Image processing apparatus

Abstract

Embodiments relate to an image processing apparatus. A technical problem to be solved by the present invention is to reduce a confirmation burden of a user. An image processing apparatus of an embodiment includes an acquisition unit, a first detection unit, and an output unit. The acquisition unit acquires an image obtained by capturing a subject placed on a top plate of a magnetic resonance imaging apparatus with a camera. The first detection unit detects a loop in which an induced current is likely to occur due to a magnetic field generated by the magnetic resonance imaging apparatus, from the image. The output unit outputs a detection result of the first detection unit.

Description

[0001] Reference to relevant applications

[0002] This application enjoys priority to Japanese Patent Application No. 2021-022379, filed on February 16, 2021, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The implementation method relates to an image processing apparatus. Background Technology

[0004] One of the technical problems to be solved by the embodiments disclosed in this specification and accompanying drawings is to reduce the user's confirmation burden. However, the technical problems to be solved by the embodiments disclosed in this specification and accompanying drawings are not limited to the above-mentioned technical problems. It is also possible to locate the technical problems corresponding to the effects of each structural agent shown in the embodiments described below as other technical problems. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to reduce the user's confirmation burden.

[0006] The image processing apparatus of this embodiment includes an acquisition unit, a first detection unit, and an output unit. The acquisition unit acquires an image obtained by photographing a subject placed on the top plate of a magnetic resonance imaging (MRI) apparatus using a camera. The first detection unit detects loops in the image that may generate induced currents due to the magnetic field generated by the MRI apparatus. The output unit outputs the detection results from the first detection unit. Attached Figure Description

[0007] Figure 1 This is a diagram illustrating an example of the structure of the verification assistance system according to the first embodiment.

[0008] Figure 2 This is a block diagram illustrating an example of the structure of the magnetic resonance imaging apparatus according to the first embodiment.

[0009] Figure 3 This is a diagram showing an example of viewing a subject from above.

[0010] Figure 4 This is a diagram showing an example of an electric field region viewed from above.

[0011] Figure 5 This indicates viewing from the Z-axis direction. Figure 4 A diagram showing an example of an electric field region.

[0012] Figure 6 This is a flowchart illustrating an example of the confirmation assistance processing performed by the magnetic resonance imaging apparatus of the first embodiment. Detailed Implementation

[0013] Hereinafter, the image processing apparatus of the present embodiment will be described with reference to the drawings. In the following embodiments, the same action is assumed for portions to which the same reference signs are assigned, and redundant description will be appropriately omitted.

[0014] (First Embodiment)

[0015] Figure 1 is a diagram showing an example of the structure of the confirmation assistance system 1 of the first embodiment. The confirmation assistance system 1 has a magnetic resonance imaging (MRI) apparatus 10 and a camera 20. Also, the MRI apparatus 10 and the camera 20 are connected through a network such as a hospital LAN (Local Area Network). In addition, Figure 1 The confirmation assistance system 1 shown in the drawing has the MRI apparatus 10 and the camera 20. However, the confirmation assistance system 1 can have a plurality of cameras 20.

[0016] Figure 1 The X-axis, the Y-axis, and the Z-axis shown in the drawing constitute an apparatus coordinate system unique to the MRI apparatus 10. For example, the Z-axis direction coincides with the axial direction of the cylinder of the gradient magnetic field coil 103 (refer to Figure 2 ), and is set along the magnetic flux of the static magnetic field generated by the static magnetic field magnet 101 (refer to Figure 2 ). In addition, the Z-axis direction is in the same direction as the length direction of the examination bed 105, and is also in the same direction as the cranial-caudal direction of the subject P placed on the examination bed 105. In addition, the X-axis direction is set along the horizontal direction orthogonal to the Z-axis direction. The Y-axis direction is set along the vertical direction orthogonal to the Z-axis direction.

[0017] The MRI apparatus 10 has the examination bed 105 on which the subject P is placed, and a stand device 11 having a substantially cylindrical shape with a hollow into which the subject P is inserted. The MRI apparatus 10 generates a high-frequency magnetic field in a case where the subject P is inserted into the hollow and the subject P is imaged. An RF (Radio Frequency) coil 12 mounted to the subject P receives an MR signal generated from the subject P. The MRI apparatus 10 receives via a cable 13 of the RF coil 12. Also, the MRI apparatus 10 generates an MR image of the subject P placed on the top plate 105a of the examination bed 105 on the basis of the received MR signal.

[0018] In addition, the cable 13 of the RF coil 12 can be colored or can be attached with a geometric pattern or the like. In a case where the cable 13 is detected from an image captured by the camera 20, the magnetic resonance imaging apparatus 10 can easily detect by being colored or being attached with the pattern. In a case where the configuration of the Y-axis direction of the cable 13 is determined from the image captured by the camera 20, the magnetic resonance imaging apparatus 10 can determine the configuration of the Y-axis direction by measuring the interval of lines of the pattern of the cable 13.

[0019] The camera 20 is an imaging device that captures a moving image or a still image. The camera 20 includes the subject P placed on the top plate 105a in an imaging region. Also, the camera 20 transmits an image captured to the magnetic resonance imaging apparatus 10. In addition, Figure 1 The illustrated camera 20 is disposed above the top plate 105a of the examination bed 105. However, the camera 20 can also be disposed at other positions.

[0020] Here, even if the cable 13 forms a loop in a two-dimensional image, the cable 13 does not always form a loop in a three-dimensional image. Therefore, the camera 20 is not limited to above the top plate 105a, but can also be disposed to the side of the top plate 105a, and can also be disposed at other positions. Also, the camera 20 can also be an imaging device that captures a three-dimensional image in which a ToF (Time of Flight) sensor, a LiDAR (Laser Imaging Detection and Ranging), or the like, which is an imaging region, is expressed in three dimensions. In addition, the camera 20 can also be an imaging device that can detect infrared rays. By this, the camera 20 can capture an image in which the subject P placed on the top plate 105a and the subject P other than the subject P are easily recognized.

[0021] In such a confirmation assistance system 1, the magnetic resonance imaging apparatus 10 acquires an image captured by the camera 20. In addition, the magnetic resonance imaging apparatus 10 determines whether there is a portion where the cable 13 or the like forms a loop, based on the image captured by the camera 20. Also, the magnetic resonance imaging apparatus 10 notifies in a case where a loop of the cable 13 or the like is detected. The magnetic resonance imaging apparatus 10 is an example of an image processing device.

[0022] Next, the magnetic resonance imaging apparatus 10 will be described.

[0023] Figure 2is a block diagram showing an example of the structure of the magnetic resonance imaging apparatus 10 of the first embodiment. The magnetic resonance imaging apparatus 10 includes a static magnetic field magnet 101, a static magnetic field power supply (not shown), a gradient magnetic field coil 103, a gradient magnetic field power supply 104, a couch 105, a couch control circuit 106, a transmission coil 107, a transmission circuit 108, a reception coil 109, a reception circuit 110, a sequence control circuit 120, and a computer system 130.

[0024] In addition, Figure 2 The illustrated structure is merely an example. For example, the sequence control circuit 120 and the computer system 130 can be appropriately combined or separated to constitute. In addition, the magnetic resonance imaging apparatus 10 does not include an object P (for example, a human body).

[0025] The static magnetic field magnet 101 is a magnet formed in a hollow substantially cylindrical shape, and generates a static magnetic field in the inside space. The static magnetic field magnet 101 is, for example, a superconducting magnet or the like, and is excited by receiving supply of electric current from a static magnetic field power supply. The static magnetic field power supply supplies electric current to the static magnetic field magnet 101. As another example, the static magnetic field magnet 101 can be a permanent magnet, in which case the magnetic resonance imaging apparatus 10 can not include the static magnetic field power supply. In addition, the static magnetic field power supply can be provided separately from the magnetic resonance imaging apparatus 10.

[0026] The gradient magnetic field coil 103 is a coil formed in a hollow substantially cylindrical shape, and is disposed inside the static magnetic field magnet 101. The gradient magnetic field coil 103 is formed by combining three coils corresponding to respective axes of X, Y, and Z that are orthogonal to each other, and generates a gradient magnetic field in which the magnetic field strength varies along the respective axes of X, Y, and Z, by receiving supply of electric current from the gradient magnetic field power supply 104. In addition, the gradient magnetic field power supply 104 supplies electric current to the gradient magnetic field coil 103 under the control of the sequence control circuit 120.

[0027] The couch 105 includes a top plate 105a on which the object P is placed, and under the control of the couch control circuit 106, the top plate 105a is inserted into the imaging port in a state in which the object P such as a patient is placed. The couch control circuit 106 drives the couch 105 to move the top plate 105a in the length direction and the vertical direction under the control of the computer system 130.

[0028] The transmission coil 107 excites an arbitrary region of the object P by applying a high-frequency magnetic field. The transmission coil 107 is, for example, a whole body type coil that surrounds the entire body of the object P. The transmission coil 107 receives supply of an RF pulse from the transmission circuit 108, and generates a high-frequency magnetic field, and applies the high-frequency magnetic field to the object P. The transmission circuit 108 supplies the RF pulse to the transmission coil 107 under the control of the sequence control circuit 120.

[0029] The reception coil 109 is disposed inside the gradient magnetic field coil 103, and receives a magnetic resonance signal (hereinafter, referred to as an MR (Magnetic Resonance) signal) emitted from the subject P due to the influence of the high-frequency magnetic field. The reception coil 109 outputs the received MR signal to the reception circuit 110 when the MR signal is received.

[0030] Further, in Figure 2 , a structure in which the reception coil 109 is separately provided from the transmission coil 107 is employed, but this is an example, and is not limited to this structure. For example, a structure in which the reception coil 109 is used as the transmission coil 107 can also be employed.

[0031] The reception circuit 110 performs analog / digital (AD) conversion on the analog MR signal output from the reception coil 109, and generates MR data. In addition, the reception circuit 110 transmits the generated MR data to the sequence control circuit 120. In addition, as for the AD conversion, it can also be performed inside the reception coil 109. In addition, the reception circuit 110 can perform arbitrary signal processing in addition to the AD conversion.

[0032] The sequence control circuit 120 drives the gradient magnetic field power supply 104, the transmission circuit 108, and the reception circuit 110 on the basis of the sequence information transmitted from the computer system 130, and thereby performs imaging of the subject P. The sequence information is information that defines steps for performing imaging. The sequence information includes, for example, the intensity of the current supplied to the gradient magnetic field coil 103 by the gradient magnetic field power supply 104, the timing of the supplied current, the intensity of the RF pulse supplied to the transmission coil 107 by the transmission circuit 108, the timing of the applied RF pulse, the timing at which the MR signal is detected by the reception circuit 110, and the like. The sequence control circuit 120 can be realized by a processor, or can be realized by a mixture of software and hardware.

[0033] When the MR data is received from the reception circuit 110 as a result of imaging of the subject P performed by driving the gradient magnetic field power supply 104, the transmission circuit 108, and the reception circuit 110, the sequence control circuit 120 relays the received MR data to the computer system 130.

[0034] The computer system 130 performs overall control of the magnetic resonance imaging apparatus 10, generation of an MR image, and the like. As shown in Figure 2 , the computer system 130 is provided with an NW (network) interface 131, a storage circuit 132, an input interface 133, a display 134, and a processing circuit 135.

[0035] The NW interface 131 communicates with the sequence control circuit 120 and the couch control circuit 106. For example, the NW interface 131 transmits sequence information to the sequence control circuit 120. In addition, the NW interface 131 receives MR data from the sequence control circuit 120.

[0036] The storage circuit 132 stores MR data received by the NW interface 131, k-space data configured in a k-space by the processing circuit 135 described later, image data generated by the processing circuit 135, and the like. The storage circuit 132 is, for example, a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, or an optical disk.

[0037] The input interface 133 accepts various instructions from an operator, information input. The input interface 133 is realized by, for example, a trackball, a switch button, a mouse, a keyboard, a touch panel that performs input operation by contacting an operation surface, a touch screen in which a display screen and a touch panel are integrated, a non-contact input circuit using an optical sensor, a sound input circuit, and the like. The input interface 133 is connected to the processing circuit 135, converts an input operation accepted from the operator into an electric signal, and outputs the electric signal to the processing circuit 135. In addition, in the present specification, the input interface 133 is not limited to an interface having a physical operation member such as a mouse or a keyboard. For example, an electric signal processing circuit that receives an electric signal corresponding to an input operation from an input device provided externally from the computer system 130 and outputs the electric signal to the control circuit is also included in the example of the input interface 133.

[0038] The display 134 displays a GUI (Graphical User Interface) for accepting input of a photographing condition, a magnetic resonance image generated by the processing circuit 135, and the like under the control of the processing circuit 135. The display 134 is, for example, a display device such as a liquid crystal display.

[0039] The processing circuit 135 controls the overall operation of the magnetic resonance imaging device 10. The processing circuit 135 includes, for example, an image acquisition function 135a, a start condition detection function 135b, an object recognition function 135c, a loop detection function 135d, a cable loop detection function 135e, a subject loop detection function 135f, a contact detection function 135g, a configuration detection function 135h, an electric field region detection function 135i, an entrainment detection function 135j, and an output function 135k. In this embodiment, each processing function performed by the image acquisition function 135a, the start condition detection function 135b, the object recognition function 135c, the loop detection function 135d, the cable loop detection function 135e, the subject loop detection function 135f, the contact detection function 135g, the configuration detection function 135h, the electric field region detection function 135i, the entrainment detection function 135j, and the output function 135k is stored in the storage circuit 132 as a computer-executable program. The processing circuit 135 is a processor that implements the functions corresponding to each program by reading and executing programs from the storage circuit 132. In other words, the processing circuit 135, having read the state of each program, has... Figure 2 The functions shown in the processing circuit 135.

[0040] In addition, Figure 2 In this paper, the image acquisition function 135a, start condition detection function 135b, object recognition function 135c, loop detection function 135d, cable loop detection function 135e, subject loop detection function 135f, contact detection function 135g, configuration detection function 135h, electric field area detection function 135i, entanglement detection function 135j, and output function 135k are described using a single processor. However, multiple independent processors can also be combined to form the processing circuit 135, with each processor executing the program to implement the functions. Furthermore, in Figure 2 In this paper, a single storage circuit, such as storage circuit 132, is used to store the program corresponding to each processing function. However, it can also be configured such that multiple storage circuits are distributed and the processing circuit 135 reads the corresponding program from the independent storage circuit.

[0041] The term "processor" used in the above description refers to, for example, a CPU (Central Processing Unit), a GPU (Graphical Processing Unit), or an ASIC (Application Specific Integrated Circuit), a programmable logic device (for example, a SPLD (Simple Programmable Logic Device), a CPLD (Complex Programmable Logic Device), and an FPGA (Field Programmable Gate Array)), and the like. The processor realizes a function by reading out and executing a program stored in the storage circuit 132. Alternatively, the processor can be configured to have a program directly incorporated in the circuit of the processor instead of storing the program in the storage circuit 132. In this case, the processor realizes a function by reading out and executing the program incorporated in the circuit.

[0042] The image acquisition function 135a acquires an image obtained by imaging the subject P placed on the top plate 105a of the magnetic resonance imaging apparatus 10 with the camera 20. The image acquisition function 135a is an example of an acquisition section. In more detail, the image acquisition function 135a acquires an image, an infrared image, a three-dimensional image, or the like imaged by one or a plurality of cameras 20.

[0043] The start condition detection function 135b detects a start condition for starting detection of a detection target based on the loop detection function 135d, the contact detection function 135g, and the arrangement detection function 135h. The start condition detection function 135b is an example of a second detection section. In more detail, the start condition detection function 135b detects a start condition for starting processing of detecting a loop of the cable 13 based on the loop detection function 135d. In addition, the start condition detection function 135b detects a start condition for starting processing of detecting a contact position of the subject P and the cable 13 based on the contact detection function 135g. In addition, the start condition detection function 135b detects a start condition for starting processing of detecting a detection target from a prescribed region based on the arrangement detection function 135h. The start condition detection function 135b detects, for example, a case where the cable 13 is connected to the magnetic resonance imaging apparatus 10, a case where the top plate 105a is lifted up for insertion into a substantially cylindrical hollow, that is, an imaging port, of the gantry apparatus 11 as the start condition.

[0044] The object recognition function 135c recognizes an object included in an image captured by the camera 20. The object recognition function 135c is an example of a recognition section. For example, the object recognition function 135c recognizes that it is an object such as the subject P, the cable 13, a wiring that has no risk of scalding, a tube for a drip, a tube for gas supply, and the like. In more detail, the object recognition function 135c recognizes each object on the basis of object feature information that indicates features of each object.

[0045] Characteristics such as a temperature, a thickness, a color, a pattern, a shape, and the like of each object are set in the object feature information. The object recognition function 135c compares the object feature information with an image of an object included in an image, and thereby can recognize the object. For example, in a case where the cable 13 is colored or patterned, the object recognition function 135c recognizes the cable 13 of the RF coil 12 that receives a signal generated from the subject P on the basis of the color or the pattern included in the image. In addition, the object recognition function 135c is not limited to one image, and can recognize an object by a plurality of images captured from different directions.

[0046] In addition, the object recognition function 135c can recognize an object on the basis of an infrared image captured by the camera 20 that detects infrared rays. In addition, the object recognition function 135c can recognize an object by a three-dimensional image captured by the camera 20 that generates a three-dimensional image.

[0047] Further, in the present embodiment, after the object recognition function 135c recognizes an object, the loop detection function 135d, the contact detection function 135g, and the arrangement detection function 135h respectively perform detection of a detection target. However, the object recognition function 135c can recognize an object of a detection target after each of the loop detection function 135d, the contact detection function 135g, or the arrangement detection function 135h detects the detection target.

[0048] The loop detection function 135d detects a loop that is likely to generate an induced current due to a magnetic field generated by the magnetic resonance imaging apparatus 10 from an image. The loop detection function 135d is an example of a first detection section. That is, the loop detection function 135d detects a loop formed by the cable 13 of the RF coil 12 used in the magnetic resonance imaging apparatus 10 or a loop formed by the subject P. In addition, the loop detection function 135d includes a cable loop detection function 135e and a subject loop detection function 135f.

[0049] The cable loop detection function 135e detects a cable loop 13a formed by the cable 13. Here, Figure 3is a diagram indicating an example of observing the subject P from above. The cable loop detection function 135e detects the cable loop 13a formed by the cable 13. In other words, the cable loop detection function 135e detects the cable loop 13a in which an induced current is likely to be generated due to the high-frequency magnetic field generated by the magnetic resonance imaging apparatus 10. For example, the cable loop detection function 135e detects the cable loop 13a by pattern matching the shape of the wheel from the image captured by the camera 20.

[0050] In addition, the cable loop detection function 135e can also detect the cable loop 13a from the infrared image captured by the camera 20 that detects infrared rays in accordance with y. Here, since there is a temperature difference, the cable loop detection function 135e can easily distinguish the subject P and the cable 13. In other words, the cable loop detection function 135e detects the cable loop 13a from the infrared image, thereby being able to reduce false detection.

[0051] Here, even if the shape of a wheel is formed by the cable 13 in a two-dimensional image, it is not a loop in a case where the cable 13 does not contact in the Y-axis direction. Therefore, the cable loop detection function 135e detects the cable loop 13a based on the configuration of the object such as the cable 13 in the three-dimensional space included in the image. The cable loop detection function 135e determines the configuration of the cable 13 in the Y-axis direction based on the interval of the lines that form the pattern in a case where the cable 13 has a pattern. That is, the cable loop detection function 135e determines the configuration of the cable 13 in the three-dimensional space. Also, in a case where the cable 13 that forms a wheel in the Y-axis direction overlaps, the cable loop detection function 135e detects as the cable loop 13a. In addition, the cable loop detection function 135e can determine the configuration of the cable 13 in the three-dimensional space based on a three-dimensional image in a case where the three-dimensional image is acquired.

[0052] In a case where it is recognized as a specific object by the object recognition function 135c, the cable loop detection function 135e does not detect as the cable loop 13a. For example, in a case where it is recognized as the subject P, the tube by the object recognition function 135c, even if a loop is formed by the subject P, the tube, the cable loop detection function 135e does not perform detection. In addition, the cable loop detection function 135e does not detect as the cable loop 13a in a case where it is recognized as the tube, the wiring in which there is no risk of heat generation by the object recognition function 135c.

[0053] In addition, in a case where it is recognized as the same object by the object recognition function 135c, the cable loop detection function 135e detects as the cable loop 13a. That is, in a case where a loop is formed by a plurality of objects, the cable loop detection function 135e does not detect as the cable loop 13a. For example, the cable loop detection function 135e does not detect as the cable loop 13a even if a loop is formed by combining the cable 13 with the subject P.

[0054] Further, the cable loop detection function 135e is not limited to pattern matching, and can detect the cable loop 13a by another method. The cable loop detection function 135e can also detect the cable loop 13a based on a learned model that detects the cable loop 13a contained in an image when the image is input. For example, the learned model is generated by supervised learning in which an image and the cable loop 13a contained in the image are input as training data.

[0055] The subject loop detection function 135f detects a loop formed by the subject P, that is, a subject loop. The subject loop is a loop formed by bare muscles of the subject P contacting each other. That is, the subject loop detection function 135f does not detect as a subject loop in a case of contacting a towel, a hospital gown. For example, the subject loop detection function 135f detects a loop by pattern matching the shape of a wheel from an image captured by the camera 20.

[0056] Further, the subject loop detection function 135f can also detect a loop from an infrared image. Here, the subject loop detection function 135f can easily distinguish the subject P and the cable 13 because of a temperature difference. In other words, the subject loop detection function 135f detects the subject P from an infrared image, and thus can reduce false detection. Further, even in a case where a shape of a wheel is formed by the subject P in a two-dimensional image, in a case where the subject P does not contact in the Y-axis direction, it is not a loop. The subject loop detection function 135f detects as a subject loop in a case where the subject P contacting in the Y-axis direction forms a wheel. Therefore, the subject loop detection function 135f detects a subject loop based on a configuration of a three-dimensional space of an object such as the subject P contained in an image. The subject loop detection function 135f can also determine a configuration of a three-dimensional space of the subject P based on a three-dimensional image in a case where the three-dimensional image is acquired.

[0057] Further, the subject loop detection function 135f is not limited to pattern matching, and can detect the cable loop 13a by another method. The subject loop detection function 135f can also detect the subject loop based on a learned model that detects the subject loop contained in an image when the image is input. For example, the learned model is generated by supervised learning in which an image and the subject loop contained in the image are input as training data.

[0058] The contact detection function 135g detects contact of the cable 13 of the RF coil 12 that receives a signal generated from the subject P with the subject P from the image. The contact detection function 135g is an example of the third detection section. In more detail, the contact detection function 135g detects a portion that the object recognition function 135c recognizes as the subject P is in contact with a portion that the object recognition function 135c recognizes as the cable 13. That is, the contact detection function 135g does not detect a contact portion in a case where the cable 13, the subject P, and a towel, a hospital gown are in contact.

[0059] In addition, the contact detection function 135g can also detect a loop from the infrared image. Here, since there is a temperature difference, the contact detection function 135g can easily distinguish the subject P and the cable 13. In other words, the contact detection function 135g detects a contact portion from the infrared image, and thus can reduce false detection.

[0060] Here, even in a case where the image in contact in the two-dimensional image, the subject P is not in contact with the cable 13 in the Y-axis direction. In addition, the contact detection function 135g can also detect a contact portion of the subject P and the cable 13 based on the three-dimensional image in a case where the three-dimensional image is acquired.

[0061] In addition, the contact detection function 135g can also detect a contact portion of the subject P and the cable 13 based on a learned model that detects a contact portion included in an image in a case where the image is input. For example, the learned model is generated by supervised learning in which an image and a contact portion of the subject P and the cable 13 are input as training data.

[0062] The arrangement detection function 135h detects a detection object from an image acquired by the image acquisition function 135a, from an electric field region E (refer to Figure 4 ) determined based on a magnetic field center C (refer to Figure 4 ) of the magnetic resonance imaging apparatus 10, or an arrangement prohibited region that is likely to be involved by movement of the examination bed 105 of the magnetic resonance imaging apparatus 10. The arrangement detection function 135h is an example of the fourth detection section. In addition, the electric field region E is an example of the first region. The arrangement prohibited region is an example of the second region. The arrangement detection function 135h has an electric field region detection function 135i and an involvement detection function 135j.

[0063] The electric field region detection function 135i detects a detection object from the electric field region E (refer to Figure 4 ) determined based on the magnetic field center C (refer to Figure 4 ) of the magnetic resonance imaging apparatus 10. The detection object of the electric field region detection function 135i is the subject P, the cable 13, or the like.

[0064] Here, Figure 4is a view showing an example of the electric field region E viewed from above. Figure 5 is a view showing an example of the electric field region E viewed from the Z-axis direction. Figure 4 The stand device 11 has a gradient magnetic field coil 103 formed in a substantially cylindrical shape on the inner side of the stand device 11. In addition, the magnetic resonance imaging device 10 generates a high-frequency magnetic field in such a manner that the magnetic field center C is formed at the position shown by Figure 4

[0065] In this case, if the cable 13, the subject P, or the like is disposed in the electric field region E, electric charges are accumulated between the gradient magnetic field coil 103 and the object disposed in the electric field region E. In other words, the gradient magnetic field coil 103 and the object disposed in the electric field region E function like a capacitor. Also, the cable 13, the subject P, or the like can be heated. Thus, the subject P can be scalded.

[0066] Therefore, the electric field region detection function 135i sets the electric field region E in which the cable 13, the subject P, or the like is prohibited from being disposed. In more detail, the electric field region detection function 135i sets, as the electric field region E, a range that is a first set distance in the Z-axis direction from the magnetic field center C on the ceiling 105a and is a second set distance from the edge of the ceiling 105a. As shown in Figure 4 Figure 5 As shown in and, the electric field region E is formed in a range at a certain distance from the inner wall of the stand device 11. That is, the electric field region detection function 135i forms the electric field region E in an arch shape. In addition, since the subject P is placed on the ceiling 105a, it is not disposed below the ceiling 105a. Therefore, the electric field region detection function 135i does not form the electric field region E below the ceiling 105a. In addition, the first set distance and the second set distance can be arbitrarily changed. Furthermore, the magnetic field center C on the ceiling 105a changes for each imaging of the subject P. For example, the position of the imaging of the subject P and the position of the subject P placed on the ceiling 105a change for each imaging of the subject P. Thus, the magnetic field center C on the ceiling 105a changes for each imaging of the subject P. Further, the electric field region E is formed at a position in the Z-axis direction on the ceiling 105a corresponding to the position at which the magnetic field center C is set. That is, the electric field region E is formed at a position in the Z-axis direction corresponding to the amount of feed of the ceiling 105a. For example, in a case where the amount of feed of the ceiling 105a is small, the electric field region E is formed on the ceiling 105a at a position close to the stand device 11. On the other hand, in a case where the amount of feed of the ceiling 105a is large, the electric field region E is formed on the ceiling 105a at a position away from the stand device 11. Then, the electric field region detection function 135i detects a detection target such as the arm, the leg, or the cable 13 of the subject P from the electric field region E.​​

[0067] The entanglement detection function 135j detects a detection object from a pre-set entanglement attention region. The entanglement attention region is, for example, a region of a gap between the examination bed 105 and the ceiling 105a, a region outside a long side direction edge of the ceiling 105a, or the like. In addition, the detection object is, for example, a tube of a drip, a tube for gas supply, a wiring, or the like.

[0068] Here, the magnetic resonance imaging apparatus 10, in a case where the subject P is imaged, inserts the ceiling 105a on which the subject P is placed into the imaging port of the gantry apparatus 11. When the ceiling 105a is moved, if a tube or a wiring is arranged in the entanglement attention region, the magnetic resonance imaging apparatus 10 can entangle the tube or the wiring.

[0069] For example, when a tube flies out to the outside from a long side direction edge of the ceiling 105a, the tube can be caught on the gantry apparatus 11 when the ceiling 105a is inserted into the imaging port. Or, if a tube is arranged in a gap between the ceiling 105a and the examination bed 105, the tube can be pulled into the gap when the ceiling 105a is inserted into the imaging port. Therefore, the entanglement detection function 135j detects a detection object from the entanglement attention region.

[0070] In addition, a method of using the magnetic resonance imaging apparatus 10 differs depending on a facility. That is, in the surroundings of the magnetic resonance imaging apparatus 10, in which position a medical instrument is arranged differs depending on a facility. Therefore, which position is set as the entanglement attention region can be arbitrarily changed.

[0071] The output function 135k outputs the detection results of the loop detection function 135d, the contact detection function 135g, and the arrangement detection function 135h. The output function 135k is an example of an output section. In more detail, the output function 135k outputs the detection results in two stages. The output function 135k, in a case where the loop detection function 135d, the contact detection function 135g, or the arrangement detection function 135h detects a detection object, causes a detection position image indicating a position of the detection object to be displayed on the display 134. The detection position image is an image in which a detection position of the detection object is highlighted in an image indicating each section of the magnetic resonance imaging apparatus 10. For example, the detection position image is an image in which an image indicating the detection object is superimposed on an image of the magnetic resonance imaging apparatus 10.

[0072] Further, the output function 135k reports that the detection object is detected by the loop detection function 135d, the contact detection function 135g, or the arrangement detection function 135h in a case where a reporting condition is detected. The reporting condition is, for example, an operation of inserting the top plate 105a into the imaging port of the stand device 11. The operation of inserting the top plate 105a into the imaging port of the stand device 11 is, for example, an operation of explicitly inserting the top plate 105a into the imaging port of the stand device 11, an operation accompanying the insertion of the top plate 105a into the imaging port of the stand device 11. The operation accompanying the insertion of the top plate 105a into the imaging port of the stand device 11 is, for example, an operation of determining an organ or the like to be an imaging target of the magnetic resonance imaging apparatus 10. Further, the reporting condition is one example, and can be arbitrarily changed.

[0073] The output function 135k reports, for example, by outputting an alarm sound. Further, the output function 135k displays a confirmation image on the display 134 in a pop-up display or the like, the confirmation image being for requesting confirmation of the detection result of the loop detection function 135d, the contact detection function 135g, or the arrangement detection function 135h. The confirmation image has a confirmation button indicating that the detection result is confirmed to be free of problems. Then, the output function 135k deletes the confirmation image in a case where an operation indicating that the detection result is confirmed to be free of problems is accepted. In a case where the confirmation image is deleted, the magnetic resonance imaging apparatus 10 continues the imaging of the subject P. In this way, the output function 135k can reduce the possibility of overlooking the detection result by restricting the imaging of the subject P by the magnetic resonance imaging apparatus 10.

[0074] Next, a confirmation assistance process performed by the magnetic resonance imaging apparatus 10 will be described. Figure 6 is a flowchart indicating one example of the confirmation assistance process performed by the magnetic resonance imaging apparatus 10 of the first embodiment.

[0075] The start condition detection function 135b determines whether or not a start condition of starting detection of a detection object is detected (step S1). In a case where the start condition is not detected (step S1: No), the start condition detection function 135b stands by.

[0076] In a case where the start condition is detected (step S1: Yes), the image acquisition function 135a acquires an image imaged by the camera 20 (step S2).

[0077] The object recognition function 135c recognizes each object included in the image acquired by the image acquisition function 135a (step S3).

[0078] The loop detection function 135d, the contact detection function 135g, or the configuration detection function 135h determines whether the detection object is detected (step S4). In a case where the detection object is not detected (step S4; No), the image acquisition function 135a acquires the image in step S2.

[0079] In a case where the detection object is detected (step S4; Yes), the output function 135k notifies the detection result of the loop detection function 135d, the contact detection function 135g, or the configuration detection function 135h (step S5). That is, the output function 135k causes the display 134 to display the detection position indicating the position at which the detection object is detected.

[0080] The output function 135k determines whether the reporting condition for reporting the detection result is satisfied (step S6). In a case where the reporting condition is not satisfied (step S6; No), the image acquisition function 135a acquires the image in step S2.

[0081] In a case where the reporting condition is satisfied (step S6; Yes), the output function 135k performs the reporting by causing the display 134 to display the confirmation screen requesting the confirmation of the detection result (step S7).

[0082] The output function 135k determines whether the confirmation operation indicating that the detection result is confirmed is accepted (step S8). In a case where the confirmation operation is not accepted (step S8; No), the output function 135k continues the display of the confirmation screen in step S7.

[0083] In a case where the confirmation operation is accepted (step S8; Yes), the magnetic resonance imaging apparatus 10 deletes the confirmation screen, and ends the confirmation assistance processing.

[0084] As described above, the magnetic resonance imaging apparatus 10 of the first embodiment acquires the image obtained by the camera 20 capturing the subject P loaded on the top plate 105a of the magnetic resonance imaging apparatus 10. In addition, the magnetic resonance imaging apparatus 10 detects the cable loop 13a, the loop of the subject P, the portion in contact with the cable 13, the portion in which the top plate 105a is likely to be entangled with the cable 13, the tube, or the like from the acquired image. Then, the magnetic resonance imaging apparatus 10 outputs to the user by displaying the detection result or the like. Accordingly, the magnetic resonance imaging apparatus 10 can reduce the confirmation burden of the user.

[0085] (Modified Example 1)

[0086] In the first embodiment, the magnetic resonance imaging apparatus 10 is provided with the image acquisition function 135a, the start condition detection function 135b, the object recognition function 135c, the loop detection function 135d, the cable loop detection function 135e, the subject loop detection function 135f, the contact detection function 135g, the arrangement detection function 135h, the electric field region detection function 135i, the entanglement detection function 135j, and the output function 135k. However, the image acquisition function 135a, the start condition detection function 135b, the object recognition function 135c, the loop detection function 135d, the cable loop detection function 135e, the subject loop detection function 135f, the contact detection function 135g, the arrangement detection function 135h, the electric field region detection function 135i, the entanglement detection function 135j, and the output function 135k are not limited to the magnetic resonance imaging apparatus 10, and can be provided to other apparatuses. For example, the image acquisition function 135a, the start condition detection function 135b, the object recognition function 135c, the loop detection function 135d, the cable loop detection function 135e, the subject loop detection function 135f, the contact detection function 135g, the arrangement detection function 135h, the electric field region detection function 135i, the entanglement detection function 135j, and the output function 135k can be provided to a computer apparatus such as a personal computer, a server, a workstation, or the like.

[0087] In addition, the image acquisition function, the start condition detection function, the object recognition function, the loop detection function, the cable loop detection function, the subject loop detection function, the contact detection function, the arrangement detection function, the electric field region detection function, the entanglement detection function, and the output function in the present specification can be realized by only hardware, only software, or a mixture of hardware and software, in addition to the processing circuit 135 described in each of the above embodiments.

[0088] The several embodiments have been described, but these embodiments are presented as examples and are not intended to limit the scope of the invention. The embodiments can be implemented in various other ways, and various omissions, substitutions, modifications, combinations of the embodiments with each other can be made within the scope of the gist of the invention. The embodiments and modifications thereof are included in the scope or gist of the invention, and are also included in the scope of the invention and equivalents thereof recited in the claims.

Claims

1. An image processing apparatus comprising: The acquisition unit acquires three-dimensional images of the subject placed on the top plate of the magnetic resonance imaging device by using a camera. The identification unit identifies objects contained in the three-dimensional image acquired by the acquisition unit; The first detection unit, based on the three-dimensional spatial configuration of the three-dimensional image acquired by the acquisition unit, detects either a first loop formed by the cable of the radio frequency coil (RF coil) used in the magnetic resonance imaging device, or a second loop formed by the subject, which may generate an induced current due to the magnetic field generated by the magnetic resonance imaging device; and The output unit displays a detection position image, which is obtained by superimposing a first image, which highlights the detected loop, onto a second image representing each part of the magnetic resonance imaging device.

2. The image processing apparatus according to claim 1, If the first detection unit identifies the object as a specific object by the recognition unit, it will not detect it as the loop.

3. The image processing apparatus according to claim 2, If the first detection unit identifies the object as the same object by the recognition unit, it detects the loop.

4. The image processing apparatus according to claim 2, The identification unit identifies the cable of the RF coil used in the magnetic resonance imaging device based on the colors or patterns contained in the three-dimensional image.

5. The image processing apparatus according to claim 1, The first detection unit detects the loop from the three-dimensional image captured by the camera that detects infrared light.

6. The image processing apparatus according to claim 1, The first detection unit detects the loops based on the learned model, which detects the loops contained in the three-dimensional image when the three-dimensional image is input.

7. The image processing apparatus according to any one of claims 1 to 6, It also includes a second detection unit that detects the start conditions that cause the first detection unit to begin detecting the object to be detected.

Images