation unit 53, and an image correction unit 55. The thickness estimation unit 51 estimates the thickness of the subject M using the average brightness value of the X-ray image generated by the image processing unit 19, the image acquisition conditions 43 read from the condition readout unit 35, and the standard thickness table T1 and thickness correction value table T2 stored in the table storage unit 31. The brightness correction value calculation unit 53 calculates a brightness correction value using the thickness value estimated by the thickness estimation unit 51 and the average brightness table T3. The image correction unit 55 uses the brightness correction value calculated by the brightness correction value calculation unit 53 to correct the brightness value of the most recently generated X-ray image, thereby generating a reference image Fs.

[0060] The various tables stored in the table storage section 31 are described. For example... Figure 5 As shown in (a), the standard body thickness table T1 is a table obtained by associating various image acquisition conditions 43 with standard body thicknesses predetermined according to each image acquisition condition 43. As an example, the parameter set suitable for acquiring X-ray images of the hip joint, namely image acquisition condition 43a, is associated with the standard body thickness R1.

[0061] like Figure 5As shown in (b), the thickness correction value table T2 is a table obtained by establishing a correlation between the brightness difference and the thickness correction value. In this embodiment, the brightness difference refers to the difference between a predetermined standard brightness value and the average brightness value of the X-ray image F generated in the X-ray device 1. In this embodiment, the standard brightness value refers to the brightness value of the X-ray image obtained when X-rays are applied to a specimen with a standard thickness and image acquisition condition 43 is used. As an example, the standard brightness value when image acquisition condition 43b is set is equivalent to the average brightness value of the X-ray image obtained by applying image acquisition condition 43b to a specimen with a standard thickness R2.

[0062] like Figure 5 As shown in (c), the average brightness table T3 is a table obtained by associating various image acquisition conditions 43 with the average brightness values ​​determined according to each image acquisition condition 43. The average brightness table T3 is created for each thickness value by acquiring X-ray images using phantoms of various thicknesses. That is, as an example, the average brightness table T3 includes multiple tables such as the average brightness table T3a applied when the thickness is 30 cm, the average brightness table T3b applied when the thickness is 40 cm, and the average brightness table T3c applied when the thickness is 50 cm.

[0063] Figure 5 (d) shows the average brightness table T3b applied when the specimen thickness is 40 cm in the average brightness table T3. That is, when an X-ray irradiation and image processing are performed on a specimen with a thickness of 40 cm according to image acquisition condition 43d, the average brightness value of the X-ray image generated by the image processing unit 19 is K4. In the X-ray apparatus 1 according to Embodiment 1, a standard thickness table T1, a thickness correction value table T2, and an average brightness table T3 are prepared in advance and stored in the table storage unit 31.

[0064] <Action Summary>

[0065] Here, use Figure 6 The flowchart shown in (a) illustrates the outline of the operation of examining the subject M using the X-ray device 1. Figure 6 (a) is a flowchart outlining the procedure for performing an examination using X-ray device 1. Figure 6 (b) is a flowchart that further explains the details of step S6, which is a main step.

[0066] In Example 1, as an example of the examination, a percutaneous coronary intervention (PCI) will be described. In the coronary intervention described in Example 1, a catheter Ch is inserted through the groin, and while confirming the catheter Ch step by step using X-ray fluoroscopy, the catheter Ch is guided to the coronary artery and a stent is placed in the coronary artery. That is, the area of ​​the subject M to be irradiated by X-ray changes from the hip joint towards the chest.

[0067] Step S1 (Selection of the target area)

[0068] When initiating an examination of subject M based on coronary intervention, the target area is first selected for X-ray irradiation to obtain the initial X-ray image. Specifically, the operator operates the control panel 27 to display the target area selection screen on the touch panel TP. Figure 7 The image shows a touch panel TP that displays a screen for selecting a part of an object.

[0069] In the target area selection screen, multiple icon groups Ac for specifying the target area are displayed on the touch panel TP. The operator selects the icon from the icon group Ac to specify the target area for X-ray irradiation and presses that icon. In Example 1, the hip joint, including the groin, is used as the target area to acquire the initial X-ray image; therefore, the operator selects the icon Ab to specify the hip joint and presses that icon Ab. Figure 7 As shown, the selected icon Ab is displayed differently compared to other icon groups Ac.

[0070] Step S2 (Setting image acquisition conditions)

[0071] When you press the icon Ab used to specify the hip joint, such as Figure 8 As shown, the information in the location information 41 indicating that the location information 41a for determining the hip joint has been selected is sent to the condition readout unit 35. The condition readout unit 35 uses the APR 33 stored in the condition storage unit 29 to search for appropriate image acquisition conditions 43 for the location involved in the received location information 41. That is, by inputting the location information 41a into the APR 33, the image acquisition conditions 43a associated with the location information 41a in the APR 33 are read out and the image acquisition conditions 43a are output.

[0072] The read image acquisition condition 43a is output from the condition readout unit 35, and as follows: Figure 7 The condition display area G1 on the touch panel TP is shown as indicated. For ease of explanation, in Figure 7In the condition display area G1, the tube voltage and tube current information in image acquisition condition 43a are displayed. An adjustment key NB is also displayed in the condition display area G1. By pressing the adjustment key NB, the operator can, for example, increase or decrease the tube voltage value from the initial value determined in image acquisition condition 43a. Additionally, the selection area display area G2 of the touch panel TP displays the area information 41 selected at the current time (here, area information 41a).

[0073] After the operator approves the image acquisition conditions 43a displayed on the touch panel TP, they press the approval icon Ad located in the lower right corner of the screen. By pressing the approval icon Ad, the image acquisition conditions 43a read by the condition readout unit 35 are set as the conditions for acquiring X-ray images. Through steps S1 and S2, the process of setting the initial image acquisition conditions 43 in the early stage before X-ray irradiation begins is completed.

[0074] Step S3 (Generation of the initial X-ray image)

[0075] After the initial image acquisition conditions 43a are set, the initial X-ray image is generated. That is, the operator operates the control panel 27 or a foot switch (not shown) to input an instruction to start X-ray irradiation. By inputting this instruction, the X-ray irradiation conditions 45a in the image acquisition conditions 43a are sent to the X-ray tube control unit (not shown). Then, the image processing conditions 47a in the image acquisition conditions 43a are sent to the image processing unit 19.

[0076] The X-ray tube control unit controls the X-ray tube 5 to irradiate X-rays according to the parameters of X-ray irradiation condition 45a. The X-ray detector 7 detects the X-rays irradiated from the X-ray tube 5 and sends the detection signal to the image processing unit 19. The image processing unit 19 performs various image processing operations, such as contrast processing, according to image processing condition 47a to generate an X-ray image F1 of the hip joint. Figure 9 As shown, in X-ray image F1, reference numeral Ba represents the pelvis, and reference numeral Bc represents the femur. The generated X-ray image F1 is displayed on display unit 21. Subsequently, X-ray images F1 are generated sequentially by intermittently irradiating with X-rays through X-ray fluoroscopy. While confirming the position of catheter Ch reflected in X-ray image F1, the operator manipulates catheter Ch to move it toward the heart.

[0077] Step S4 (Reading out the image acquisition conditions)

[0078] The operator maneuvers catheter Ch, thereby positioning catheter Ch from the hip joint towards the chest. Therefore, in order to confirm a more visible X-ray image and continue the catheterization procedure, image acquisition condition 43 needs to be changed from a condition suitable for acquiring X-ray images of the hip joint to a condition suitable for acquiring X-ray images of the chest.

[0079] Therefore, while generating X-ray images of the hip joint sequentially according to image acquisition condition 43a, new image acquisition conditions 43 are read out simultaneously. The operator then causes the touch panel TP to re-display as shown. Figure 7 The APR 33 selection screen is shown, and a new object part is selected. Here, the operator selects the icon Ae in the icon group Ac to specify the chest and presses the icon Ae.

[0080] By pressing icon Ae, chest location information 41c is sent to conditional readout unit 35. Conditional readout unit 35 inputs location information 41c to APR 33, thereby reading out image acquisition conditions 43c associated with location information 41c.

[0081] Step S5 (Referencing Image Generation)

[0082] When an X-ray image of the subject M has already been generated in the X-ray apparatus 1, when the condition readout unit 35 reads out the image acquisition condition 43, a reference image Fs is generated using the most recently read out image acquisition condition 43 and the most recently generated X-ray image. That is, the most recently read out image acquisition condition 43c by the condition readout unit 35 is sent to the reference image generation unit 37. In addition, the data of the most recently generated X-ray image (here, X-ray image F1) by the image processing unit 19 is also sent to the reference image generation unit 37.

[0083] Then, the reference image generation unit 37 generates a reference image Fs by performing new image processing on the X-ray image F1 reflecting the hip joint according to various parameters of the image acquisition condition 43c. The generated reference image Fs is as follows: Figure 10 As shown, it is displayed on the reference image display unit 39 along with the recently generated X-ray image F1. The specific steps for generating the reference image Fs will be described later.

[0084] The reference image Fs is an image obtained by virtually reproducing an X-ray image generated under the assumption that the condition readout unit 35 recently read out image acquisition condition 43 was applied to the object region of the recently generated X-ray image. Specifically, Figure 10The reference image Fs shown is not an image obtained by actually irradiating the hip joint with X-rays, but rather an image reproduced by reproducing an X-ray image generated under the assumption that the hip joint was irradiated with X-rays using image acquisition condition 43c. By visually viewing the X-ray image F1 and the reference image Fs displayed on the reference image display unit 39, the operator can understand the change in the appearance of the X-ray image envisioned when the image acquisition condition 43 used to acquire the X-ray image is changed from image acquisition condition 43a to image acquisition condition 43c.

[0085] Step S6 (Approval of image acquisition conditions)

[0086] The operator determines whether the image acquisition condition 43c is appropriate for the subsequent X-ray fluoroscopy of the chest area by checking visual elements such as the brightness, contrast, and sharpness of the reference image Fs. That is, in this embodiment, in addition to displaying the parameters of the image acquisition condition 43 as numerical information on the display unit 21, the reference image Fs as image information is also displayed on the display unit 21. Then, the operator can determine whether the image acquisition condition 43 is appropriate for the subsequent acquisition of X-ray images by using both numerical and image information as clues.

[0087] If the image acquisition condition 43c is deemed appropriate, the operator approves the image acquisition condition 43c. This operation sets the image acquisition condition 43c, read by the condition readout unit 35, as the condition for acquiring X-ray images. Examples of the operator approving the image acquisition condition 43c include pressing the approval icon Ad and selecting the reference image Fs. If the reference image display unit 39 is a monitor, the operator selects the reference image Fs using a mouse or keyboard. If the reference image display unit 39 is a touch panel, the operator selects the reference image Fs by touching it.

[0088] Furthermore, if it is determined that the image acquisition condition 43c is inappropriate, the process returns to step S4, selects an icon from the icon group Ac for specifying other object parts, and presses that icon. The condition reading unit 35 reads the image acquisition condition 43 associated with the part information 41 corresponding to the pressed icon, and the reference image generation unit 37 generates the reference image Fs again.

[0089] Step S7 (Generation of X-ray image)

[0090] With image acquisition condition 43c approved by referring to image Fs, an X-ray image of the chest area of ​​subject M is generated. The operator operates C-arm 9 to move the X-ray field from the hip joint of subject M towards the chest. Then, the X-ray irradiation is started by operating the control panel 27 or foot switch, etc. By inputting this instruction, X-ray irradiation condition 45c in image acquisition condition 43c is sent to the X-ray tube control unit (not shown). Then, image processing condition 47c in image acquisition condition 43c is sent to the image processing unit 19.

[0091] The X-ray tube control unit controls the X-ray tube 5 to irradiate X-rays from the X-ray tube 5 according to the parameters of X-ray irradiation condition 45c. The image processing unit 19 performs various image processing according to the image processing condition 47c to generate an X-ray image F2 of the chest area. Furthermore, if other image acquisition conditions 43 are set again, the process returns to step S4 to read out the image acquisition conditions.

[0092] like Figure 11 As shown, the generated X-ray image F2 is displayed on display unit 21. The generated chest X-ray image F2 shows the heart H, lung Lu, and catheter Ch. Then, X-ray images F2 are generated sequentially by intermittently irradiating with X-ray fluoroscopy. While confirming the X-ray image F2, the operator manipulates catheter Ch to place a stent in the coronary artery, thereby concluding the PCI procedure.

[0093] <Details of the process for generating the reference image>

[0094] Here, the process of generating the reference image in step S5 will be described in detail. Figure 6 (b) is a flowchart illustrating the series of processes involved in step S5.

[0095] Step S51 (Estimation of body thickness)

[0096] When the process involved in step S5 begins, the process of estimating the thickness of the subject M is started in the reference image generation unit 37. That is, the X-ray image (here, X-ray image F1) recently generated by the image processing unit 19 and the image acquisition condition 43 (here, image acquisition condition 43c) recently read out by the condition readout unit 35 are sent to the thickness estimation unit 51. In addition, the thickness estimation unit 51 reads the standard thickness table T1 and the thickness correction value table T2 stored in the table storage unit 31, and reads the standard brightness value NS data that has been stored in the storage unit 23, etc.

[0097] The thickness estimation unit 51 first uses the data from the most recently read image acquisition condition 43 and the standard thickness table T1 to determine the value of the standard thickness. For example... Figure 5As shown in (a), in the standard body thickness table T1, the value of the standard body thickness corresponding to the image acquisition condition 43c is R3. Therefore, the body thickness estimation unit 51 determines the standard body thickness value R3.

[0098] Next, the thickness estimation unit 51 uses the recently generated X-ray image of the subject M and the standard brightness value NS to calculate the brightness difference D. In this embodiment, the thickness estimation unit 51 calculates the average brightness value N1 of the X-ray image F1, and calculates the brightness difference D by subtracting the average brightness value N1 from the standard brightness value NS. The structure of the thickness estimation unit 51 calculating the average brightness value N1 of the X-ray image F1 is not limited to this; the average brightness value N1 of the X-ray image F1 may also be calculated in the image processing unit 19, or by a processor other than the thickness estimation unit 51 in the main control unit 25.

[0099] Finally, the thickness estimation unit 51 estimates the thickness of the subject M using the thickness correction value table T2, the brightness difference D, and the standard thickness value corresponding to the image acquisition condition 43. Generally, when the thickness of the subject is large, the brightness value of the X-ray image of the subject decreases. Therefore, the larger the value obtained by subtracting the standard thickness from the thickness of the subject M, the larger the value obtained by subtracting the brightness value of the X-ray image of the subject M from the standard brightness value NS. As an example, when the brightness difference D is 20, such as Figure 5 As shown in (b), the body thickness correction value is 4 cm. Therefore, the value obtained by adding 4 cm to the standard body thickness value R3 corresponding to image acquisition condition 43c is estimated as the body thickness value of the subject M. The estimated body thickness value of the subject M is calculated as the estimated body thickness value L. The estimated body thickness value L calculated by the body thickness estimation unit 51 is sent to the brightness correction value calculation unit 53.

[0100] Step S52 (Calculation of brightness correction value)

[0101] After the estimated body thickness value L is calculated by the body thickness estimation unit 51, the brightness correction value is calculated. First, the brightness correction value calculation unit 53 selects a table to be read from among a plurality of average brightness tables T3 stored in the table storage unit 31, referring to the estimated body thickness value L. As an example, if the estimated body thickness value L is 40cm, the average brightness table T3b corresponding to a body thickness of 40cm is selected from the average brightness tables T3 and read into the brightness correction value calculation unit 53. Furthermore, if there is no average brightness table T3 that matches the estimated body thickness value L, the average brightness table T3 corresponding to the body thickness closest to the estimated body thickness value L is read.

[0102] Next, the brightness correction value calculation unit 53 calculates the brightness correction value Q by referring to the selected average brightness table T3, the image acquisition conditions 43 used in the most recently generated X-ray image, and the image acquisition conditions 43 most recently selected using the touch panel TP. In the selected average brightness table T3, when the average brightness corresponding to the image acquisition conditions 43 used in the most recently generated X-ray image is set to HA, and the average brightness corresponding to the most recently selected image acquisition conditions 43 is set to HB, the brightness correction value calculation unit 53 calculates the value obtained by subtracting the average brightness HA from the average brightness HB as the brightness correction value Q. If the average brightness HA is a value greater than the average brightness HB, the brightness correction value Q becomes a negative value.

[0103] The structure for calculating the luminance correction value Q is further explained in detail using specific numerical examples. In Example 1, a specific numerical example was selected. Figure 5 The average brightness table T3b shown in (d) uses image acquisition condition 43a for the most recently generated X-ray image F1. In the average brightness table T3b corresponding to a body thickness of 40 cm, the average brightness value corresponding to image acquisition condition 43a is K1.

[0104] Furthermore, the recently selected image acquisition condition 43 is the image acquisition condition 43c corresponding to the chest area information 41c selected in step S4. In the average brightness table T3b corresponding to the body thickness 40cm, the average brightness value corresponding to image acquisition condition 43c is K3. That is, the average brightness HA value is K1, and the average brightness HB value is K3. Therefore, the brightness correction value calculation unit 53 calculates the value of (K3-K1) as the brightness correction value Q. The calculated brightness correction value Q is sent to the image correction unit 55. In addition, the data of the X-ray image F1 recently generated by the image processing unit 19 is also sent to the image correction unit 55.

[0105] Step S53 (Correction of X-ray image)

[0106] The image correction unit 55 generates a reference image Fs using the brightness correction value Q and data from the recently generated X-ray image F1. Specifically, the image correction unit 55 corrects the X-ray image F1 by adding the brightness correction value Q to each pixel of the X-ray image F1. When an X-ray image is acquired using image acquisition conditions 43a, which include parameters such as tube voltage 30kV and tube current 2.0mA, for a 40cm specimen, the average brightness of each pixel in the X-ray image is K1. Furthermore, when an X-ray image is acquired using image acquisition conditions 43c, which include parameters such as tube voltage 60kV and tube current 3.5mA, for a 40cm specimen, the average brightness of each pixel in the X-ray image is K3.

[0107] That is, when the image acquisition condition 43 involved in the X-ray image is changed from image acquisition condition 43a to image acquisition condition 43c, the brightness of the X-ray image is considered to increase by a value of (K3-K1). Therefore, by adding the value of (K3-K1) to each pixel of the X-ray image F1 obtained according to image acquisition condition 43a, a reference image Fs that takes into account the change in brightness value caused by changing each parameter from image acquisition condition 43a to image acquisition condition 43c can be generated. In other words, the reference image Fs is generated based on the X-ray image F1 actually generated by irradiating the hip joint with X-rays based on image acquisition condition 43a, and serves as the X-ray image envisioned when the hip joint is irradiated with X-rays using image acquisition condition 43c.

[0108] Step S54 (Refer to the image display)

[0109] After generating a reference image Fs by adding a brightness correction value Q, the data of reference image Fs is sent from the image correction unit 55 to the reference image display unit 39. Additionally, the data of the most recently generated X-ray image from the image processing unit 19 is also sent to the reference image display unit 39. The reference image display unit 39 displays the most recently generated X-ray image F1 and the reference image Fs generated by the image correction unit 55 side-by-side. By displaying the reference image Fs in the reference image display unit 39, the series of actions involved in step S5 is completed.

[0110] Furthermore, the structure for generating reference images Fs is not limited to being based solely on image acquisition conditions 43 associated with the object region selected in step S4. That is, multiple reference images Fs can also be created based on the individual image acquisition conditions 43 associated with multiple regions adjacent to the object region in the most recently generated X-ray image or with multiple regions adjacent to the object region selected in step S4.

[0111] As an example, if the chest is selected as the target area in step S4, such as Figure 12 As shown, in addition to the image acquisition condition 43 associated with the chest, three reference images Fs are generated based on the image acquisition conditions 43 associated with adjacent parts of the chest, namely the abdomen and the shoulder, and these reference images Fs are displayed. In this case, the three images are displayed as reference images Fs: reference image Fs1 generated using X-ray image F1 and image acquisition condition 43c corresponding to the chest, reference image Fs2 generated using X-ray image F1 and image acquisition condition 43b corresponding to the abdomen, and reference image Fs3 generated using X-ray image F1 and image acquisition condition 43d corresponding to the shoulder.

[0112] Referring to image Fs2, a virtual X-ray image is generated by performing new image processing on the X-ray image F1 reflecting the hip joint according to the image acquisition condition 43b corresponding to the abdomen. When the estimated body thickness L and brightness difference D of the subject M are the same as in steps S51 to S54 above, as follows... Figure 5 As shown in (d), the average brightness of the X-ray image acquired using the image acquisition condition 43b corresponding to the abdomen is K2. Therefore, the brightness correction value Q calculated by the brightness correction value calculation unit 53 is (K2-K1). Therefore, the image correction unit 55 generates the reference image Fs2 by adding the brightness value of (K2-K1) to the brightness value of each pixel of the X-ray image F1.

[0113] Similarly, the reference image Fs3 is a virtual X-ray image generated by performing new image processing on the X-ray image F1 reflecting the hip joint according to the image acquisition condition 43d corresponding to the shoulder. Figure 5 As shown in (d), the average brightness of the X-ray image acquired using image acquisition condition 43d corresponding to the shoulder is K4. Therefore, the brightness correction value Q calculated by the brightness correction value calculation unit 53 is (K4-K1). Therefore, the image correction unit 55 generates the reference image Fs3 by adding the brightness value of (K4-K1) to the brightness value of each pixel of the X-ray image F1.

[0114] By displaying reference images Fs1 to Fs3 together with the X-ray image F1, the operator can visually confirm not only the appearance of the envisioned X-ray image when the image acquisition condition 43 corresponding to the chest is actually selected using the operating table 27, but also the appearance of the envisioned X-ray image when the image acquisition condition 43 corresponding to each object part close to the chest is applied. By generating reference images for multiple parts, the quality and quantity of information obtained by the operator visually can be further improved. Therefore, the appropriate image acquisition condition 43 can be more reliably selected for actual X-ray irradiation.

[0115] [Example 2]

[0116] Next, Embodiment 2 of the present invention will be described. The overall structure of the X-ray device 1A involved in Embodiment 2 is similar to that described above. Figure 1 The overall structure of the X-ray apparatus 1 involved in Embodiment 1 is basically the same. Therefore, in Embodiment 2, the same reference numerals are used to refer to the same structures as in Embodiment 1, and detailed descriptions are omitted.

[0117] The X-ray apparatus 1A described in Embodiment 2 differs from Embodiment 1, which uses an APR 33A that associates image acquisition conditions 43 with inspection item information 61, in that it uses an APR 33 that associates image acquisition conditions 43 with location information 41. Furthermore, in Embodiment 2, a reference image Fs corresponding to the image acquisition conditions 43 associated with the selected inspection item is displayed by selecting an inspection item instead of the object location. The structure for generating and displaying the reference image Fs in Embodiment 2 will now be described.

[0118] Generally, if the object shown in an X-ray image is different, the various parameters of the image acquisition conditions 43 suitable for acquiring that X-ray image will be different. However, even if the object in the X-ray image is the same, if the type of examination performed on that object (also called the examination item or procedure) is different, the various parameters of the image acquisition conditions 43 suitable for acquiring that X-ray image will also be different.

[0119] As an example, the image acquisition conditions 43 suitable for obtaining X-ray images differ between a routine X-ray imaging procedure performed without any insertion into the abdomen and an endoscopic retrograde cholangiopancreatography (ERCP) procedure performed with an endoscope inserted into the abdomen. That is, the visibility of the X-ray image is affected by the examination equipment, such as a catheter or endoscope, and the presence or absence of examination agents, such as contrast agents. Therefore, the various parameters of the appropriate image acquisition conditions 43 differ depending on the examination procedure.

[0120] Therefore, in Embodiment 2, the touch panel TP is used to select the inspection item in steps S1 and S4. Figure 13 A touch panel TP is shown, displaying a screen for selecting examination items. The touch panel TP according to Example 2 displays multiple icon groups Bc for specifying examination items. As an example, when selecting a routine chest X-ray as the examination item, the icon Ba for "Chest / Routine" is selected. When selecting a procedure involving the insertion of a catheter into the chest for PCI, the icon Bd for "Chest / PCI" is selected. When selecting an upper gastrointestinal X-ray series (UGI) for the abdomen, the icon Bf for "Abdomen / UGI" is selected.

[0121] Here, APR 33A related to Example 2 will be described. For example... Figure 14As shown in (a), APR33A is a program that is associated with image acquisition conditions 43 corresponding to the examination item information 61. The examination item information 61 is information used to determine the examination items to be performed on the subject. That is, by inputting the examination item information 61 into APR33A, APR33A outputs image acquisition conditions 43 corresponding to the examination items involved in the examination item information 61.

[0122] Figure 14 (b) illustrates the specific content of the image acquisition conditions 43 associated with the examination item information 61 in the APR 33A involved in Embodiment 2. As an example, the examination item information 61a, which includes a chest X-ray, is associated in advance with the image acquisition condition 43e, which includes X-ray irradiation condition 45e and image processing condition 47e. The examination item information 61b, which includes a chest PCI, is associated in advance with the image acquisition condition 43f. The examination item information 61c, which includes an abdominal X-ray, is associated in advance with the image acquisition condition 43g. The examination item information 61d, which includes an abdominal UGI, is associated in advance with the image acquisition condition 43h. Thus, in Embodiment 2, an APR 33A is pre-set to associate appropriate image acquisition conditions 43 with each of the multiple examination item information 61, and this APR 33A is stored in the condition storage unit 29.

[0123] The series of procedures for examining the subject M using the X-ray apparatus 1A according to Example 2 are the same as in Example 1, except that in steps S1 and S4, the examination item is selected instead of the target area. In Example 2, the case in which a normal abdominal radiograph is first performed to obtain an X-ray image, and then a contrast agent is administered orally to the subject M to perform an abdominal UGI X-ray radiograph will be described as an example.

[0124] First, in step S1 of Embodiment 2, the examination item related to the initially acquired X-ray image is selected. That is, the operator operates the control panel 27 to display the examination item selection screen on the touch panel TP (see...). Figure 13 Then, select the icon for specifying the target examination item from the icon group Bc and press that icon. Here, select the icon for specifying the examination item for abdominal radiography, namely the icon Bh displayed as "Abdomen / Routine" and press that icon Bh.

[0125] When an examination item is selected, step S2 is entered, and image acquisition conditions 43 are set for acquiring the initial X-ray image. That is, the information in the examination item information 61 indicating that the examination item information 61c, which determines abdominal radiography as an examination item, has been selected, is sent to the condition readout unit 35. The condition readout unit 35 uses the APR 33A stored in the condition storage unit 29 to read the image acquisition conditions 43g associated with the examination item information 61c and outputs the image acquisition conditions 43g. The read image acquisition conditions 43g are as follows: Figure 13 The condition display area G1 on the touch panel TP is shown as indicated. Additionally, the inspection item information 61c selected by the operator is displayed in the selection area G2. The operator sets the image acquisition condition 43g to the conditions for acquiring X-ray images by pressing the approval icon Ad.

[0126] When image acquisition conditions 43g are set, step S3 is entered to acquire the initial X-ray image. That is, the operator operates the control panel 27, etc., to input an instruction to begin X-ray irradiation. By inputting this instruction, X-ray irradiation and various image processing are performed based on the set image acquisition conditions 43g to generate an abdominal X-ray image F3. The generated X-ray image F3 is displayed on the display unit 21. Figure 15 As shown, in X-ray image F3, the reference numeral Ga represents the stomach, and the reference numeral Sh represents the lumbar spine.

[0127] Upon acquiring the initial X-ray image, the process proceeds to step S4, initiating the readout of new image acquisition conditions. Since the next inspection item to be performed is the abdominal UGI, the operator re-displays the selection screen of APR 33A on the touch panel TP, selects the icon for specifying the abdominal UGI (displayed as "Abdomen / UGI"), and presses icon Bf. By pressing icon Bf, the abdominal UGI inspection item information 61d is sent to the condition readout unit 35. The condition readout unit 35 reads out the image acquisition conditions 43h associated with the inspection item information 61d by inputting the inspection item information 61d into APR 33A.

[0128] When the newly read image acquisition condition 43 is displayed, step S5 is initiated to begin the process of generating the reference image Fs. First, data from the X-ray image F3 most recently generated by the image processing unit 19 and data from the image acquisition condition 43h most recently read by the condition readout unit 35 are sent to the thickness estimation unit 51 of the reference image generation unit 37. The thickness estimation unit 51 uses the standard thickness table T1, the thickness correction value table T2, the standard brightness value NS, the average brightness value N3 of the X-ray image F3, and the image acquisition condition 43h to estimate the thickness of the subject M and calculate the estimated thickness value L (step S51).

[0129] Next, the brightness correction value calculation unit 53 reads the average brightness table T3 corresponding to the estimated volume thickness value L. Then, using the read average brightness table T3, it determines the average brightness HA corresponding to the image acquisition condition 43g used in the most recently generated X-ray image F3 and the average brightness HB corresponding to the most recently selected image acquisition condition 43h. Finally, the brightness correction value calculation unit 53 calculates the value obtained by subtracting the average brightness HA from the average brightness HB as the brightness correction value Q (step S52).

[0130] The image correction unit 55 corrects each pixel of the recently generated X-ray image F3 by adding a brightness correction value Q to generate a reference image Fs (step S53). The generated reference image Fs is as follows: Figure 15 As shown, it is displayed together with X-ray image F3 on reference image display unit 39 (step S54). By visually viewing X-ray image F3 and reference image Fs, the operator can understand the changes in the appearance of the X-ray image envisioned when abdominal UGI is performed without the administration of contrast agent and X-ray irradiation.

[0131] When the reference image Fs is displayed, proceed to step S6. The operator confirms the brightness, etc., of the reference image Fs and determines whether the image acquisition condition 43h is appropriate for the subsequent abdominal UGI. If it is deemed appropriate, the operator approves the image acquisition condition 43h. Through this operation, the image acquisition condition 43h is set as the condition for acquiring X-ray images.

[0132] When the new image acquisition conditions 43h are approved, the process proceeds to step S7 to generate an X-ray image. The operator administers contrast agent to the subject M and operates the operating table 27, etc., to input instructions to begin X-ray irradiation. By inputting these instructions, X-ray irradiation and various image processing are performed based on the image acquisition conditions 43h set in step S6 to generate an X-ray image F4 of the abdominal UGI. Figure 16 As shown, the generated X-ray image F4 is displayed on display unit 21. The operator confirms the contrast agent Ct and other substances reflected in the X-ray image F4 to complete the UGI.

[0133] In Example 2, the examination item information 61 is associated with the image acquisition condition 43 in APR 33A. Furthermore, it has the following structure: when an examination item is selected, the image acquisition condition 43 associated with the corresponding examination item information 61 is read out, and a reference image Fs is generated using the read-out image acquisition condition 43 and a recently generated X-ray image, etc. In this structure, reference images Fs are generated not only when the object location changes, but also when the examination item changes due to endoscope insertion or contrast agent administration.

[0134] That is, by selecting the examination item for contrast agent testing before contrast agent administration, the image acquisition conditions 43 corresponding to the contrast agent testing item are read out. Then, a reference image Fs is generated using the image acquisition conditions 43, etc., as the X-ray image envisioned after contrast agent administration. By visually viewing this reference image Fs, the operator can obtain not only numerical information such as parameters, but also image information such as image visibility. Therefore, it is possible to determine with greater accuracy whether the image acquisition conditions 43 are appropriate for the examination of the subject M before contrast agent administration. Thus, it is possible to avoid situations where the image acquisition conditions 43 are found to be inappropriate after contrast agent administration and actual X-ray irradiation, requiring re-administration of contrast agent and re-irradiation, thereby reducing the burden on the operator and the subject.

[0135] [Example 3]

[0136] Next, Embodiment 3 of the present invention will be described. In Embodiment 1, the operator manually selects the object part using a touch panel TP or the like. On the other hand, in the X-ray apparatus 1B according to Embodiment 3, a learning model constructed through machine learning is used to automatically determine the object part reflected in the X-ray image. Here, Embodiment 3, like Embodiment 1, includes an APR 33 that establishes an association between the part information 41 and the image acquisition condition 43. Therefore, Embodiment 3 has a structure that automatically reads out the image acquisition condition 43 corresponding to the X-ray image by acquiring the X-ray image. The characteristic structure of Embodiment 3 will now be described.

[0137] The X-ray device 1B involved in Example 3 is as follows: Figure 17 As shown, a machine learning unit 71 and an image analysis unit 73 are provided in the main control unit 25. Furthermore, a learning model storage unit 75 is provided in the storage unit 23.

[0138] The machine learning unit 71 creates a learning model 77 by performing machine learning on pre-acquired X-ray images or optical images. The image analysis unit 73 analyzes the X-ray images or optical images generated by the X-ray device 1B using the learning model 77 to determine the object parts reflected in the images. The learning model storage unit 75 stores the learning model 77 constructed by the machine learning unit 71.

[0139] Here, use Figure 18 The structure of Example 3, which automatically reads out image acquisition condition 43 by acquiring X-ray or optical images, will be described.

[0140] First, as in Figure 18 The learning model 77 is pre-created as shown by reference numeral M1 in the attached diagram. That is, the learning model 77 is created in advance by performing machine learning in the machine learning unit 71. The machine learning unit 71 pre-acquires images of various parts of the human body as the source image R1. As an example, the source image R1 is a group of multiple images including X-ray images, DRR images obtained by projecting three-dimensional CT images in various directions, optical images acquired by an optical camera, etc.

[0141] Then, the machine learning unit 71 performs image processing on the original image R1 to address changes in X-ray conditions, such as increasing or decreasing contrast, increasing or decreasing brightness, and increasing or decreasing noise, thereby obtaining multiple one-dimensional data-enhanced images R2. Then, the machine learning unit 71 performs image processing on the one-dimensional data-enhanced images R2 to address changes in the configuration of the subject M or the position of the C-arm 9, such as rotating, enlarging, and shrinking, thereby obtaining multiple two-dimensional data-enhanced images R3.

[0142] Furthermore, the machine learning unit 71 performs machine learning on the original image R1, the one-dimensional data-enhanced image R2, and the two-dimensional data-enhanced image R3 as training images to create a learning model 77 for inferring the parts of the human body reflected in the image. That is, by inputting an X-ray image F or an optical image D as input information into the learning model 77, the learning model 77 infers which part of the human body is reflected in the input image and outputs the inferred information about the human body part. The learned learning model 77 is stored in the learning model storage unit 75.

[0143] Furthermore, while Embodiment 3 illustrates a structure for creating a learning model 77 within the X-ray apparatus 1B, the learning model 77 can also be created in advance using other devices, and the program for the created learning model 77 can be stored in the learning model storage unit 75. In this case, the machine learning unit 71 can be omitted from the X-ray apparatus 1B.

[0144] Second, as in Figure 18As indicated by reference numeral M2 in the attached diagram, the image is analyzed to obtain information about the regions reflected in the image. Specifically, the image analysis unit 73 analyzes the image using the learning model 77 to determine the regions of the subject M reflected in the image obtained for the subject M. That is, the image analysis unit 73 reads the learning model 77 stored in the learning model storage unit 75.

[0145] Then, after the image processing unit 19 generates an X-ray image of the subject M through X-ray irradiation, the X-ray image F sent from the image processing unit 19 is input as an input image to the learning model 77. The learning model 77 analyzes the input image using the constituent elements of the human body reflected in the input X-ray image as clues, and infers the location of the subject M reflected in the input image. The location information obtained through inference is output from the learning model 77 as location information 41. The input image is not limited to the X-ray image F; an optical image D captured by an optical camera (not shown) may also be used as the input image.

[0146] Furthermore, the learning model 77 outputs multiple site information 41 along with accuracy results from parsing the input image. For example, when X-ray image F1 is input to the learning model 77, the following information is output: the accuracy for the site reflected in X-ray image F1 is 91.4% for the hip joint, 1.4% for the head and neck, 4.2% for the chest, and 0.1% for the abdomen. The output multiple site information 41, along with the accuracy information, are sent from the image parsing unit 73 to the conditional readout unit 35. Alternatively, the image parsing unit 73 may not send all site information 41, but instead select a predetermined number of site information 41 in descending order of accuracy and send them to the conditional readout unit 35.

[0147] Third, as in Figure 18 As shown by reference numeral M3 in the accompanying drawings, the condition readout unit 35 reads out the image acquisition condition 43. That is, the condition readout unit 35 uses the part information 41 obtained by the image analysis unit 73 and the APR 33 to read out the appropriate image acquisition condition 43. The condition readout unit 35 inputs the part information 41 obtained by the image analysis unit 73 into the APR 33, reads out the image acquisition condition 43 stored in the APR 33 in association with the part information 41, and outputs the image acquisition condition 43.

[0148] The output image acquisition condition 43 is set as the condition to be used in the subsequent acquisition of the X-ray image. The newly set image acquisition condition 43 as the condition for acquiring the X-ray image is sent to the X-ray tube control unit and image processing unit 19 (not shown), thereby generating a new X-ray image of the subject M according to the various parameters of the set image acquisition condition 43. Thus, in Embodiment 3, the image acquisition condition 43 to be used in the subsequent acquisition of the X-ray image is automatically read out by using the most recently acquired X-ray image F, etc., as the input image.

[0149] <Action in Example 3>

[0150] Here, we will specifically describe the operation of examining the subject M using the X-ray device 1B while the learning model 77 and APR 33 are stored in the storage unit 23. Figure 19 This is a flowchart illustrating a series of steps in the operation of the X-ray apparatus 1B involved in Embodiment 3. In Embodiment 3, the example of performing multiple conventional X-ray imaging examinations on the chest of the subject M will be used for explanation.

[0151] Step P1 (Select the target area)

[0152] When the examination of subject M begins, the target area to be irradiated by X-rays is first selected to obtain the initial X-ray image. In generating the initial X-ray image, there is no input image for the image analysis unit 73. Therefore, in step P1, similar to step S1 in Embodiment 1, the operator manually selects the target area. That is, the operator operates the operation table 27, such as... Figure 7 As shown, display the target area selection screen on the touch panel TP, and press the icon Ae to specify the chest as the target area.

[0153] Step P2 (Setting image acquisition conditions)

[0154] When a target area is selected, image acquisition conditions 43 are set based on the selected target area. The process of step P2 in Embodiment 3 is similar to the process of step S2 in Embodiment 1. That is, when the icon Ae for specifying the chest is pressed, information indicating that the chest area information 41c has been selected is sent to the condition readout unit 35. The condition readout unit 35 reads out the image acquisition conditions 43c associated with the area information 41c using APR 33. The read out image acquisition conditions 43c are displayed in the condition display area G1 of the touch panel TP. The operator sets the image acquisition conditions 43c read out by the condition readout unit 35 as the conditions for acquiring the initial X-ray image by pressing the approval icon Ad.

[0155] Step P3 (Generation of the initial X-ray image)

[0156] When the initial image acquisition condition 43 is set, the initial X-ray image is generated. The procedure of step P3 in Embodiment 3 is similar to the procedure of step S3 in Embodiment 1. That is, after setting the image acquisition condition 43c to the initial image acquisition condition 43, the operator operates the control panel 27, etc., to input an instruction to start X-ray irradiation.

[0157] By entering this instruction, such as Figure 20 As shown, X-rays are irradiated from the X-ray tube 5 onto the chest Lc according to X-ray irradiation condition 45c in X-ray acquisition condition 43c. Then, the image processing unit 19 performs various image processing on the X-ray detection signal of the X-ray detector 7 according to image processing condition 47c in image acquisition condition 43c. The image processing by the image processing unit 19 generates an X-ray image F5 of the chest as the target area. The generated X-ray image F5 is displayed on the display unit 21.

[0158] Step P4 (Input image parsing)

[0159] In the X-ray apparatus 1B according to Embodiment 3, when an X-ray image is acquired, the X-ray image can be analyzed and the image acquisition condition 43 can be automatically read out. Furthermore, a reference image can be generated using the X-ray image and the image acquisition condition 43. Therefore, the initially generated X-ray image F5 is used as an input image and analyzed by the image analysis unit 73.

[0160] When step P4 begins, as Figure 20 As shown, the data of X-ray image F5 is sent to image analysis unit 73 as the most recently generated X-ray image. Image analysis unit 73 inputs X-ray image F5 as input image to learning model 77. Learning model 77 analyzes X-ray image F5 as input information to estimate the location reflected in X-ray image F5. The estimated location information is output as location information 41 along with its accuracy. In this embodiment, as an example, the learning model 77 estimates that the location reflected in X-ray image F5 is the chest with an accuracy of 80%, the abdomen with an accuracy of 15%, and the hip joint with an accuracy of 5%. As a result, learning model 77 outputs location information 41c for determining the chest, location information 41b for determining the abdomen, and location information 41a for determining the hip joint along with their respective accuracy, and sends them to conditional readout unit 35.

[0161] Step P5 (Reading out the image acquisition conditions)

[0162] When the input image is parsed and part information 41 is output, the part information 41 and APR 33 are used to read the image acquisition condition 43. That is, as Figure 20 As shown, the condition readout unit 35 inputs the received part information 41a to 41c into the APR 33 and searches for image acquisition conditions 43 corresponding to the part information 41a to 41c respectively. Image acquisition condition 43a is associated with part information 41a. Image acquisition condition 43b is associated with part information 41b, and image acquisition condition 43c is associated with part information 41c. Therefore, the condition readout unit 35 reads out image acquisition conditions 43a, 43b, and 43c. Thus, when the initial X-ray image F5 is generated, image acquisition conditions 43a to 43c are automatically read out through the processes of steps P4 and P5. The automatically read out image acquisition conditions 43a to 43c are sent from the condition readout unit 35 to the reference image generation unit 37. In addition, the data of the most recently generated X-ray image, i.e., X-ray image F5, is sent to the reference image generation unit 37.

[0163] Step P6 (Referencing Image Generation)

[0164] When the recently read image acquisition conditions 43 (here, image acquisition conditions 43a to 43c) and the data of the recently generated X-ray image are sent to the reference image generation unit 37, the process of generating the reference image Fs involved in step P6 begins. The process of step P6 is the same as the process of step S5 involved in Embodiment 1.

[0165] In this embodiment, since three image acquisition conditions 43a, 43b, and 43c have been recently read out, three reference images Fs are generated for each of the image acquisition conditions 43a to 43c. That is, based on the image of a chest X-ray, i.e., X-ray image F5, new image processing is performed according to various parameters of image acquisition condition 43a, thereby generating the first reference image FsA.

[0166] The specific generation process of the reference image FsA is described below. The thickness estimation unit 51 first uses the most recently read image to acquire data from condition 43a and the standard thickness table T1, such as... Figure 5As shown in (a), the standard body thickness value R1 corresponding to image acquisition condition 43a is determined. Then, the body thickness estimation unit 51 calculates the brightness difference D by subtracting the average brightness value of the most recently generated X-ray image F5 from the standard brightness value predetermined based on the standard body thickness R1 and image acquisition condition 43a. Finally, the body thickness estimation unit 51 calculates the estimated body thickness value L of the subject M using the body thickness correction value table T2, the brightness difference D, and the standard body thickness value R1 (see step S51). Next, the brightness correction value calculation unit 53 calculates the brightness correction value Q1 using the estimated body thickness value L, the average brightness table T3, the image acquisition condition 43c used in the most recently generated X-ray image F5, and the most recently read image acquisition condition 43a (see step S52). Then, the image correction unit 55 adds the brightness correction value Q1 to the brightness value of each pixel of the X-ray image F5 to generate a reference image FsA.

[0167] Similarly, based on X-ray image F5, new image processing is performed according to various parameters of image acquisition condition 43b, thereby generating a second reference image FsB. Based on X-ray image F5, new image processing is performed according to various parameters of image acquisition condition 43c, thereby generating a third reference image FsC. However, in the case of generating reference image FsB, the data of image acquisition condition 43b is used as the most recently read image acquisition condition 43. Moreover, in the case of generating reference image FsC, the data of image acquisition condition 43c is used as the most recently read image acquisition condition 43.

[0168] The generated reference images FsA, FsB, and FsC are respectively as follows: Figure 21 As shown, the X-ray image F5 recently generated by the image processing unit 19 is displayed on the reference image display unit 39. Reference image FsA is an X-ray image generated assuming that X-rays were irradiated on the chest area using image acquisition condition 43a. Reference image FsB is an X-ray image generated assuming that X-rays were irradiated on the chest area using image acquisition condition 43b.

[0169] Step P7 (Approval of image acquisition conditions)

[0170] The operator visually identifies the reference images FsA to FsC and the X-ray image F5 displayed on the reference image display unit 39 to determine which of the image acquisition conditions 43a to 43c is most suitable as the image acquisition condition 43 for acquiring the next generated X-ray image. The operator then selects and approves the image acquisition condition 43 deemed most suitable. For example, if image acquisition condition 43b is deemed suitable, the operator approves it by clicking on the reference image FsB with the mouse. By performing this approval indication, the approved image acquisition condition 43b is set as the image acquisition condition 43 to be used when acquiring the second X-ray image.

[0171] Step P8 (Generation of X-ray image)

[0172] When image acquisition condition 43b is set, the next X-ray image is generated. That is, after adjusting the position of the C-arm 9 and appropriately adjusting the position of the X-ray irradiation field, instructions for X-ray irradiation are input using the control panel 27, etc., thereby performing a second X-ray irradiation. That is, X-rays are irradiated according to X-ray irradiation condition 45b in image acquisition condition 43b, and image processing unit 19 performs image processing according to image processing condition 47b. As a result, a second X-ray image F6 is generated based on image acquisition condition 43b. X-ray image F6 is displayed on display unit 21.

[0173] When a third X-ray image is generated, the process returns to step P4 and repeats steps P4 through P8. In step P4, the most recently generated X-ray image F6 from the image processing unit 19 is input to the learning model 77, and the image analysis unit 73 analyzes the input X-ray image F6. The analysis results in the output of three part information 41 in descending order of accuracy. In step P5, image acquisition conditions 43 associated with the part information 41 output from the analysis of X-ray image F6 are read out. In step P6, reference images are generated based on the most recently generated X-ray image F6 using the respective image acquisition conditions 43 read out in step P5. In step P7, the three reference images are confirmed, and when a third X-ray image is acquired, an appropriate image acquisition condition 43 is selected and approved.

[0174] In Embodiment 3, a learning model 77 constructed through machine learning is used to analyze recently generated X-ray images, thereby automatically determining the location information 41 for identifying the object region in the X-ray image. In this Embodiment 3, the operator does not need to manually operate a touch panel TP or the like to select the object region. That is, the operation of manually selecting the object region to interrupt the progress of the examination or surgery can be avoided, and the operation of re-selecting the object region or the examination itself due to operator selection errors can also be avoided. Therefore, X-ray fluoroscopy or X-ray imaging can be performed more reliably and quickly under appropriate conditions.

[0175] <Effects obtained from the structure of the implementation method>

[0176] (First item) The X-ray apparatus (1) according to the first embodiment includes: an X-ray tube (5) that irradiates an object (M) with X-rays; an X-ray detector (7) disposed opposite to the X-ray tube for detecting X-rays that have passed through the object; an image processing unit (19) that generates an X-ray image by performing image processing using the detection signal output by the X-ray detector; and a condition storage unit (29) that stores image acquisition conditions (43) corresponding to multiple parts of the object in association with part information (41), wherein the image acquisition conditions (43) include at least one of X-ray irradiation conditions (45) and image processing conditions (47), and the part information (41) is used to determine Information on which part of the subject is being examined; an input unit (27) that can input an instruction for selecting the part of the subject to be irradiated with X-rays from multiple parts of the subject as part information (41); a condition readout unit (35) that reads out the image acquisition condition (43) associated with the part information and stored in the condition storage unit based on the part information (41) selected by the input unit; a reference image generation unit (37) that performs image processing on the recently generated X-ray image based on the image acquisition condition read out by the condition readout unit to generate a reference image (Fs); and a reference image display unit (39) that displays the reference image generated by the reference image generation unit.

[0177] According to the X-ray apparatus 1 described in the first item, the part of the subject to be irradiated with X-rays is selected as part information. Image acquisition conditions associated with the part information are then read out, and a reference image is generated and displayed on the reference image display unit. The reference image is an image obtained by applying the read-out image acquisition conditions to a recently generated X-ray image through image processing. Therefore, by visually recognizing the reference image, the operator can have a general idea of ​​how the generated X-ray image will look when the image acquisition conditions corresponding to the object part selected by the input unit are applied. That is, by visually recognizing the reference image, the degree of various conditions such as brightness and contrast of the X-ray image can be anticipated, thus more reliably avoiding situations where the image acquisition conditions are actually executed with inappropriate parameters and the image acquisition conditions need to be reset. Therefore, appropriate image acquisition conditions can be set more reliably and quickly to perform X-ray fluoroscopy or X-ray radiography.

[0178] (Second item) In addition, the X-ray apparatus described in the first item further includes: a learning model storage unit (75) that stores a learning model (77) which performs machine learning by using an image of a human body as a training image to infer the part of the human body reflected in the image and outputs the part; an image analysis unit (73) that analyzes the input image by inputting at least one of the recently obtained X-ray image (F) and optical image (D) of the subject as an input image into the learning model, infers the part reflected in the input image, and outputs information for determining the inferred part as part information; and a control unit (25) that performs the X-ray... The control of at least one of the control of the X-ray tube (5) and the control of the image processing unit (19) is performed, wherein the control of the X-ray tube (5) is performed to irradiate X-rays according to the X-ray irradiation conditions (45) read by the condition readout unit (35), and the control of the image processing unit (19) is performed to generate the X-ray image according to the image processing conditions (47) read by the condition readout unit (35). The condition readout unit (35) is configured to select the part output by the image parsing unit (73) as the part information (41) and read out the image acquisition conditions (43) associated with the part information (41) and stored in the condition storage unit (29).

[0179] According to the X-ray apparatus described in the second item, image acquisition conditions 43 are automatically set using a learning model 77. The learning model 77 is configured to infer the body parts reflected in the image and output these parts through machine learning by using an image of the human body as a training image. Specifically, the image analysis unit 73 infers the body parts reflected in the input image by inputting an image of the subject M into the learning model 77, and outputs information for determining the inferred body parts as body part information. The condition readout unit 35 automatically reads the image acquisition conditions 43 stored associated with the output body part information 41 of the subject M. Therefore, when an X-ray image F of the subject is acquired, the image analysis unit 73 and the condition readout unit 35 automatically read out the appropriate image acquisition conditions 43 for the position of the irradiation field of the X-ray image F. Thus, even if the part of the subject M to be irradiated by X-rays changes, the appropriate image acquisition conditions 43 for the changed part are automatically read out. That is, the operator does not need to manually select the object and set the image acquisition conditions 43, so X-ray fluoroscopy or X-ray photography can be performed more reliably and quickly under appropriate conditions.

[0180] (Third item) In addition, the X-ray apparatus described in the first or second item also includes a table storage unit (31), which stores a standard body thickness table (T1), a body thickness correction value table (T2), and an average brightness table (T3). The standard body thickness table (T1) is obtained by associating the image acquisition conditions (43) with the standard body thickness determined according to the image acquisition conditions. The body thickness correction value table (T2) is obtained by associating the brightness difference (D) with the body thickness correction value. The brightness difference (D) is a value obtained by subtracting the average brightness value (N1) of the X-ray image (F1) recently generated by the image processing unit (19) from a predetermined standard brightness value (NS). The average brightness table (T3) is obtained by associating the image acquisition conditions with the average brightness determined according to the image acquisition conditions. Multiple average brightness tables (T3) are generated according to the body thickness of the subject. The reference image generation unit (3) 7) Includes: a body thickness estimation unit (51) that estimates the body thickness of the subject using the image acquisition conditions (43c) recently read out by the condition readout unit (35), the X-ray image (F1) recently generated by the image processing unit, the standard body thickness table (T1), and the body thickness correction value table (T2), and calculates the estimated body thickness of the subject as an estimated body thickness value (L); a brightness correction value calculation unit (53) that calculates a brightness correction value (Q) using the average brightness table (T3b) corresponding to the estimated body thickness value (L), the image acquisition conditions (43a) used in the X-ray image (F1) recently generated by the image processing unit, and the image acquisition conditions (43c) recently read out by the condition readout unit; and an image correction unit (55) that generates the reference image (Fs) by adding the brightness correction value (Q) to each pixel of the X-ray image (F1) recently generated by the image processing unit.

[0181] According to the X-ray fluoroscopy apparatus described in the third item, the body thickness estimation unit estimates the body thickness of the subject using a standard body thickness table and a body thickness correction value table. The brightness correction value calculation unit calculates a brightness correction value using the estimated body thickness of the subject and an average brightness table. The image correction unit generates a reference image by adding brightness correction values ​​to each pixel of the X-ray image most recently generated by the image processing unit. In this case, even if the body thickness of the subject deviates from the standard range, the body thickness estimation unit estimates the body thickness of the subject and calculates an appropriate brightness correction value based on the estimated body thickness. Therefore, the brightness value correction of the most recently generated X-ray image performed for generating the reference image is performed appropriately, and thus the reference image more accurately reproduces the image envisioned as the clinical image of the subject. Therefore, even if the body thickness of the subject deviates from the standard range, the operator can more reliably and quickly set appropriate image acquisition conditions to perform X-ray fluoroscopy or X-ray radiography.

[0182] (Fourth item) The X-ray apparatus (1A) according to the second embodiment includes: an X-ray tube (5) that irradiates an object (M) with X-rays; an X-ray detector (7) disposed opposite to the X-ray tube for detecting X-rays that have passed through the object; an image processing unit (19) that generates an X-ray image by performing image processing using the detection signal output by the X-ray detector; and a condition storage unit (29) that stores image acquisition conditions (43) corresponding to a plurality of examination items of the object in association with the examination items (61), wherein the image acquisition conditions (43) include X-ray irradiation conditions (45) and image processing conditions (47). The conditions of at least one party; an input unit (27) capable of inputting an instruction for selecting the type of examination to be performed on the subject as an examination item (61); a condition readout unit (35) which reads out the image acquisition conditions (43) associated with the examination item stored in the condition storage unit based on the examination item selected by the input unit; a reference image generation unit (37) which generates a reference image (Fs) by performing image processing on the recently generated X-ray image (F1) based on the image acquisition conditions (43) read out by the condition readout unit; and a reference image display unit (39) which displays the reference image generated by the reference image generation unit.

[0183] According to the X-ray apparatus described in the fourth item, the type of examination to be performed on the subject is selected as the examination item. The image acquisition conditions associated with the examination item are then read out, and a reference image is generated and displayed on the reference image display unit. The reference image is an image obtained by applying the read-out image acquisition conditions to a recently generated X-ray image through image processing. Therefore, by visually recognizing the reference image, the operator can anticipate how the generated X-ray image will look when the image acquisition conditions corresponding to the object selected using the input unit are applied. That is, by visually recognizing the reference image, the degree of various conditions such as brightness and contrast of the X-ray image can be predicted, thus more reliably avoiding situations where the image acquisition conditions are actually executed with inappropriate parameters and the image acquisition conditions need to be reset. Therefore, appropriate image acquisition conditions can be set more reliably and quickly to perform X-ray fluoroscopy or X-ray radiography.

[0184] (Fifth item) In addition, the X-ray apparatus described in the fourth item further includes: a learning model storage unit (75) that stores a learning model (77) which performs machine learning by using an examination image of a human body as a training image to infer the type of examination in the examination image and output the type of examination; an image analysis unit (73) that analyzes the input image by inputting at least one of the recently obtained X-ray image (F) and optical image (D) of the subject as an input image to the learning model (77), infers the type of examination in the input image, and outputs the type of examination; and a control unit (25) that performs the X-ray... The control of the tube (5) and the control of the image processing unit (19) is at least one of the control of the tube (5), wherein the control of the X-ray tube (5) is for irradiating X-rays according to the X-ray irradiation conditions (45) read by the condition readout unit, and the control of the image processing unit (19) is for generating the X-ray image according to the image processing conditions (47) read by the condition readout unit. The condition readout unit (35) is configured to select the type of inspection output by the image parsing unit (73) as the inspection item (61), and read out the image acquisition conditions (43) associated with the inspection item and stored in the condition storage unit (29).

[0185] According to the X-ray apparatus described in the fifth item, image acquisition conditions 43 are automatically set using a learning model 77. The learning model 77 is configured to infer the type of examination in an image through machine learning by using an image of the human body as a training image, and output this as examination item information 61. Specifically, the image analysis unit 73 infers the type of examination in the input image by inputting an image of the subject M into the learning model 77, and outputs information for determining the inferred type of examination as examination item information 61. The condition readout unit 35 automatically reads the image acquisition conditions 43 stored associated with the output examination item information 61 of the subject M.

[0186] Therefore, when an X-ray image F of the subject is acquired, the image analysis unit 73 and the condition readout unit 35 automatically read out the appropriate image acquisition conditions 43 for the examination items of the X-ray image F. Thus, even if the examination items for the subject M change due to the insertion of an endoscope or catheter, or the administration of contrast agent, the appropriate image acquisition conditions 43 for the changed examination items are automatically read out. That is, the operator does not need to manually select the target area and set the image acquisition conditions 43 every time the examination items are changed, thus enabling more reliable and rapid performance of X-ray fluoroscopy or X-ray radiography under appropriate conditions.

[0187] (Sixth item) In addition, the X-ray apparatus described in the fourth or fifth item also includes a table storage unit (31), which stores a standard body thickness table (T1), a body thickness correction value table (T2), and an average brightness table (T3). The standard body thickness table (T1) is obtained by associating the image acquisition conditions (43) with the standard body thickness determined according to the image acquisition conditions. The body thickness correction value table (T2) is obtained by associating the brightness difference (D) with the body thickness correction value. The brightness difference (D) is a value obtained by subtracting the average brightness value (N1) of the X-ray image (F1) recently generated by the image processing unit (19) from a predetermined standard brightness value (NS). The average brightness table (T3) is obtained by associating the image acquisition conditions with the average brightness determined according to the image acquisition conditions. Multiple average brightness tables (T3) are generated according to the body thickness of the subject. The reference image generation unit (3) 7) Includes: a body thickness estimation unit (51) that estimates the body thickness of the subject using the image acquisition conditions (43c) recently read out by the condition readout unit (35), the X-ray image (F1) recently generated by the image processing unit, the standard body thickness table (T1), and the body thickness correction value table (T2), and calculates the estimated body thickness of the subject as an estimated body thickness value (L); a brightness correction value calculation unit (53) that calculates a brightness correction value (Q) using the average brightness table (T3b) corresponding to the estimated body thickness value (L), the image acquisition conditions (43a) used in the X-ray image (F1) recently generated by the image processing unit, and the image acquisition conditions (43c) recently read out by the condition readout unit; and an image correction unit (55) that generates the reference image (Fs) by adding the brightness correction value (Q) to each pixel of the X-ray image (F1) recently generated by the image processing unit.

[0188] According to the X-ray fluoroscopy apparatus described in item six, the body thickness estimation unit estimates the body thickness of the subject using a standard body thickness table and a body thickness correction value table. The brightness correction value calculation unit calculates a brightness correction value using the estimated body thickness of the subject and an average brightness table. The image correction unit generates a reference image by adding brightness correction values ​​to each pixel of the X-ray image most recently generated by the image processing unit. In this case, even if the body thickness of the subject deviates from the standard range, the body thickness estimation unit estimates the body thickness of the subject and calculates an appropriate brightness correction value based on the estimated body thickness. Therefore, the brightness value correction of the most recently generated X-ray image performed for generating the reference image is performed appropriately, and thus the reference image more accurately reproduces the image conceived as the clinical image of the subject. Therefore, even if the body thickness of the subject deviates from the standard range, the operator can more reliably and quickly set appropriate image acquisition conditions to perform X-ray fluoroscopy or X-ray radiography.

[0189] <Other Implementation Methods>

[0190] Furthermore, the embodiments disclosed herein are illustrative in all respects and not restrictive. The scope of the invention includes the claims and all modifications within the meaning and scope of their equivalents. As an example, the invention can be modified and implemented as follows.

[0191] (1) In the above embodiments, the description was given as an example of an X-ray image (clinical image) reflecting the subject M as the object of X-ray irradiation. However, the reference image Fs can also be set to reflect an X-ray image (phantom image). That is, when the reference image Fs is a clinical image as in each embodiment, there is no recently generated clinical image when the first X-ray image is generated. Therefore, in each embodiment where the reference image Fs is a clinical image, the reference image Fs is not displayed when the image acquisition condition 43 is read out in step S2.

[0192] On the other hand, in a variation where the phantom image is used as a reference image Fs, a phantom image with an average body thickness is irradiated with X-rays under various image acquisition conditions 43 to obtain phantom images corresponding to each image acquisition condition 43, which are then used as reference images Fs. The obtained series of phantom images are stored in the storage unit 23. Then, if image acquisition condition 43b is selected as an example in step S1 to acquire an X-ray image of the subject M, when image acquisition condition 43b is read out in step S2, between steps S2 and S3, the reference image generation unit 37 reads out the phantom image generated based on image acquisition condition 43b from the storage unit 23. The read-out phantom image is then displayed as reference image Fs on the reference image display unit 39.

[0193] The operator checks the brightness and other parameters of the phantom image displayed as the reference image Fs to determine whether image acquisition condition 43b is appropriate for acquiring the first X-ray image. If it is deemed appropriate, image acquisition condition 43b is approved. After approval, the operator performs operations to begin X-ray irradiation to actually generate the first X-ray image.

[0194] In this variation, the reference image Fs can be confirmed during the preparation for acquiring the first X-ray image, thus eliminating the need to determine the suitability of image acquisition condition 43 solely using numerical parameters during the preparation stage. Therefore, the suitability of image acquisition condition 43 can be determined with higher accuracy even during the generation of the first X-ray image.

[0195] Furthermore, in a variation where the phantom image is used as a reference image, the reference image Fs can be switched from the phantom image to a clinical image of the subject M when acquiring the second or subsequent X-ray images. That is, the phantom image is used as a reference image only during the generation of the first X-ray image. Then, during the generation of the second X-ray image, a clinical image applying the most recently readout image acquisition condition 43 is generated based on the first X-ray image reflecting the subject M, as in Example 1, and displayed as the reference image Fs.

[0196] The clinical image is an X-ray image reflecting the subject M itself. Therefore, as an example, even if the thickness of the subject M deviates from the standard range, the appropriate image acquisition condition 43 can be selected with higher precision. Therefore, when the X-ray device 1 is structured to switch between the phantom image and the clinical image as a reference image, even when the first X-ray image is acquired without a clinical image of the subject M, the phantom image can be displayed as a reference image, and the clinical image can be displayed as a reference image when acquiring the second and subsequent X-ray images. Thus, the accuracy of the information obtained from the reference image can be further improved.

[0197] Furthermore, in a variation where the phantom image is used as a reference image, the phantom image can also be used as a reference image Fs when acquiring a second or subsequent X-ray image. When the X-ray apparatus 1 is configured to display only the phantom image as a reference image, it is not necessary to calculate the estimated thickness value L or the brightness correction value Q during the step of generating the reference image Fs. Therefore, the reference image generation unit 37 does not need to include a thickness estimation unit 51 or a brightness correction value calculation unit 53. In other words, complex calculations are not required when generating a reference image, thus reducing the burden on the processor, such as the main control unit 25.

[0198] (2) In the above embodiments, the image acquisition condition 43 is not limited to a structure that includes both the X-ray irradiation condition 45 and the image processing condition 47, but may be a structure that includes either one. Furthermore, the X-ray irradiation condition 45 may be a structure that independently includes both X-ray fluoroscopy conditions (as a set of parameters used in intermittent irradiation with a relatively weak dose of X-rays) and X-ray radiography conditions (as a set of parameters used in a single irradiation with a relatively strong dose of X-rays), or it may be a structure that includes either one.

[0199] (3) In the above embodiments, an X-ray fluoroscopic imaging device with a C-arm 9 is used as an example of X-ray device 1, but it is not limited thereto. The structure of the present invention can be applied to any radiographic imaging device, such as an X-ray imaging device for ordinary X-ray imaging or a tomographic imaging device.

[0200] (4) In Embodiment 3 above, the X-ray image F used as input information to the learning model 77 can be either an X-ray fluoroscopy image or an X-ray radiograph. Alternatively, the X-ray fluoroscopy image can be input to the learning model 77, and X-ray radiography can be performed using the image acquisition conditions 43 output from the APR 33. Alternatively, the X-ray radiograph image can be input to the learning model 77, and X-ray fluoroscopy can be performed using the image acquisition conditions 43 output from the APR 33.

[0201] (5) In the above embodiment 3, the structure in which the operator manually selects the target area during the stage of acquiring the first X-ray image (the stage before X-ray irradiation) was described as an example, but it is not limited to this. That is, the X-ray device 1B may also include an optical camera (not shown) arranged at the same irradiation angle as the X-ray tube 5. During the stage before X-ray irradiation, the optical camera acquires an optical image D of the subject M and uses this optical image D as the input image. In the structure with the optical camera, during the stage of acquiring the first X-ray image, the optical image D is used as the input image instead of the X-ray image F for inference based on the learning model 77. Therefore, even during the stage of acquiring the first X-ray image, the operation of the operator manually selecting the target area can be omitted.

[0202] Explanation of reference numerals in the attached figures

[0203] 1: X-ray fluoroscopy apparatus; 3: Top plate; 5: X-ray tube; 7: X-ray detector; 9: C-arm; 17: Collimator; 19: Image processing unit; 21: Display unit; 23: Storage unit; 25: Main control unit; 27: Operating table; 29: Condition storage unit; 31: Table storage unit; 33: Anatomy procedure (APR); 35: Condition readout unit; 37: Reference image generation unit; 39: Reference image display unit; 41: Site information; 43: Image acquisition conditions; 45: X-ray irradiation conditions; 47: Image processing conditions; 51: Body thickness estimation unit; 53: Brightness correction value calculation unit; 55: Image correction unit; T1: Standard body thickness table; T2: Body thickness correction value table; T3: Average brightness table; Ac: Icon group; TP: Touch panel; L: Estimated body thickness value; Q: Brightness correction value.

Claims

1. An X-ray device comprising: An X-ray tube irradiates the subject with X-rays. An X-ray detector, which is arranged facing the X-ray tube, is used to detect X-rays that have passed through the subject. The image processing unit generates an X-ray image by performing image processing using the detection signal output by the X-ray detector; The storage unit stores image acquisition conditions corresponding to multiple parts of the subject in association with part information, and stores the X-ray image generated based on the image acquisition conditions associated with the first part information, the image acquisition conditions including at least one of X-ray irradiation conditions and image processing conditions, the part information being information used to determine which part of the parts; The input unit is capable of inputting an instruction for selecting, from multiple parts of the subject, the part to be irradiated with X-rays as part information; The condition readout unit reads out the image acquisition conditions stored in the storage unit in association with the location information based on the location information selected by the input unit; The reference image generation unit generates a reference image by performing image processing on the X-ray image generated based on the image acquisition conditions associated with the image acquisition conditions associated with the first location information stored in the storage unit, based on the image acquisition conditions read by the condition readout unit and associated with the second location information which is different from the first location information. as well as The reference image display unit displays the reference image generated by the reference image generation unit.

2. The X-ray apparatus according to claim 1, characterized in that, It also has: The learning model storage unit stores learning models that perform machine learning by using images of the human body as training images to infer and output the parts of the human body reflected in the images. The image analysis unit analyzes the input image by inputting at least one of the recently obtained X-ray image and optical image of the subject into the learning model, infers the region reflected in the input image, and outputs the region. as well as The control unit controls at least one of the X-ray tube and the image processing unit, wherein the control of the X-ray tube is for irradiating X-rays according to the X-ray irradiation conditions read by the condition readout unit, and the control of the image processing unit is for generating the X-ray image according to the image processing conditions read by the condition readout unit. The condition readout unit is configured to: select the region output by the image parsing unit as the region information, and read out the image acquisition conditions associated with the region information and store them in the storage unit.

3. The X-ray apparatus according to claim 1 or 2, characterized in that, It also includes a table storage unit that stores a standard body thickness table, a body thickness correction value table, and an average brightness table. The standard body thickness table is obtained by associating the image acquisition conditions with a standard body thickness determined based on the image acquisition conditions. The body thickness correction value table is obtained by associating brightness differences with body thickness correction values. The brightness difference is a value obtained by subtracting the average brightness value of the most recently generated X-ray image from a predetermined standard brightness value. The average brightness table is obtained by associating the image acquisition conditions with an average brightness determined based on the image acquisition conditions. Multiple average brightness tables are created based on the body thickness of the subject. The reference image generation unit includes: The body thickness estimation unit uses the image acquisition conditions recently read out by the condition readout unit, the X-ray image recently generated by the image processing unit, the standard body thickness table, and the body thickness correction value table to estimate the body thickness of the subject, and calculates the estimated body thickness of the subject as an estimated body thickness value. A brightness correction value calculation unit calculates a brightness correction value using the average brightness table corresponding to the estimated volume thickness value, the image acquisition conditions used in the X-ray image recently generated by the image processing unit, and the image acquisition conditions recently read out by the condition readout unit; and The image correction unit generates the reference image by adding the brightness correction value to each pixel of the X-ray image recently generated by the image processing unit.

4. An X-ray device comprising: An X-ray tube irradiates the subject with X-rays. An X-ray detector, which is arranged facing the X-ray tube, is used to detect X-rays that have passed through the subject. The image processing unit generates an X-ray image by performing image processing using the detection signal output by the X-ray detector; The storage unit stores image acquisition conditions corresponding to multiple examination items of the subject in association with the examination items, and stores the X-ray image generated based on the image acquisition conditions associated with the first examination item, the image acquisition conditions including at least one of X-ray irradiation conditions and image processing conditions. The input unit is capable of inputting instructions for selecting the type of examination to be performed on the subject as the examination item. The condition readout unit reads out the image acquisition conditions associated with the inspection item stored in the storage unit based on the inspection item selected through the input unit; The reference image generation unit generates a reference image by performing image processing on the X-ray image generated based on the image acquisition conditions associated with the first inspection item stored in the storage unit, which are read by the condition readout unit and are different from the first inspection item. as well as The reference image display unit displays the reference image generated by the reference image generation unit.

5. The X-ray apparatus according to claim 4, characterized in that, It also has: The learning model storage unit stores learning models that perform machine learning by using examination images of the human body as training images to infer the type of examination in the examination images and output the type of examination. The image analysis unit analyzes the input image by inputting at least one of the recently obtained X-ray image and optical image of the subject into the learning model, infers the type of examination in the input image, and outputs the type of examination. as well as The control unit controls at least one of the X-ray tube and the image processing unit, wherein the control of the X-ray tube is for irradiating X-rays according to the X-ray irradiation conditions read by the condition readout unit, and the control of the image processing unit is for generating the X-ray image according to the image processing conditions read by the condition readout unit. The condition readout unit is configured to: select the type of inspection output by the image parsing unit as the inspection item, and read out the image acquisition conditions associated with the inspection item and stored in the storage unit.

6. The X-ray apparatus according to claim 4 or 5, characterized in that, It also includes a table storage unit that stores a standard body thickness table, a body thickness correction value table, and an average brightness table. The standard body thickness table is obtained by associating the image acquisition conditions with a standard body thickness determined based on the image acquisition conditions. The body thickness correction value table is obtained by associating brightness differences with body thickness correction values. The brightness difference is a value obtained by subtracting the average brightness value of the most recently generated X-ray image from a predetermined standard brightness value. The average brightness table is obtained by associating the image acquisition conditions with an average brightness determined based on the image acquisition conditions. Multiple average brightness tables are created based on the body thickness of the subject. The reference image generation unit includes: The body thickness estimation unit uses the image acquisition conditions recently read out by the condition readout unit, the X-ray image recently generated by the image processing unit, the standard body thickness table, and the body thickness correction value table to estimate the body thickness of the subject, and calculates the estimated body thickness of the subject as an estimated body thickness value. A brightness correction value calculation unit calculates a brightness correction value using the average brightness table corresponding to the estimated volume thickness value, the image acquisition conditions used in the X-ray image recently generated by the image processing unit, and the image acquisition conditions recently read out by the condition readout unit; and The image correction unit generates the reference image by adding the brightness correction value to each pixel of the X-ray image recently generated by the image processing unit.

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