Exterior field response distribution visualization device and exterior field response distribution visualization method

Abstract

An external field response distribution visualization device (100) includes: a sensing circuit (110) that induces a first field component from each of a plurality of sensing positions; a sensor (130) that senses the intensity of the field at a plurality of sensing positions for each of the plurality of sensing positions; and an information processing circuit (150) that generates an image representing the external field response distribution, the information processing circuit (150) calculating a sensing position-dependent field function that inputs a sensing position and a sensing position and outputs the intensity of the field using the sensing result as a boundary condition, calculating an imaging function that is a function that inputs an imaging target position and outputs an image intensity, is a function determined based on the intensity output from the sensing position-dependent field function by inputting the imaging target position to the sensing position-dependent field function, and generating the image based on the imaging function.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to an external field response distribution visualization device or the like that generates an image representing an external field response distribution. BACKGROUND

[0002] In Patent Literature 1, a device that acquires a field by measurement is described. The device acquires a magnetic force image of a distribution of a magnetic force on a first measurement surface above a sample, acquires an auxiliary magnetic force image by measurement on a second measurement surface at a minute distance d from the first measurement surface, and acquires a magnetic force gradient image by dividing a difference between the magnetic force image and the auxiliary magnetic force image by the minute distance d. Then, the device acquires a three-dimensional field representing the magnetic force by Fourier transforming the magnetic force image and the magnetic force gradient image and substituting them into a three-dimensional field acquisition formula derived from a general solution of Laplace's equation.

[0003] The device described in Patent Literature 1 is able to acquire a state of magnetic domains on a surface of a sample with high precision by acquiring a three-dimensional field.

[0004] PRIOR ART DOCUMENTS

[0005] PATENT LITERATURE

[0006] Patent Literature: International Publication No. 2008 / 123432 SUMMARY

[0007] PROBLEMS TO BE SOLVED BY THE INVENTION

[0008] However, the device described in Patent Literature 1 is only able to acquire a state of magnetic domains on a surface of a sample. It is difficult to acquire a state of magnetic domains at a position deeper than the surface of a sample. That is, it is difficult to acquire a distribution of magnetic susceptibility (that is, an external field response distribution) inside a sample.

[0009] Therefore, the present disclosure provides an external field response distribution visualization device or the like that is able to generate an image representing an external field response distribution of a region including an interior of an object with high precision.

[0010] SOLUTION TO PROBLEM

[0011] One aspect of this disclosure relates to an external field response distribution visualization apparatus that generates an image representing the distribution of responses to an external field, i.e., the external field response distribution. The apparatus comprises: a sensing circuit that senses a first field component from each of a plurality of sensing positions relative to the object, located outside the object; a sensor that senses the intensity of a field at each of the plurality of sensing positions relative to the object, including a second field component sensed from the object due to the first field component, at each of the plurality of sensing positions, thereby sensing the intensity of the field at each of the plurality of sensing positions; and an information processing circuit that acquires a sensing result of the field intensity and generates a representation based on the sensing result. The image of the external field response distribution of the object, including its internal region, is used by the information processing circuit as a boundary condition to calculate a sensing position-related field function that takes a virtual sensing position as input and outputs the field intensity at the virtual sensing position. The information processing circuit also calculates an image function that takes an image object position as input and outputs the image intensity at the image object position. This image function is determined based on the intensity output from the sensing position-related field function by inputting the image object position as the virtual sensing position and the virtual sensing position into the sensing position-related field function. The information processing circuit generates the image based on the image function.

[0012] Furthermore, these general or specific methods can be implemented by systems, devices, methods, integrated circuits, computer programs, or non-transitory recording media such as computer-readable CD-ROMs, or by any combination of systems, devices, methods, integrated circuits, computer programs, and recording media.

[0013] The effects of the invention

[0014] According to one aspect of this disclosure, it is possible to generate with high precision an image representing the distribution of the external field response of a region including the interior of an object. Attached Figure Description

[0015] Figure 1 This is a structural diagram showing the first example of a visualization device for magnetic susceptibility distribution in the implementation method.

[0016] Figure 2 This is a conceptual diagram representing the reconstruction of the magnetic field in the reference example.

[0017] Figure 3 This is a conceptual diagram illustrating the sensing position and the sensing location in the implementation method.

[0018] Figure 4 This is a conceptual diagram illustrating other examples of sensing and sensing positions in the implementation method.

[0019] Figure 5 is a conceptual diagram representing another other example of the inductive position and the sensing position in the embodiment.

[0020] Figure 6 is a structural diagram representing a second example of the magnetic susceptibility distribution visualization device in the embodiment.

[0021] Figure 7 is a conceptual diagram representing a first example of the human body scanner in the embodiment.

[0022] Figure 8 is a conceptual diagram representing the inductive circuit in the embodiment.

[0023] Figure 9 is a conceptual diagram representing the magnetic sensor in the embodiment.

[0024] Figure 10 is a conceptual diagram representing a specific configuration of the magnetic sensor in the embodiment.

[0025] Figure 11 is a conceptual diagram representing a second example of the human body scanner in the embodiment.

[0026] Figure 12 is a conceptual diagram representing a third example of the human body scanner in the embodiment.

[0027] Figure 13 is a conceptual diagram representing a combination circuit of the magnetic sensor and the inductive circuit in the embodiment.

[0028] Figure 14 is a conceptual diagram representing a fourth example of the human body scanner in the embodiment.

[0029] Figure 15 is a conceptual diagram representing a fifth example of the human body scanner in the embodiment.

[0030] Figure 16 is a conceptual diagram representing a sixth example of the human body scanner in the embodiment.

[0031] Figure 17 is a conceptual diagram representing an example of information displayed on an external terminal in the embodiment.

[0032] Figure 18 is a conceptual diagram representing an example of the security inspection system in the embodiment.

[0033] Figure 19 is a flowchart representing the action of the magnetic susceptibility distribution visualization device in the embodiment. DETAILED DESCRIPTION

[0034] For example, an external field response distribution visualization device according to one embodiment of the present disclosure generates an image representing a distribution of responses to an external field, that is, an external field response distribution, and includes: a sensing circuit that senses a first field component generated from each of a plurality of sensing positions that are determined as a plurality of positions relative to an object on the outside of the object; a sensor that senses an intensity of a field including a second field component generated from the object due to the first field component at each of a plurality of sensing positions that are determined as a plurality of positions relative to the object on the outside of the object, thereby sensing the intensity of the field at the plurality of sensing positions for each of the plurality of sensing positions; and an information processing circuit that acquires a sensing result of the intensity of the field, generates the image representing the external field response distribution of a region including an interior of the object based on the sensing result, and calculates an induced position-dependent field function of an intensity of the field at a virtual sensing position by inputting a virtual sensing position and a virtual sensing position and using the sensing result as a boundary condition, calculates an imaging function that is a function of inputting an imaging target position and outputting an image intensity of the imaging target position, is a function determined based on an intensity output from the induced position-dependent field function by inputting the imaging target position as the virtual sensing position and the virtual sensing position to the induced position-dependent field function, and generates the image based on the imaging function.

[0035] Thus, the external field response distribution visualization device can generate an image representing an external field response distribution of a region including an interior of an object with high precision based on a sensing result of an intensity of a field according to a variety of combinations of each of a plurality of sensing positions and each of a plurality of sensing positions.

[0036] For example, the information processing circuit calculates a solution of a Laplace equation satisfied by the induced position-dependent field function as the induced position-dependent field function using the sensing result as the boundary condition.

[0037] Thus, the external field response distribution visualization device can appropriately derive an induced position-dependent field function based on a sensing result and a Laplace equation related to a multipath problem in a static or quasi-static field.

[0038] For example, the information processing circuit calculates a limit value of the induced position-dependent field function as the imaging function by performing a limit operation on the induced position-dependent field function such that the virtual sensing position and the virtual sensing position input to the induced position-dependent field function tend toward the imaging target position.

[0039] Thus, the external field response distribution visualizing apparatus can appropriately derive the imaging function based on the induced position-dependent field function.

[0040] Further, for example, the plurality of sensing positions are determined on a first plane, and the plurality of sensing positions are determined on a second plane that is the same as or different from the first plane.

[0041] Thus, the external field response distribution visualizing apparatus can suppress an increase in the configuration space of the induction circuit and the sensor. Further, the external field response distribution visualizing apparatus can suppress complication of the operation processing.

[0042] Further, for example, the plurality of sensing positions are located on the same side as the plurality of induction positions with respect to the object.

[0043] Thus, the external field response distribution visualizing apparatus can sense the intensity of the field at each of the plurality of sensing positions on the side opposite the plurality of induction positions with respect to the object. Thus, the external field response distribution visualizing apparatus can suppress the influence of the first field component induced by the induction circuit when sensing the intensity of the field at each of the plurality of sensing positions.

[0044] Further, for example, the plurality of sensing positions are located on the same side as the plurality of induction positions with respect to the object.

[0045] Thus, the external field response distribution visualizing apparatus can sense the intensity of the field at each of the plurality of sensing positions on the same side as the plurality of induction positions with respect to the object. Thus, the external field response distribution visualizing apparatus can suppress an increase in the configuration space of the induction circuit and the sensor.

[0046] Further, for example, the induction circuit moves to each of the plurality of induction positions, induces the first field component from each of the plurality of induction positions, and the sensor moves to each of the plurality of sensing positions, senses the intensity of the field at each of the plurality of sensing positions.

[0047] Thus, the external field response distribution visualizing apparatus can apply one induction circuit to the plurality of induction positions, and one sensor to the plurality of sensing positions. Thus, the external field response distribution visualizing apparatus can suppress an increase in resource costs.

[0048] Further, for example, the induction circuit is constituted by a plurality of induction circuits disposed at the plurality of induction positions, and the sensor is constituted by a plurality of sensors disposed at the plurality of sensing positions.

[0049] Thus, the external field response distribution visualization device can induce the field component from each of the plurality of induction positions without moving the induction circuit and the sensor, and can sense the intensity of the field at each of the plurality of sensing positions. Thus, the external field response distribution visualization device can acquire the sensing results corresponding to the plurality of induction positions and the plurality of sensing positions at high speed.

[0050] In addition, for example, the plurality of induction circuits are arranged on a first plane, and the plurality of sensors are arranged on a second plane that is the same as or different from the first plane.

[0051] Thus, the external field response distribution visualization device can acquire the sensing results corresponding to the plurality of induction positions on the first plane and the plurality of sensing positions on the second plane at high speed.

[0052] In addition, for example, the plurality of induction circuits are arranged on a first straight line, and the plurality of sensors are arranged on a second straight line that is the same as or different from the first straight line.

[0053] Thus, the external field response distribution visualization device can reduce the space in which the plurality of induction circuits are arranged and the space in which the plurality of sensors are arranged.

[0054] In addition, for example, the object moves, the induction circuit induces the first field component from the prescribed position at each of a plurality of times that are different from each other, thereby inducing the first field component from each of the plurality of induction positions that are determined relative to the moving object, and the sensor senses the intensity of the field at the prescribed position at each of a plurality of times that are different from each other, thereby sensing the intensity of the field at each of the plurality of sensing positions that are determined relative to the moving object.

[0055] Thus, the external field response distribution visualization device can induce the field component from each of the plurality of induction positions without arranging a large number of induction circuits and a large number of sensors, and can sense the intensity of the field at each of the plurality of sensing positions without moving the induction circuit and the sensor.

[0056] In addition, for example, the induction circuit is included in a first wall, and the sensor is included in a second wall that is the same as or different from the first wall.

[0057] Thus, the external field response distribution visualization device can generate the image representing the external field response distribution without being noticed by a person.

[0058] In addition, for example, the induction circuit and the sensor are included in the ground.

[0059] Thus, the external field response distribution visualization device can generate the image representing the external field response distribution without being noticed by a person.

[0060] Alternatively, for example, the sensing circuit is included in a first column, and the sensor is included in a second column that is the same as or different from the first column.

[0061] Thus, the external field response distribution visualization device can generate an image representing the external field response distribution without being noticed by humans.

[0062] Furthermore, for example, in a three-dimensional space composed of x, y, and z coordinates, the virtual sensing position is represented by (y1, z1), the virtual sensing position is represented by (x, y2, z2), the z-coordinate of the location where the sensing circuit exists is determined as 0, the z-coordinate of the location where the sensor exists is determined as z0, and the sensing position correlation field function is...

[0063] [Number 1]

[0064]

[0065] To determine,

[0066] [Number 2]

[0067]

[0068] The Fourier transform image representing the sensing result, k x k y1 and k y2 These are the wavenumbers related to x, y1, and y2, respectively. The visualization function uses...

[0069] [Number 3]

[0070]

[0071] To determine.

[0072] Therefore, the external field response distribution visualization device can use the sensing position-related field function expressed in the above formula and the image function expressed in the above formula to generate an image representing the external field response distribution with high precision.

[0073] Furthermore, for example, in a three-dimensional space composed of x, y, and z coordinates, the virtual sensing position is represented by (y1, z1), the virtual sensing position is represented by (x, y2, z2), the z-coordinate of the location where the sensing circuit exists is determined as 0, the z-coordinate of the location where the sensor exists is determined as z0, and the sensing position correlation field function is...

[0074] [Number 4]

[0075]

[0076] To determine,

[0077] [Num 5]

[0078]

[0079] a Fourier transform image representing the sensing result, k x , k y1 and k y2 are wave numbers related to x, y1 and y2, respectively, and the imaging function is determined by

[0080] [Num 6]

[0081]

[0082]

[0083] Thus, the external field response distribution visualization device can use the induction position dependent field function expressed by the above formula and the imaging function expressed by the above formula to generate an image representing the external field response distribution with high precision.

[0084] In addition, for example, in a three-dimensional space composed of an x coordinate, a y coordinate and a z coordinate, the virtual induction position is expressed by (x1, y, z1), the virtual sensing position is expressed by (x2, y, z2), the z coordinate of the position where the induction circuit exists is determined to be 0, the z coordinate of the position where the sensor exists is determined to be z0, and the induction position dependent field function is determined by

[0085] [Num 7]

[0086]

[0087]

[0088] [Num 8]

[0089]

[0090] a Fourier transform image representing the sensing result, k x1 , k x2 and k y are wave numbers related to x1, x2 and y, respectively, and the imaging function is determined by

[0091] [Num 9]

[0092]

[0093]

[0094] Thus, the external field response distribution visualization device can use the induction position dependent field function expressed by the above formula and the imaging function expressed by the above formula to generate an image representing the external field response distribution with high precision.​​​

[0095] In addition, for example, in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual induction position is expressed by (x1, y, z1), the virtual sensing position is expressed by (x2, y, z2), the z coordinate of the position where the induction circuit exists is determined to be 0, the z coordinate of the position where the sensor exists is determined to be z0, and the induction position-dependent field function is determined by

[0096] [Equation 10]

[0097]

[0098]

[0099] [Equation 11]

[0100]

[0101] The Fourier transform image representing the sensing result, k x1 , k x2 , and k y are wave numbers related to x1, x2, and y, respectively, and the imaging function is determined by

[0102] [Equation 12]

[0103]

[0104]

[0105] Thus, the external field response distribution visualization device can generate an image representing an external field response distribution with high precision using the induction position-dependent field function expressed by the above equation and the imaging function expressed by the above equation.

[0106] In addition, for example, the information processing circuit determines whether or not a detection target object is included in the object on the basis of the image, and outputs information representing the position of the detection target object or the object to an external terminal in a case where it is determined that the detection target object is included in the object.

[0107] Thus, the external field response distribution visualization device can notify the position of a specific detection target object or the position of an object including a specific detection target object.

[0108] ​​Further, for example, the present disclosure relates to an external field response distribution visualization method that generates an image representing a distribution of responses to an external field, that is, an external field response distribution, characterized by including the steps of: using an induction circuit, inducing a first field component from each of a plurality of induction positions that are determined to be a plurality of positions relative to an object on the outside of the object; using a sensor, sensing an intensity of a field including a second field component induced from the object due to the first field component at each of a plurality of sensing positions that are determined to be a plurality of positions relative to the object on the outside of the object, thereby sensing the intensity of the field at the plurality of sensing positions for each of the plurality of induction positions; and acquiring a sensing result of the intensity of the field, generating the image representing the external field response distribution of a region including an interior of the object based on the sensing result, in the step of generating the image, using the sensing result as a boundary condition, calculating an induction position-dependent field function that inputs a virtual induction position and a virtual sensing position and outputs an intensity of the field at the virtual sensing position, calculating an imaging function that is a function that inputs an imaging object position and outputs an intensity of an image at the imaging object position, is a function determined based on an intensity output from the induction position-dependent field function by inputting the imaging object position to the induction position-dependent field function as the virtual induction position and the virtual sensing position, and generating the image based on the imaging function.

[0109] Thus, it is possible to generate an image representing an external field response distribution of a region including an interior of an object with high precision based on a sensing result of an intensity of a field in a variety of combinations of each of a plurality of induction positions and each of a plurality of sensing positions.

[0110] Hereinafter, the embodiments will be described using drawings. Furthermore, the embodiments described below each represent an example in general or a specific example. Numerical values, shapes, materials, structural elements, arrangement positions and connection modes of structural elements, steps, orders of steps, and the like shown in the following embodiments are merely examples, and the purpose is not to limit the scope of protection.

[0111] Further, here, as an example of an external field response distribution visualization device, a magnetic susceptibility distribution visualization device using a magnetic field is mainly described. Further, a magnetic field component in the description herein is a component constituting a magnetic field. The magnetic field component can also be each of a plurality of magnetic fields superimposed on the entire magnetic field.

[0112] (Embodiment)

[0113] Figure 1 is a structural diagram representing a first example of a magnetic susceptibility distribution visualization device in the present embodiment. Figure 1The illustrated magnetic susceptibility distribution visualizing apparatus 100 is provided with an induction circuit 110, an induction circuit actuator 120, a magnetic sensor 130, a magnetic sensor actuator 140, an information processing circuit 150, a display 160, and a sample stage 170. Furthermore, the magnetic susceptibility distribution visualizing apparatus 100 generates an image representing a magnetic susceptibility distribution of a region including the inside of a sample placed on the sample stage 170. This image can represent a magnetic body, more specifically a ferromagnetic body, contained in the sample.

[0114] The induction circuit 110 is a circuit that induces a magnetic field component. The induction circuit 110 can also be a coil or a wire, etc. Here, the magnetic field component induced by the induction circuit 110 is referred to as a first magnetic field component. In the example shown in FIG. 1, the induction circuit 110 is stationary. Furthermore, the induction circuit 110 induces the first magnetic field component from each of a plurality of induction positions. By the first magnetic field component, a magnetic field component is induced from the sample. Here, the magnetic field component induced from the sample is referred to as a second magnetic field component. Figure 1

[0115] The induction circuit actuator 120 is an actuator that moves the induction circuit 110. The induction circuit actuator 120 moves the induction circuit 110 to each of a plurality of induction positions. Thereby, the induction circuit 110 induces the first magnetic field component from each of the plurality of induction positions.

[0116] The magnetic sensor 130 is a sensor that senses magnetism. The magnetic sensor 130 can also be a TMR (Tunneling Magneto Resistive) element, a GMR (Giant Magneto Resistive) element, a SQUID (Superconducting Quantum Interference Device) element, or a MI (Magneto-Impedance element), etc.

[0117] In the example shown in FIG. 1, the magnetic sensor 130 is stationary. Furthermore, the magnetic sensor 130 senses magnetism in a magnetic field containing the second magnetic field component induced from the sample at each of a plurality of sensing positions. Thereby, the magnetic sensor 130 senses magnetism at the plurality of sensing positions with respect to each of the plurality of induction positions. Figure 1

[0118] The magnetic sensor actuator 140 is an actuator that moves the magnetic sensor 130. The magnetic sensor actuator 140 moves the magnetic sensor 130 to each of a plurality of sensing positions. Thereby, the magnetic sensor 130 senses magnetism at each of the plurality of sensing positions.

[0119] ​​The information processing circuit 150 is a circuit that performs information processing. The information processing circuit 150 can also be a computer or a processor of a computer, or the like. The information processing circuit 150 acquires a magnetic sensing result, and generates an image representing a magnetic susceptibility distribution of a region including the inside of a sample based on the sensing result.

[0120] Specifically, the information processing circuit 150 calculates a sensing position dependent magnetic field function using the sensing result as a boundary condition. The sensing position dependent magnetic field function is a function that inputs a sensing position of a first magnetic field component and a magnetic sensing position and outputs a strength of the magnetism at the sensing position.

[0121] Further, the information processing circuit 150 calculates an imaging function. The imaging function is a function that inputs an imaging target position and outputs an image intensity of the imaging target position, and is a function determined based on a strength output from the sensing position dependent magnetic field function by inputting the imaging target position to the sensing position dependent magnetic field function as the sensing position and the sensing position. Further, the information processing circuit 150 generates an image representing a magnetic susceptibility distribution of a region including the inside of a sample based on the imaging function.

[0122] In addition, the information processing circuit 150 can also output the generated image to the display 160 or the like. For example, the information processing circuit 150 can also display the image on the display 160 by outputting the image to the display 160. Alternatively, the information processing circuit 150 can also print the image by a printer (not illustrated) by outputting the image to the printer. Alternatively, the information processing circuit 150 can also transmit the image as electronic data to another device (not illustrated) through wired or wireless communication.

[0123] The display 160 is a display device such as a liquid crystal display. Further, the display 160 is an arbitrary structural element, and is not a necessary structural element. In addition, the display 160 can also be a device that is external to the magnetic susceptibility distribution visualization device 100.

[0124] The sample stage 170 is a stage for placing a sample. Further, the sample stage 170 is an arbitrary structural element, and is not a necessary structural element. The magnetic susceptibility distribution visualization device 100 can also generate an image for a sample that is not placed on the sample stage 170 or the like. In addition, the sample stage 170 can also be a structural element that is external to the magnetic susceptibility distribution visualization device 100. The sample can be a circuit, or another object.

[0125] The magnetic susceptibility distribution visualization device 100 senses the magnetism affected by the sample while changing the relative positional relationship between the sample and the sensing and sensing positions. As a result, the magnetic susceptibility distribution visualization device 100 can acquire sufficient information related to the magnetic susceptibility distribution of the sample, including its internal regions. Then, based on the acquired sufficient information, the magnetic susceptibility distribution visualization device 100 can calculate the sensing position-related magnetic field function and generate an image representing the magnetic susceptibility distribution with high precision based on the calculated sensing position-related magnetic field function.

[0126] For example, the magnetic susceptibility distribution visualization device 100 can generate a high-precision image by synthesizing multiple measurements corresponding to multiple combinations of multiple sensing positions and multiple sensing locations.

[0127] Figure 2 This is a conceptual diagram representing the reconstruction of the magnetic field in the reference example. The static magnetic field in a space where there is no magnetic source satisfies the following equation (1-1) according to Maxwell's equations.

[0128] [Number 13]

[0129] ΔH z =0

[0130] ···(1-1)

[0131] In the above equation (1-1), H z It is the magnetic field in the z-direction of the xyz orthogonal coordinate system, corresponding to the z-component of the magnetic field vector. Δ is the Laplace operator, also known as the Laplace symbol. Furthermore, the general solution of the above equation (1-1) is expressed as the sum of terms that increase exponentially in the z-direction and terms that decrease exponentially, as shown in equation (1-2).

[0132] [Number 14]

[0133]

[0134] In equation (1-2) above, k x and k y These represent the wavenumber in the x-direction and the wavenumber in the y-direction, respectively. Additionally, a(k) x k y ) and b(k x k y ) is using k x and k y The function represented. For example, by measurement, the z-component H of the magnetic field vector on the plane z=0 can be obtained. z (x, y, 0) and the gradient in the z-direction of the z-component of the magnetic field vector. Using these methods, we can find a(k) of equation (1-2) as shown in equations (1-3) and (1-4) below.x , k y ) and b(k x , k y ).

[0135] [Num 15]

[0136]

[0137] [Num 16]

[0138]

[0139] In the above-described formula (1-3) and formula (1-4), f(k x , k y ) is a two-dimensional Fourier transform image of H z (x, y, 0), and g(k x , k y ) is a two-dimensional Fourier transform image of By substituting formula (1-2) into formula (1-3) and formula (1-4), H z is obtained as the following formula (1-5).

[0140] [Num 17]

[0141]

[0142] By the above-described method, H z (x, y, z) at an arbitrary z coordinate of a space in which a magnetic generation source does not exist can be obtained using H z (x, y, 0) as a Dirichlet-type boundary condition and as a Neumann-type boundary condition. That is, a magnetic field on the surface of a sample can be reconstructed from a magnetic field on a measurement surface which is an xy plane of z = 0.

[0143] However, the formula used in the above-described method holds in a space in which a magnetic generation source does not exist. Thus, it is difficult to reconstruct a magnetic field at a position deeper than the surface of a sample only by the above-described method. That is, it is difficult to visualize a magnetic susceptibility distribution inside a sample in which a magnetic generation source exists only by the above-described method.

[0144] In contrast to this, the magnetic susceptibility distribution visualization device 100 in the present embodiment calculates a position-of-induction-dependent magnetic field function based on a sensing result obtained by changing a relative positional relationship between a sample and a position of induction and a position of sensing while sensing magnetism. Then, the magnetic susceptibility distribution visualization device 100 generates an image representing a magnetic susceptibility distribution based on the position-of-induction-dependent magnetic field function. That is, the magnetic susceptibility distribution visualization device 100 can reconstruct a magnetic field at a position deeper than the surface of a sample.

[0145] Figure 3 is a conceptual diagram showing the induction position and the sensing position in the present embodiment. In Figure 3 , the induction position and the sensing position in an xyz orthogonal coordinate system are shown.

[0146] Specifically, the induction circuit 110 is a wire through which current flows in parallel with the x axis. Thus, the position of the induction circuit 110 is shown as T LINE (y1, z1). That is, the induction position is shown as T LINE (y1, z1). In addition, the magnetic sensor 130 can have an x coordinate, a y coordinate, and a z coordinate, and thus the position of the magnetic sensor 130 is shown as R TMR (x, y2, z2). That is, the sensing position is shown as R TMR (x, y2, z2).

[0147] In addition, in the example of Figure 3 , the position of the sample is shown as P. The sample can also be shown as an induction magnetic source. Furthermore, the magnetic field components are transmitted in the manner of T LINE (y1, z1) → P → R TMR (x, y2, z2).

[0148] In addition, with respect to the induction position T LINE (y1, z1) and the sensing position R TMR (x, y2, z2), the strength of the magnetism at the sensing position R TMR (x, y2, z2) can be shown as Φ(x, y1, y2, z1, z2). Φ(x, y1, y2, z1, z2) is an induction position-dependent magnetic field function that inputs the induction position T LINE (y1, z1) and the sensing position R TMR (x, y2, z2) and outputs the strength of the magnetism at the sensing position R TMR (x, y2, z2).

[0149] The induction position T LINE (y1, z1) can also be a virtual position of the induction circuit 110. The sensing position R TMR (x, y2, z2) can also be a virtual position of the magnetic sensor 130. In the case where the induction position T LINE (y1, z1) coincides with the actual position of the induction circuit 110 and the sensing position R TMR (x, y2, z2) coincides with the actual position of the magnetic sensor 130, Φ(x, y1, y2, z1, z2) coincides with the measured value that is the actual sensing result.

[0150] In addition, in the example of Figure 3In the example of FIG. 10, the induction circuit 110 is located at z = 0, and scanning is performed in the y-axis direction. In addition, the magnetic sensor 130 is located at z = z0, and scanning is performed in the x-axis direction and the y-axis direction on the xy plane. Thus, for each combination of x, y1, and y2, Φ(x, y1, y2, z1 = 0, z2 = z0) is obtained as a measurement value. This measurement value is used as a boundary condition for Φ(x, y1, y2, z1, z2) as a magnetic field function related to the induction position.

[0151] In addition, Φ(x, y1, y2, z1, z2) is a harmonic function related to y1 and z1 of the sensing position T LINE (y1, z1), and is a harmonic function related to x, y2, and z2 of the sensing position R TMR (x, y2, z2). Thus, Φ(x, y1, y2, z1, z2) satisfies the following equations (2-1) and (2-2) as basic equations, respectively, as Laplace equations related to a multipath problem in a static or quasi-static field.

[0152] [Num 18]

[0153]

[0154] [Num 19]

[0155]

[0156] In a case where the z coordinate of the position P of the sample is greater than the z coordinate of the induction circuit 110 and is less than the z coordinate of the magnetic sensor 130, the general solutions of equations (2-1) and (2-2) are expressed by one of a term that increases exponentially in the z direction and a term that attenuates exponentially. Specifically, the general solutions of equations (2-1) and (2-2) are expressed as equations (2-3) and (2-4), respectively, as follows.

[0157] [Num 20]

[0158]

[0159] [Num 21]

[0160]

[0161] The combination of equations (2-3) and (2-4) is expressed as equation (2-5) as follows.

[0162] [Num 22]

[0163]

[0164] By applying z1=0 and the measured value at z2=z0 to formula (2-5) as a boundary condition, the following formula (2-6) is obtained.

[0165] [Num 23]

[0166]

[0167] By inverse Fourier transform of formula (2-6), the following formula (2-7) is obtained.

[0168] [Num 24]

[0169]

[0170] Here,

[0171] [Num 25]

[0172]

[0173] is a Fourier transform image of the measured value. Thus, the induced position-dependent magnetic field function is expressed by the following formula (2-8).

[0174] [Num 26]

[0175]

[0176] It is assumed that by applying x→x, y2→y1(=y), and z2→z1(=z) to the induced position-dependent magnetic field function, the intensity of the magnetism sensed at (x, y, z) after the induced generated magnetic field component is sensed there. Also, it is assumed that the stronger the magnetism, the higher the magnetic susceptibility, and it is assumed that an image representing the intensity of the magnetism represents the magnetic susceptibility distribution of the region including the interior of the sample. An imaging function for generating such an image is expressed by the following formula (2-9).

[0177] [Num 27]

[0178]

[0179] The imaging function represented by formula (2-9) is a function that inputs an imaging target position and outputs the image intensity of the imaging target position. The image intensity corresponds to the value output as the intensity of the magnetism from the induced position-dependent magnetic field function by inputting the imaging target position to the induced position-dependent magnetic field function.

[0180] For example, the information processing circuit 150 of the magnetic susceptibility distribution visualization device 100 calculates the induced position-dependent magnetic field function on the basis of the sensing result as a measured value and Equation (2-8). Then, the information processing circuit 150 calculates the imaging function on the basis of the induced position-dependent magnetic field function and Equation (2-9). Then, the information processing circuit 150 generates an image representing the magnetic susceptibility distribution on the basis of the imaging function. Specifically, the information processing circuit 150 generates an image constituted by values output from the imaging function for each imaging target position as the image representing the magnetic susceptibility distribution.

[0181] Thus, the magnetic susceptibility distribution visualization device 100 can generate an image representing the magnetic susceptibility distribution with high precision using the induced position-dependent magnetic field function and the imaging function described above.

[0182] Using Figure 3 The equations of the induced position-dependent magnetic field function and the imaging function and the like described above are examples, and the equations of the induced position-dependent magnetic field function and the imaging function and the like are not limited to the examples described above. Other equations based on other conditions can be derived by the same kind of method as the method described above.

[0183] For example, in the example of Figure 3 The magnetic sensor 130 can also be located on the same side as the induction circuit 110 with respect to the sample. For example, in a case where the z coordinate of P is smaller than the z coordinate of the induction circuit 110 and smaller than the z coordinate of the magnetic sensor 130, the above-described Equation (2-3) is replaced by the following Equation (3-1).

[0184] [Num 28]

[0185]

[0186] Thus, in this case, the induced position-dependent magnetic field function is expressed by the following Equation (3-2).

[0187] [Num 29]

[0188]

[0189] In this case, the imaging function is expressed by the following Equation (3-3).

[0190] [Num 30]

[0191]

[0192] Figure 4 is a conceptual diagram representing other examples of the induced position and the sensing position in the present embodiment. As with the example of Figure 3 As with the example of Figure 4The example illustrates the sensing position and the perceived position in the xyz orthogonal coordinate system. Figure 4 In this example, the sensing circuit 110 is a coil. Furthermore, the sensing circuit 110 and the magnetic sensor 130 are located at the same y-coordinate, and the y-coordinate of the sensing circuit 110 changes in tandem with the y-coordinate of the magnetic sensor 130.

[0193] Therefore, the position of the sensing circuit 110 is represented by T. COIL (x1, y, z1). That is, the sensing position is represented by T. COIL (x1, y, z1). Additionally, the position of the magnetic sensor 130 is represented by R. TMR (x2, y, z2). In other words, the sensed position is represented by R. TMR (x2, y, z2). x1 and x2 are independent of each other, and z1 and z2 are independent of each other.

[0194] In addition, with Figure 3 Similarly, in Figure 4 In the example, P represents the position of the sample. Furthermore, the magnetic field composition is expressed in terms of T. COIL (x1, y, z1) → P → R TMR The data is passed in the form of (x2, y, z2).

[0195] Additionally, regarding the sensing position T COIL (x1, y, z1) and sensing position R TMR (x2, y, z2), sensing position R TMR The magnetic field strength at (x2, y, z2) can be represented as Φ(x1, x2, y, z1, z2). Φ(x1, x2, y, z1, z2) is the input sensing position T. COIL (x1, y, z1) and sensing position R TMR (x2, y, z2) and output the sensed position R. TMR The induced position-dependent magnetic field function of the magnetic field strength at (x2, y, z2).

[0196] Sensing position T COIL (x1, y, z1) can also be a virtual position of the sensing circuit 110. Sensing position R TMR (x2, y, z2) can also be the virtual position of the magnetic sensor 130. At the sensing position T... COIL (x1, y, z1) corresponds to the actual position of the sensing circuit 110, and the sensing position R TMR When (x2, y, z2) corresponds to the actual position of the magnetic sensor 130, Φ(x1, x2, y, z1, z2) corresponds to the measured value as the actual sensing result.

[0197] In addition,Figure 4 In the example of FIG. 10, the induction circuit 110 is located at z = 0, and is scanned in the x-axis direction and the y-axis direction on the xy plane. In addition, the magnetic sensor 130 is located at z = z0, and is scanned in the x-axis direction and the y-axis direction on the xy plane. Thus, Φ(x1, x2, y, z1 = 0, z2 = z0) is obtained as a measurement value for each combination of x1, x2, and y. This measurement value is used as a boundary condition for Φ(x1, x2, y, z1, z2) as a magnetic field function related to the induction position.

[0198] In addition, Φ(x1, x2, y, z1, z2) is a harmonic function related to x1, y, and z1 corresponding to the induction position T COIL (x1, y, z1), and is a harmonic function related to x2, y, and z2 corresponding to the sensing position R TMR (x2, y, z2). Thus, Φ(x1, x2, y, z1, z2) satisfies the following equations (4-1) and (4-2) as a Laplace equation related to a multipath problem in a static or quasi-static field as a basic equation, respectively.

[0199] [Num 31]

[0200]

[0201] [Num 32]

[0202]

[0203] In a case where the z coordinate of the position P of the sample is greater than the z coordinate of the induction circuit 110 and is less than the z coordinate of the magnetic sensor 130, the general solution of each of the equations (4-1) and (4-2) is expressed by one of a term that increases exponentially in the z direction and a term that attenuates exponentially. Specifically, the general solution of the equation (4-1) and the general solution of the equation (4-2) are expressed as the following equations (4-3) and (4-4), respectively.

[0204] [Num 33]

[0205]

[0206] [Num 34]

[0207]

[0208] The combination of the equation (4-3) and the equation (4-4) is expressed as the following equation (4-5).

[0209] [Num 35]

[0210]

[0211] By applying z1=0 and the measured value at z2=z0 to formula (4-5) as a boundary condition, the following formula (4-6) is obtained.

[0212] [Num 36]

[0213]

[0214] By inverse Fourier transform of formula (4-6), the following formula (4-7) is obtained.

[0215] [Num 37]

[0216]

[0217] Here,

[0218] [Num 38]

[0219]

[0220] The Fourier transform image of the measured value. Thus, the induced position-dependent magnetic field function is expressed by the following formula (4-8).

[0221] [Num 39]

[0222]

[0223] It is assumed that by applying x2→x1(=x), y→y, and z2→z1(=z) to the induced position-dependent magnetic field function, the intensity of the magnetism sensed at (x, y, z) after the induced generated magnetic field component is sensed there. Also, it is assumed that the stronger the magnetism, the higher the magnetic susceptibility, and that an image representing the intensity of the magnetism represents the magnetic susceptibility distribution of the region including the interior of the sample. An imaging function for generating such an image is expressed by the following formula (4-9).

[0224] [Num 40]

[0225]

[0226] The imaging function represented by formula (4-9) is a function that inputs an imaging target position and outputs the image intensity of the imaging target position. The image intensity corresponds to the value output as the intensity of the magnetism from the induced position-dependent magnetic field function by inputting the imaging target position to the induced position-dependent magnetic field function.

[0227] For example, the information processing circuit 150 of the magnetic susceptibility distribution visualization device 100 calculates the induction position-dependent magnetic field function based on the sensing result as a measured value and Equation (4-8). Then, the information processing circuit 150 calculates the imaging function based on the induction position-dependent magnetic field function and Equation (4-9). Then, the information processing circuit 150 generates an image representing the magnetic susceptibility distribution based on the imaging function. Specifically, the information processing circuit 150 generates an image constituted by values output from the imaging function for each imaging target position as the image representing the magnetic susceptibility distribution.

[0228] Thus, the magnetic susceptibility distribution visualization device 100 can generate an image representing the magnetic susceptibility distribution with high precision using the induction position-dependent magnetic field function and the imaging function described above.

[0229] Figure 5 is a conceptual diagram representing still other examples of the induction position and the sensing position in the present embodiment. In the examples of Figure 4 In the examples of Figure 5 In the examples of Figure 5 Other conditions in the examples of Figure 4 are the same as those in the examples of

[0230] In the case where the z coordinate of P is smaller than the z coordinate of the induction circuit 110 and smaller than the z coordinate of the magnetic sensor 130 as in the examples of Figure 5 In the case where the z coordinate of P is smaller than the z coordinate of the induction circuit 110 and smaller than the z coordinate of the magnetic sensor 130 as in the examples of

[0231] [Numeral 41]

[0232]

[0233] Thus, in this case, the induction position-dependent magnetic field function is expressed by the following Equation (5-2).

[0234] [Numeral 42]

[0235]

[0236] In this case, the imaging function is expressed by the following Equation (5-3).

[0237] [Numeral 43]

[0238]

[0239] Figure 6 is a structural diagram representing a second example of the magnetic susceptibility distribution visualization device in the present embodiment. Figure 6The magnetic susceptibility distribution visualization device 200 shown includes multiple sensing circuits 210, sensing circuit support structures 220, multiple magnetic sensors 230, magnetic sensor support structures 240, information processing circuits 150, a display 160, and a sample stage 170. The magnetic susceptibility distribution visualization device 200 generates an image representing the magnetic susceptibility distribution of a sample placed on the sample stage 170, including its interior region.

[0240] Multiple sensing circuits 210 are with Figure 1 The circuit shown is of the same type as the sensing circuit 110. In Figure 6 In this example, multiple sensing circuits 210 are used instead of one sensing circuit 110. The multiple sensing circuits 210 do not move and sequentially generate the first magnetic field component. That is, the multiple sensing circuits 210 generate the first magnetic field component one by one or in predetermined units. Thus, like the sensing circuit 110, the multiple sensing circuits 210 can generate the first magnetic field component from each of the multiple sensing positions.

[0241] The induction circuit support structure 220 is a structure that fixes the plurality of induction circuits 210 in place. Figure 6 In the example, since multiple sensing circuits 210 do not move, it is not necessary to Figure 1 The induction circuit actuator 120 is shown.

[0242] Multiple magnetic sensors 230 are with Figure 1 The magnetic sensor shown is of the same type as the 130 magnetic sensor. In Figure 6 In this example, multiple magnetic sensors 230 are used instead of a single magnetic sensor 130. The multiple magnetic sensors 230 remain stationary and are capable of sensing magnetism at multiple sensing locations. That is, like the magnetic sensor 130, the multiple magnetic sensors 230 are capable of sensing magnetism at each of the multiple sensing locations.

[0243] The magnetic sensor support structure 240 is a structure that securely supports a plurality of magnetic sensors 230. Figure 6 In the example, since multiple magnetic sensors 230 do not move, it is not necessary to Figure 1 The magnetic sensor actuator 140 shown.

[0244] Figure 6 The magnetic susceptibility distribution visualization device 200 shown includes multiple sensing circuits 210 and multiple magnetic sensors 230, which can function as a visual representation of magnetic susceptibility distribution. Figure 1 The magnetic susceptibility distribution visualization device 100 shown has the same function as the sensing circuit 110 and the magnetic sensor 130. Therefore, the magnetic susceptibility distribution visualization device 200, like the magnetic susceptibility distribution visualization device 100, can sense the magnetism affected by the sample while changing the relative positional relationship between the sample and the sensing and sensing positions.

[0245] Thus, the magnetic susceptibility distribution visualizing apparatus 200 can acquire sufficient information about the magnetic susceptibility distribution of the region including the inside of the sample. Then, the magnetic susceptibility distribution visualizing apparatus 200 can calculate the induced position-dependent magnetic field function on the basis of the acquired sufficient information, and can generate an image representing the magnetic susceptibility distribution with high precision on the basis of the calculated induced position-dependent magnetic field function.

[0246] Further, the example of the magnetic susceptibility distribution visualizing apparatus 200 can be combined with the example of the magnetic susceptibility distribution visualizing apparatus 200. Figure 1 For example, both the mobile induction circuit 110 and the plurality of magnetic sensors 230 can be used, and both the plurality of induction circuits 210 and the mobile magnetic sensor 130 can be used. Figure 2

[0247] Figure 7 is a conceptual diagram of a first example of a human body scanner that uses the magnetic susceptibility distribution visualizing apparatus 200 shown in Figure 6

[0248] Figure 7 The human body scanner 300 shown in Figure 6 is provided with the information processing circuit 150 and the display 160 shown in

[0249] Since the knife has iron as a component, the magnetic susceptibility of the knife is high. On the other hand, the magnetic susceptibility of the aluminum case is low. Thus, it is assumed that the knife appears in the image representing the magnetic susceptibility distribution. That is, the human body scanner 300 can generate an image of the knife that the person has in the aluminum case by generating the image representing the magnetic susceptibility distribution.

[0250] Figure 7 is a conceptual diagram, the number and size of the plurality of induction circuits 210 and the number and size of the plurality of magnetic sensors 230 can be different from the example of Figure 7 Both a large number of smaller induction circuits 210 can be densely arranged, and a large number of smaller magnetic sensors 230 can be densely arranged. The same applies to other conceptual diagrams.

[0251] In the example of the magnetic susceptibility distribution visualizing apparatus 200 shown in Figure 7 ​​In this case, for example, the plurality of induction circuits 210 induce the first magnetic field component in a column by column manner in the vertical direction or the horizontal direction. By the first magnetic field component, the tool induces the second magnetic field component. Then, the plurality of magnetic sensors 230 sense the magnetism of the magnetic field containing the second magnetic field component. Thereby, the plurality of magnetic sensors 230 are able to sense the magnetism at the plurality of sensing positions for each of the plurality of induction positions. Then, the human body scanner 300 is able to generate the image of the tool with high precision based on the sensing results.

[0252] Specifically, one column of the plurality of induction circuits 210 in the vertical direction or the horizontal direction functions as the induction circuit 110 shown in Figure 3 the same as the wire shown in the induction circuit 110. It is assumed that the basic equation shown in Expression (2-1) and Expression (2-2) or the like holds. Thus, by using the method explained above, the induction position dependent magnetic field function and the imaging function shown in Expression (2-8) and Expression (2-9) can be derived. Figure 3

[0253] Thus, the human body scanner 300 is able to generate the image of the tool with high precision based on the induction position dependent magnetic field function and the imaging function shown in Expression (2-8) and Expression (2-9). In particular, the aluminum case does not pass through terahertz waves and microwaves or the like. The human body scanner 300 is able to generate the image of the tool in such an aluminum case with high precision.

[0254] Further, the plurality of induction circuits 210 can also induce the first magnetic field component in a column by column manner or in a prescribed unit, not in a column by column manner, in the vertical direction or the horizontal direction. In this case, a method of the same kind as the method using Figure 3 the method explained above can be used to derive the induction position dependent magnetic field function and the imaging function different from Expression (2-8) and Expression (2-9). The human body scanner 300 can also generate the image of the tool based on such an induction position dependent magnetic field function and the imaging function.

[0255] Figure 8 is a conceptual diagram showing the induction circuit 210. Figure 8 The induction circuit 210 shown in Figure 7 corresponds to each of the plurality of induction circuits 210 shown in

[0256] Figure 9 is a conceptual diagram showing the magnetic sensor 230. Figure 9 The magnetic sensor 230 shown in Figure 7 corresponds to each of the plurality of magnetic sensors 230 shown in​

[0257] Figure 10 is a conceptual diagram showing a specific configuration of the magnetic sensor 230. As described above, the magnetic sensor 230 is constituted of, for example, a TMR element. Figure 9

[0258] In the TMR element, an insulating film is sandwiched by magnetic films having a thickness of 10 nm to 100 nm or so. More specifically, the TMR element is constituted of a soft magnetic layer 231, a tunnel layer 232, and a PIN layer (magnetization fixed layer) 233, which are multiple thin films. The soft magnetic layer 231 is a magnetic film whose direction of magnetization varies depending on the direction of magnetization of the outside. The PIN layer 233 is a magnetic film whose direction of magnetization does not vary. Further, the tunnel layer 232 is an insulating film.

[0259] The resistance differs between a case where the direction of magnetization in the soft magnetic layer 231 is the same as the direction of magnetization in the PIN layer 233 and a case where these directions are different. The variation in the resistance is used to sense a magnetic field component.

[0260] The magnetic sensor 230 senses and measures a magnetic field component using the characteristics described above, for example. Further, the magnetic sensor 230 is not limited to the example described above constituted of a TMR element, but can be constituted of other elements such as a GMR element, a SQUID element, or a MI element.

[0261] Figure 11 is a conceptual diagram showing a second example of a human scanner using the magnetic susceptibility distribution visualization device 200 shown in Figure 6 Figure 11 The human scanner 400 shown in Figure 7 is basically the same as the human scanner 300 shown in

[0262] More specifically, the multiple induction circuits 210 are included in one of the two walls, and the multiple magnetic sensors 230 are included in the other of the two walls. During the person is positioned between the two walls, the first magnetic field component is induced from each of the multiple induction positions by the multiple induction circuits 210, and the magnetism is sensed at the multiple sensing positions by the multiple magnetic sensors 230. Thereby, the human scanner 400 can generate an image of the knife that the person has in the aluminum box without being noticed by the person.

[0263] Figure 12 is a conceptual diagram showing a third example of a human scanner using the magnetic susceptibility distribution visualization device 200 shown in Figure 6 Figure 12 The human scanner 500 shown in​​​Figure 11 The human body scanner 500 is identical to the one shown in the diagram 400, but it includes multiple combined circuits 310 that combine multiple sensing circuits 210 with multiple magnetic sensors 230. Specifically, each combined circuit 310 includes one sensing circuit 210 and one magnetic sensor 230. Furthermore, the multiple combined circuits 310 are housed within a single wall.

[0264] In other words, the multiple magnetic sensors 230 are located on the same side as the multiple sensing circuits 210 relative to the person corresponding to the sample. Therefore, the sensing position-related magnetic field function and imaging function shown, for example, in equations (3-2) and (3-3) can be applied. Moreover, the human body scanner 500 can generate images of the tool with high precision.

[0265] Furthermore, in the case where a first magnetic field component is induced by one column in the vertical or horizontal direction in multiple combination circuits 310, magnetism can also be sensed by multiple columns other than that column. Thus, in the combination circuit 310, excessive magnetism is suppressed due to the first magnetic field component induced by itself.

[0266] Figure 13 This is a conceptual diagram representing the combinational circuit 310. (For example...) Figure 13 Thus, the combination circuit 310 includes a sensing circuit 210 and a magnetic sensor 230. Specifically, the sensing circuit 210 is a coil. The magnetic sensor 230 is composed of a TMR element and is included inside the coil. Therefore, the combination circuit 310 is capable of generating a first magnetic field component and sensing the magnetism in a magnetic field containing a second magnetic field component.

[0267] Figure 14 It means to use Figure 6 A conceptual diagram of the fourth example of a human body scanner of the magnetic susceptibility distribution visualization device 200 shown. Figure 14 The human body scanner 600 shown is basically the same as Figure 12 The human body scanner 500 shown is the same, but the multiple combination circuits 310 of the human body scanner 600 are included on the ground.

[0268] and Figure 12 Similarly, in this example, multiple magnetic sensors 230 are located on the same side as multiple sensing circuits 210 relative to the person corresponding to the sample. Therefore, the sensing position-related magnetic field function and imaging function shown, for example, in equations (3-2) and (3-3) can be applied. Moreover, the human body scanner 600 can generate images of the tool with high precision.

[0269] Figure 15 It means to use Figure 6 A conceptual diagram of the fifth example of a human body scanner of the magnetic susceptibility distribution visualization device 200 shown. Figure 15The human body scanner 700 shown is basically the same as Figure 12 The human body scanner 700 shown is the same, but the multiple combination circuits 310 of the human body scanner 700 are included in the post. The post can also be a barrier bar, etc.

[0270] exist Figure 15 For example, when a person passes near a pillar, multiple combination circuits 310 included in the pillar sequentially generate a first magnetic field component. Then, the multiple combination circuits 310 sense the magnetism. At this time, the magnetism can also be sensed by multiple combination circuits 310 other than the one that generates the first magnetic field component. The human body scanner 700 repeats these processes while the person is passing near the pillar.

[0271] Specifically, by moving one-dimensionally past a person in a direction orthogonal to the pillar, the magnetic sensor 230, included in the combination circuit 310 within the pillar, performs a one-dimensional scan of the person. Then, the data obtained from the magnetic sensor array, consisting of multiple magnetic sensors 230 arranged one-dimensionally within the pillar, is combined to obtain a two-dimensional image (two-dimensional sensing result).

[0272] For example, as a person passes near a pillar, the multiple combination circuits 310 can scan the person relatively on a plane. That is, the human body scanner 700 can sense a first magnetic field component from each of the multiple sensing positions on the plane, and can sense the magnetism of a magnetic field containing a second magnetic field component at each of the multiple sensing positions on the plane. Then, the human body scanner 700 can generate an image of a knife or other object held by the person in an aluminum box based on the sensing results.

[0273] For example, in use Figure 15 The direction of people's progress is used as a reference. Figure 4 In the y-axis direction, the y-coordinate of the sensing circuit 210 relative to the moving person coincides with the y-coordinate of the magnetic sensor 230. Furthermore, the magnetic sensor 230 is located on the same side as the sensing circuit 210 relative to the person corresponding to the sample. Therefore, the sensing position-related magnetic field function and the image function shown in equations (5-2) and (5-3) can be applied, for example.

[0274] Figure 16 It means to use Figure 6 A conceptual diagram of the sixth example of a human body scanner of the magnetic susceptibility distribution visualization device 200 shown. Figure 16 The human body scanner 800 shown is basically the same as Figure 15The human body scanner 700 is the same as shown, but the plurality of combination circuits 310 of the human body scanner 800 are included in a plurality of columns. Also, the human body scanner 800 senses the magnetism of the magnetic field including the second magnetic field component while the person passes between 2 of the plurality of columns. The human body scanner 800 senses the magnetism of the magnetic field including the second magnetic field component while the person passes between 2 of the plurality of columns.

[0275] The human body scanner 800 can also sense the first magnetic field component from the column of one of the 2 columns and sense the magnetism of the magnetic field including the second magnetic field component at the column of the other. At this time, the first magnetic field component can also be sensed one by one by the plurality of combination circuits 310 included in the column of one of the 2 columns. Thus, the human body scanner 800, like the human body scanner 300, can sense the first magnetic field component from each of a plurality of sensing positions on a plane and can sense the magnetism of the magnetic field including the second magnetic field component at each of a plurality of sensing positions on a plane.

[0276] Then, the human body scanner 800 can generate an image of a knife or the like that the person has in the aluminum box based on the sensing results.

[0277] In the example of Figure 16 , the plurality of combination circuits 310 are included in each column. However, the plurality of sensing circuits 210 can also be included in the column of one of a pair of columns and the plurality of magnetic sensors 230 can also be included in the column of the other.

[0278] For example, in Figure 16 , the person advances between 2 columns in a direction parallel to the center line between the 2 columns. In the case where the advancing direction of the person in this case is used as the y-axis direction of Figure 4 , the y coordinate of the relative sensing circuit 210 with respect to the advancing person coincides with the y coordinate of the magnetic sensor 230. In addition, the magnetic sensor 230 is located on the opposite side from the sensing circuit 210 with respect to the person corresponding to the sample. Therefore, the sensing position-dependent magnetic field function and the imaging function shown in, for example, Equations (4-8) and (4-9) can be applied.

[0279] In addition, the human body scanner 800 can also detect a knife or the like based on the generated image. Then, in the case where a knife or the like is detected, information indicating the position at which the knife or the like was detected or the position of the person having the knife or the like can also be notified to an external terminal or the like.

[0280] Figure 17 is an image indicating the detection of a knife or the like by Figure 16A conceptual diagram of an example of the information displayed by the human body scanner 800 to the external terminal. For example, the human body scanner 800 generates a plurality of images based on the sensing results obtained from the plurality of poles. Then, the human body scanner 800 detects a knife or the like based on each of the images, detects a position corresponding to the knife or the like. Then, the human body scanner 800 transmits information indicating the position corresponding to the knife or the like to the external terminal 1000.

[0281] The above-described operation can also be performed by the information processing circuit 150 or the like of the magnetic susceptibility distribution visualization device 200. For example, the information processing circuit 150 determines whether or not the detection target object is included in the object corresponding to the sample, and outputs information indicating the position of the detection target object or the object to the external terminal 1000 in a case where it is determined that the detection target object is included in the object. The external terminal 1000 receives the information indicating the position corresponding to the knife or the like as the detection target object, and displays the information as Figure 17

[0282] In addition, the above-described operation is not limited to being performed by the human body scanner 800, and can also be performed by the human body scanners 300, 400, 500, 600, 700, or any combination thereof, or the like.

[0283] Furthermore, the human body scanners 300, 400, 500, 600, 700, and 800 described above correspond to the magnetic susceptibility distribution visualization device 200, but can also be changed to correspond to the magnetic susceptibility distribution visualization device 100. That is, the mobile induction circuit 110 can also be used instead of the plurality of induction circuits 210, and the mobile magnetic sensor 130 can also be used instead of the plurality of magnetic sensors 230.

[0284] Figure 18 is a conceptual diagram of an example of a security inspection system using the magnetic susceptibility distribution visualization device 100 or 200 shown in Figure 1 Figure 6 is a conceptual diagram of an example of a security inspection system using the magnetic susceptibility distribution visualization device 100 or 200 shown in

[0285] For example, Figure 18 The security inspection system 900 shown in includes the magnetic susceptibility distribution visualization device 100 or 200. More specifically, the security inspection system 900 can also include the human body scanner 400 shown in Figure 11

[0286] ​​​Further, the security inspection system 900 is provided with a gas-phase chemical agent analysis device 910 and a pipe 920, and analyzes gasoline or toxic gas in real time. For example, a wall surface is formed with fine holes in one dimension or two dimensions, and the surrounding air is drawn into a plurality of channels. The drawn air is sent to the gas-phase chemical agent analysis device 910 via the pipe 920.

[0287] For example, the gas-phase chemical agent analysis device 910 is constituted by a gas chromatograph, a mass spectrometer, an ion mobility analysis device, or a combination of two or more of them, and can also be a gas classification detector. The gas-phase chemical agent analysis device 910 identifies (recognizes) the air sent to the gas-phase chemical agent analysis device 910 and analyzes the risk.

[0288] The gas-phase chemical agent analysis device 910 shares information on a person who possesses toxic gas or the like in a communication network as with a person who possesses a weapon such as a knife or a firearm. The gas-phase chemical agent analysis device 910 can report such dangerous person information to a crisis management countermeasure such as a police officer, or can reflect such dangerous person information in the instruction of an evacuation route for the surrounding citizens.

[0289] Further, Figure 18 is a conceptual diagram, the number and size of the holes connected to the gas-phase chemical agent analysis device 910 via the pipe 920 can also be different from Figure 18 the example. A smaller number of holes can be more densely formed.

[0290] In addition, the security inspection system 900 can also be a security gate. In addition, the above-described security inspection system 900 corresponds to the human body scanner 400, but can also be changed to correspond to the human body scanners 300, 500, 600, 700, or 800. For example, the gas-phase chemical agent analysis device 910 and the pipe 920 can be included only in a single wall, can be included in the ground, or can be included in a column.

[0291] Figure 19 is a flowchart showing the action of the magnetic susceptibility distribution visualization device (100, 200) in the embodiment.

[0292] For example, the induction circuit (110, 210) induces a first magnetic field component from each of a plurality of induction positions that are determined as a plurality of positions with respect to the object on the outside of the object (S101).

[0293] Then, the magnetic sensor (130, 230) senses magnetism in a magnetic field including a second magnetic field component induced from the object by the first magnetic field component at each of a plurality of sensing positions that are determined as a plurality of positions with respect to the object on the outside of the object (S102). Thereby, the magnetic sensor (130, 230) senses magnetism at the plurality of sensing positions for each of the plurality of induction positions.

[0294] Then, the information processing circuit (150) acquires the magnetic sensing result, generates an image representing the magnetic susceptibility distribution of the region of the object including the inside based on the sensing result (S103). Then, for example, the information processing circuit (150) displays the image on the display (160) (S104). Alternatively, the information processing circuit (150) can print the image or transmit the image to another device.

[0295] The information processing circuit (150) calculates the induced position-dependent magnetic field function using the sensing result as a boundary condition when generating the image. The induced position-dependent magnetic field function is a function that inputs a virtual induced position and a virtual sensing position of the magnetic field of the first magnetic field component and outputs an intensity of the magnetic field at the virtual sensing position.

[0296] Then, the information processing circuit (150) calculates the imaging function. The imaging function is a function that inputs an imaging target position and outputs an image intensity of the imaging target position, and is a function determined based on the intensity output from the induced position-dependent magnetic field function by inputting the imaging target position to the induced position-dependent magnetic field function as the virtual induced position and the virtual sensing position. Then, the information processing circuit (150) generates the image based on the imaging function.

[0297] Thus, the magnetic susceptibility distribution visualization device (100, 200) can generate an image representing the magnetic susceptibility distribution of the region of the object including the inside with high precision from the magnetic sensing result based on a variety of combinations of each of the induced positions based on a plurality of induced positions and each of the sensing positions of a plurality of sensing positions.

[0298] For example, the information processing circuit (150) can also calculate a solution of a Laplace equation satisfied by the induced position-dependent magnetic field function as the induced position-dependent magnetic field function using the sensing result as a boundary condition. Thus, the magnetic susceptibility distribution visualization device (100, 200) can appropriately derive the induced position-dependent magnetic field function based on the sensing result and the Laplace equation related to a multi-path problem in a static or quasi-static field.

[0299] In addition, for example, the information processing circuit (150) can also calculate a limit value of the induced position-dependent magnetic field function as the imaging function by performing a limit operation on the induced position-dependent magnetic field function such that the virtual induced position and the virtual sensing position input to the induced position-dependent magnetic field function tend toward the imaging target position. Thus, the magnetic susceptibility distribution visualization device (100, 200) can appropriately derive the imaging function based on the induced position-dependent magnetic field function.

[0300] Further, for example, the plurality of sensing positions can also be determined on a second plane which is the same as or different from the first plane. In other words, the plurality of sensing positions can also be determined on the first plane on which the plurality of induction positions are determined or on a second plane which is different from the first plane. The second plane can also be a plane which is parallel to the first plane.

[0301] Thus, the magnetic susceptibility distribution visualization device (100, 200) can suppress an increase in the configuration space of the induction circuit (110, 210) and the magnetic sensor (130, 230). Further, the magnetic susceptibility distribution visualization device (100, 200) can suppress complication of the operation processing.

[0302] Further, for example, the plurality of sensing positions can also be located on the same side as the plurality of induction positions with respect to the object. Thus, the magnetic susceptibility distribution visualization device (100, 200) can sense the magnetism at each of the plurality of sensing positions on the same side as the plurality of induction positions with respect to the object. Thus, the magnetic susceptibility distribution visualization device (100, 200) can suppress the influence of the first magnetic field component induced by the induction circuit (110, 210) when sensing the magnetism at each of the plurality of sensing positions.

[0303] Further, for example, the plurality of sensing positions can also be located on the same side as the plurality of induction positions with respect to the object. Thus, the magnetic susceptibility distribution visualization device (100, 200) can sense the magnetism at each of the plurality of sensing positions on the same side as the plurality of induction positions with respect to the object. Thus, the magnetic susceptibility distribution visualization device (100, 200) can suppress the influence of the first magnetic field component induced by the induction circuit (110, 210) when sensing the magnetism at each of the plurality of sensing positions.

[0304] Further, for example, the induction circuit (110, 210) can also be moved to each of the plurality of induction positions to induce the first magnetic field component from each of the plurality of induction positions. Further, the magnetic sensor (130, 230) can also be moved to each of the plurality of sensing positions to sense the magnetism at each of the plurality of sensing positions.

[0305] Thus, the magnetic susceptibility distribution visualization device (100, 200) can apply one induction circuit (110, 210) for the plurality of induction positions and one magnetic sensor (130, 230) for the plurality of sensing positions. Thus, the magnetic susceptibility distribution visualization device (100, 200) can suppress an increase in resource costs.

[0306] In addition, for example, the induction circuit (110, 210) can also be constituted by a plurality of induction circuits (110, 210) arranged at a plurality of induction positions. In addition, the magnetic sensor (130, 230) can also be constituted by a plurality of magnetic sensors (130, 230) arranged at a plurality of sensing positions.

[0307] Thus, the magnetic susceptibility distribution visualization device (100, 200) can induce the magnetic field component generated from each of the plurality of induction positions without moving the induction circuit (110, 210) and the magnetic sensor (130, 230), and can sense the magnetism at each of the plurality of sensing positions. Thus, the magnetic susceptibility distribution visualization device (100, 200) can acquire the sensing results corresponding to the plurality of induction positions and the plurality of sensing positions at high speed.

[0308] Further, it is not limited to a one-to-one correspondence between the plurality of induction circuits (110, 210) and the plurality of induction positions, and two or more of the plurality of induction circuits (110, 210) can correspond to one induction position (region). In addition, it is not limited to a one-to-one correspondence between the plurality of magnetic sensors (130, 230) and the plurality of sensing positions, and two or more of the plurality of magnetic sensors (130, 230) can correspond to one sensing position (region).

[0309] In addition, for example, the plurality of induction circuits (110, 210) can be arranged on a first plane. In addition, the plurality of magnetic sensors (130, 230) can be arranged on a second plane that is the same as or different from the first plane. In other words, the plurality of magnetic sensors (130, 230) can be arranged on the first plane on which the plurality of induction circuits (110, 210) are arranged or on a second plane that is different from the first plane. The second plane can also be a plane parallel to the first plane.

[0310] Thus, the magnetic susceptibility distribution visualization device (100, 200) can acquire the sensing results corresponding to the plurality of induction positions on the first plane and the plurality of sensing positions on the second plane at high speed.

[0311] In addition, for example, the plurality of induction circuits (110, 210) can be arranged on a first straight line. In addition, the plurality of magnetic sensors (130, 230) can be arranged on a second straight line that is different from the first straight line. In other words, the plurality of magnetic sensors (130, 230) can be arranged on the first straight line on which the plurality of induction circuits (110, 210) are arranged or on a second straight line that is different from the first straight line. The second straight line can also be a straight line parallel to the first straight line.

[0312] Thus, the magnetic susceptibility distribution visualization device (100, 200) can reduce the space in which the plurality of induction circuits (110, 210) are arranged and the space in which the plurality of magnetic sensors (130, 230) are arranged.

[0313] In addition, for example, the object can also move. Also, the induction circuit (110, 210) can induce the first magnetic field component from the prescribed position at each of a plurality of times that are different from each other, thereby inducing the first magnetic field component from each of a plurality of induction positions that are determined in relation to the moving object. Also, the magnetic sensor (130, 230) can sense the magnetism at the prescribed position at each of a plurality of times that are different from each other, thereby sensing the magnetism at each of a plurality of sensing positions that are determined in relation to the moving object.

[0314] Thus, the magnetic susceptibility distribution visualization device (100, 200) can induce the magnetic field component from each of a plurality of induction positions without configuring a large number of induction circuits (110, 210) and a large number of magnetic sensors (130, 230), and can sense the magnetism at each of a plurality of sensing positions without moving the induction circuit (110, 210) and the magnetic sensor (130, 230).

[0315] In addition, for example, the induction circuit (110, 210) can also be included in the first wall. Also, the magnetic sensor (130, 230) can also be included in a second wall that is the same as or different from the first wall. In other words, the magnetic sensor (130, 230) can also be included in the first wall that includes the induction circuit (110, 210) or a second wall that is different from the first wall. The second wall can also be a wall that faces the first wall. In addition, for example, the induction circuit (110, 210) and the magnetic sensor (130, 230) can also be included in the ground.

[0316] In addition, for example, the induction circuit (110, 210) can also be included in the first column. Also, the magnetic sensor (130, 230) can also be included in a second column that is the same as or different from the first column. In other words, the magnetic sensor (130, 230) can also be included in the first column that includes the induction circuit (110, 210) or a second column that is different from the first column.

[0317] Through these, the induction circuit (110, 210) and the magnetic sensor (130, 230) are integrated into the environment. Thus, the magnetic susceptibility distribution visualization device (100, 200) can generate the image representing the magnetic susceptibility distribution without being noticed by people.

[0318] In addition, for example, in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual sensing position can also be expressed as (y1, z1). The virtual sensing position can also be expressed as (x, y2, z2). The z coordinate of the position of the presence sensing circuit (110, 210) can also be determined as 0. The z coordinate of the position of the magnetic sensor (130, 230) can also be determined as z0. In a case where the plurality of sensing positions are located on the same side as the plurality of sensing positions with respect to the object, the sensing position-dependent magnetic field function can also be determined by the following equation.

[0319] [Equation 44]

[0320]

[0321] Here,

[0322] [Equation 45]

[0323]

[0324] The Fourier transform image representing the sensing result. k x , k y1 , and k y2 are wave numbers related to x, y1, and y2, respectively. In addition, the imaging function can also be determined by the following equation.

[0325] [Equation 46]

[0326]

[0327] Thus, the magnetic susceptibility distribution visualization device (100, 200) can generate an image representing a magnetic susceptibility distribution with high precision using the sensing position-dependent magnetic field function expressed by the above equation and the imaging function expressed by the above equation.

[0328] In addition, for example, in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual sensing position can also be expressed as (y1, z1). The virtual sensing position can also be expressed as (x, y2, z2). The z coordinate of the position of the presence sensing circuit (110, 210) can also be determined as 0. The z coordinate of the position of the magnetic sensor (130, 230) can also be determined as z0. In a case where the plurality of sensing positions are located on the same side as the plurality of sensing positions with respect to the object, the sensing position-dependent magnetic field function can also be determined by the following equation.

[0329] [Equation 47]

[0330]

[0331] Here,

[0332] [Equation 48]

[0333]

[0334] a Fourier transform image representing a sensing result. k x , k y1 , and k y2 are wave numbers related to x, y1, and y2, respectively. In addition, the imaging function can also be determined by the following equation.

[0335] [Num 49]

[0336]

[0337] Thus, the magnetic susceptibility distribution visualization device (100, 200) can use the induced position-dependent magnetic field function expressed by the above equation and the imaging function expressed by the above equation to generate an image representing the magnetic susceptibility distribution with high precision.

[0338] In addition, for example, in a three-dimensional space composed of x coordinates, y coordinates, and z coordinates, the virtual induced position can also be expressed as (x1, y, z1). The virtual sensing position can also be expressed as (x2, y, z2). The z coordinate of the position where the induction circuit (110, 210) exists can also be determined as 0. The z coordinate of the position where the magnetic sensor (130, 230) exists can also be determined as z0. In the case where the plurality of sensing positions are located on the side opposite to the plurality of induced positions with respect to the object, the induced position-dependent magnetic field function can also be determined by the following equation.

[0339] [Num 50]

[0340]

[0341] Here,

[0342] [Num 51]

[0343]

[0344] a Fourier transform image representing a sensing result. k x , k y1 , and k y2 are wave numbers related to x, y1, and y2, respectively. In addition, the imaging function can also be determined by the following equation.

[0345] [Num 52]

[0346]

[0347] Thus, the magnetic susceptibility distribution visualizing apparatus (100, 200) can generate an image representing the magnetic susceptibility distribution with high precision using the induced position-dependent magnetic field function expressed by the above-described formula and the imaging function expressed by the above-described formula.

[0348] In addition, for example, in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual induced position can also be expressed by (x1, y, z1). The virtual sensing position can also be expressed by (x2, y, z2). The z coordinate of the position where the induced circuit (110, 210) exists can also be determined as 0. The z coordinate of the position where the magnetic sensor (130, 230) exists can also be determined as z0. In a case where the plurality of sensing positions are located on the same side as the plurality of induced positions with respect to the object, the induced position-dependent magnetic field function can also be determined by the following formula.

[0349] [Num. 53]

[0350]

[0351] Here,

[0352] [Num. 54]

[0353]

[0354] The Fourier transform image representing the sensing result. k x , k y1 , and k y2 are wave numbers related to x, y1, and y2, respectively. In addition, the imaging function can also be determined by the following formula.

[0355] [Num. 55]

[0356]

[0357] Thus, the magnetic susceptibility distribution visualizing apparatus (100, 200) can generate an image representing the magnetic susceptibility distribution with high precision using the induced position-dependent magnetic field function expressed by the above-described formula and the imaging function expressed by the above-described formula.

[0358] In addition, for example, the information processing circuit (150) can determine whether or not the object includes the detection target object on the basis of the image, output information representing the position of the detection target object or the object to the external terminal (1000) in a case where it is determined that the object includes the detection target object. Thus, the magnetic susceptibility distribution visualizing apparatus (100, 200) can notify the position of a specific detection target object or the position of an object including a specific detection target object.

[0359] The above describes the manner in which the magnetic susceptibility distribution visualization device is implemented, but the manner in which the magnetic susceptibility distribution visualization device is implemented is not limited to the embodiments. The embodiments can be implemented with modifications that can be conceived by those skilled in the art, and the plurality of structural elements in the embodiments can be combined arbitrarily. For example, the processing performed by a specific structural element in the embodiments can be performed by another structural element instead of the specific structural element. In addition, the order of the plurality of processes can be changed, and the plurality of processes can be executed in parallel.

[0360] In addition, the magnetic susceptibility distribution visualization method including the steps performed by the structural elements of the magnetic susceptibility distribution visualization device can be performed by any device or system. For example, a part or all of the magnetic susceptibility distribution visualization method can be performed by a computer provided with a processor, a memory, an input / output circuit, and the like. At this time, the magnetic susceptibility distribution visualization method can be performed by executing a program for causing the computer to perform the magnetic susceptibility distribution visualization method by the computer.

[0361] In addition, the above-described program can be recorded in a non-transitory computer-readable recording medium.

[0362] In addition, the structural elements of the magnetic susceptibility distribution visualization device can be constituted by a dedicated hardware, a general-purpose hardware that executes the above-described program and the like, or a combination thereof. In addition, the general-purpose hardware can be constituted by a memory in which the program is recorded and a general-purpose processor that reads out the program from the memory and executes the program, and the like. Here, the memory can be a semiconductor memory or a hard disk, and the general-purpose processor can be a CPU or the like.

[0363] In addition, the dedicated hardware can be constituted by a memory and a dedicated processor, and the like. For example, the dedicated processor can execute the above-described magnetic susceptibility distribution visualization method with reference to the memory in which the measurement data is recorded.

[0364] In addition, the structural elements of the magnetic susceptibility distribution visualization device can be circuits. These circuits can be constituted as one circuit as a whole, or can be different circuits. In addition, these circuits can correspond to a dedicated hardware, or a general-purpose hardware that executes the above-described program and the like.

[0365] In addition, the magnetic susceptibility distribution visualization device can be implemented as an image generation device. In addition, the magnetic susceptibility distribution visualization device can be a security inspection device such as a human body scanner, or can be included in a security inspection device. In addition, the example of the human body scanner is shown in the above, but the application example is not limited to the above example. The application example can be used for inspection of a circuit, or inspection of a reinforced structure. In addition, the application example can be used for medical diagnosis in which a human body is inspected using a contrast medium containing a magnetic substance.

[0366] In addition, in the above description, a magnetic field is used, but the concept of the present disclosure can be applied to all fields that satisfy Laplace's equation related to a multipath problem in a static or quasi-static field. Here, a quasi-static field is a field that is substantially static, and can also be an electromagnetic field of 100 kHz or less that can be considered to have no wave properties, or the like. Specifically, an electric field can also be used instead of a magnetic field, a temperature field can also be used, and a pressure field can also be used.

[0367] Thus, the above-described magnetic susceptibility distribution visualization device can also be expressed as an external field response distribution visualization device. For example, the external field response distribution visualization device generates an image representing an external field response distribution that is a distribution of a response to an external field. In addition, the above-described magnetic sensor can also be a sensor that senses the intensity of a field. Also, the intensity of the field can be used instead of the intensity of the magnetism. In addition, the induced position-dependent magnetic field function can be expressed as an induced position-dependent field function.

[0368] That is, the magnetic field in the above description can be replaced with "field", and the magnetic susceptibility distribution can be replaced with an external field response distribution. For example, the induction circuit induces a first field component from a plurality of induction positions. Thereby, a second field component is induced from the object. The sensor senses the intensity of the field including the second field component at each of the plurality of sensing positions. Then, the information processing circuit acquires the sensing result of the intensity, and generates an image representing an external field response distribution of a region including the inside of the object based on the sensing result.

[0369] At this time, the information processing circuit uses the sensing result as a boundary condition, calculates an induced position-dependent field function, and calculates an imaging function based on the induced position-dependent field function. Then, the information processing circuit generates an image based on the imaging function. Thereby, the external field response distribution visualization device can generate an image representing an external field response distribution of a region including the inside of the object with high precision.

[0370] Industrial applicability

[0371] One embodiment of the present disclosure is useful for a magnetic susceptibility visualization device that generates an image representing a magnetic susceptibility distribution, and can be applied to a magnetic field diagnosis device, an inspection of an electronic component, a seismic resistance inspection of a reinforced structure, a medical diagnosis, and a safety inspection system, and the like.

[0372] Explanation of reference signs

[0373] 100, 200: magnetic susceptibility distribution visualization device (external field response distribution visualization device);

[0374] 110, 210: induction circuit;

[0375] 120: induction circuit actuator;

[0376] 130, 230: magnetic sensor (sensor)

[0377] 140: magnetic sensor actuator (sensor actuator)

[0378] 150: information processing circuit

[0379] 160: display

[0380] 170: sample stage

[0381] 220: inductive circuit support structure

[0382] 231: soft magnetic layer

[0383] 232: tunnel layer

[0384] 233: PIN layer (magnetization fixed layer)

[0385] 240: magnetic sensor support structure (sensor support structure)

[0386] 300, 400, 500, 600, 700, 800: human body scanner

[0387] 310: combination circuit

[0388] 900: security inspection system

[0389] 910: gas phase chemical agent analysis device

[0390] 920: tube

[0391] 1000: external terminal

Claims

1. An external field response distribution visualization apparatus that generates an image representing a distribution of responses to an external field, i.e., an external field response distribution, characterized by, Possessing: one or more induction circuits that sequentially induce a first field component from each of a plurality of actual induction positions that are determined as a plurality of positions relative to an object on an outside of the object; one or more sensors that sense an intensity of a field including a second field component induced from the object due to the first field component sequentially induced from each of the plurality of actual induction positions, at each of a plurality of actual sensing positions that are determined as a plurality of positions relative to the object on the outside of the object, thereby sensing the intensity of the field at the plurality of actual sensing positions for each of the plurality of actual induction positions; and an information processing circuit that acquires a sensing result of the intensity of the field, generates the image representing the outside field response distribution of a region including an inside of the object based on the sensing result, the information processing circuit derives an induction position-dependent field function that inputs a virtual induction position and a virtual sensing position and outputs the intensity of the field at the virtual sensing position using the sensing result as a boundary condition, the information processing circuit derives an imaging function that is a function that inputs an imaging target position and outputs an image intensity of the imaging target position, is a function determined based on an intensity output from the induction position-dependent field function by inputting the imaging target position to the induction position-dependent field function as the virtual induction position and the virtual sensing position, the information processing circuit generates the image based on the imaging function.

2. The outside field response distribution visualizing apparatus according to claim 1, wherein the information processing circuit derives the induction position-dependent field function by deriving a solution of a Laplace equation that the induction position-dependent field function satisfies using the sensing result as the boundary condition.

3. The outside field response distribution visualizing apparatus according to claim 1 or 2, wherein the information processing circuit derives the imaging function corresponding to a limit value of the induction position-dependent field function by performing a limit operation on the induction position-dependent field function such that the virtual induction position and the virtual sensing position input to the induction position-dependent field function tend toward the imaging target position.

4. The outside field response distribution visualizing apparatus according to claim 1 or 2, wherein the plurality of actual induction positions are determined on a first plane, the plurality of actual sensing positions are determined on a second plane that is the same as or different from the first plane.

5. The outside field response distribution visualizing apparatus according to claim 1 or 2, wherein the plurality of actual sensing positions are located on a side opposite to the plurality of actual induction positions with respect to the object.

6. The outside field response distribution visualizing apparatus according to claim 1 or 2, wherein the plurality of actual sensing positions are located on a side same as the plurality of actual induction positions with respect to the object.

7. The outside field response distribution visualizing apparatus according to claim 1 or 2, wherein The one or more induction circuits are moved to each of the plurality of actual induction positions, and one of the induction circuits induces the first field component from each of the plurality of actual induction positions, The one or more sensors are moved to each of the plurality of actual sensing positions, and one of the sensors senses the intensity of the field at each of the plurality of actual sensing positions.

8. The external field response distribution visualizing apparatus according to claim 1 or 2, wherein The one or more induction circuits are a plurality of induction circuits arranged at the plurality of actual induction positions, The one or more sensors are a plurality of sensors arranged at the plurality of actual sensing positions.

9. The external field response distribution visualizing apparatus according to claim 8, wherein The plurality of induction circuits are arranged on a first plane, The plurality of sensors are arranged on a second plane which is the same as or different from the first plane.

10. The external field response distribution visualizing apparatus according to claim 8, wherein The plurality of induction circuits are arranged on a first straight line, The plurality of sensors are arranged on a second straight line which is the same as or different from the first straight line.

11. The external field response distribution visualizing apparatus according to claim 1 or 2, wherein The object moves, The one or more induction circuits induce the first field component from a prescribed position at each of a plurality of times which are different from each other, thereby inducing the first field component from each of the plurality of actual induction positions which are determined relatively to the moving object, The one or more sensors sense the intensity of the field at a prescribed position at each of a plurality of times which are different from each other, thereby sensing the intensity of the field at each of the plurality of actual sensing positions which are determined relatively to the moving object.

12. The external field response distribution visualizing apparatus according to claim 1 or 2, wherein The one or more induction circuits are included in a first wall, The one or more sensors are included in a second wall which is the same as or different from the first wall.

13. The external field response distribution visualizing apparatus according to claim 1 or 2, wherein The one or more induction circuits and the one or more sensors are included in a ground.

14. The external field response distribution visualizing apparatus according to claim 1 or 2, wherein The one or more induction circuits are included in a first column, The one or more sensors are included in a second column which is the same as or different from the first column.

15. The external field response distribution visualizing apparatus according to claim 5, wherein in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual induction position is represented by (y1, z1), the virtual sensing position is represented by (x, y2, z2), a z coordinate of a position where the one or more induction circuits exist is determined to be 0, a z coordinate of a position where the one or more sensors exist is determined to be z0, and the induction position dependent field function is represented by ​ [Num 1] is determined, [Num 2] a Fourier transform image representing the sensing result, k x , k y1 and k y2 are wave numbers related to x, y1 and y2, respectively, the imaging function is determined using [Num 3] .

16. The external field response distribution visualization device according to claim 6, wherein in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual induction position is expressed by (yl, zl), the virtual sensing position is expressed by (x, y2, z2), the z coordinate of the position where the one or more induction circuits exist is determined to be 0, the z coordinate of the position where the one or more sensors exist is determined to be z0, the induction position-dependent field function is determined using [Num 4] , [Num 5] a Fourier transform image representing the sensing result, k x , k y1 and k y2 are wave numbers related to x, y1 and y2, respectively, the imaging function is determined using [Num 6] .

17. The external field response distribution visualization device according to claim 5, wherein in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual induction position is expressed by (xl, y, zl), the virtual sensing position is expressed by (x2, y, z2), the z coordinate of the position where the one or more induction circuits exist is determined to be 0, the z coordinate of the position where the one or more sensors exist is determined to be z0, the induction position-dependent field function is determined using [Num 7] , [Num 8] a Fourier transform image representing the sensing result, k x1 , k x2 and k y are wave numbers related to x1, x2 and y, respectively, the imaging function is determined using [Num 9] .

18. The external field response distribution visualization device according to claim 6, wherein in a three-dimensional space constituted by an x coordinate, a y coordinate, and a z coordinate, the virtual induction position is expressed by (xl, y, zl), the virtual sensing position is expressed by (x2, y, z2), the z coordinate of the position where the one or more induction circuits exist is determined to be 0, the z coordinate of the position where the one or more sensors exist is determined to be z0, the induction position-dependent field function is determined using [Num 10] , [Num 11] a Fourier transform image representing the sensing result, k x1 , k x2 and k y are wave numbers related to x1, x2 and y, respectively, the imaging function is determined using [Num 12] .

19. The external field response distribution visualization device according to claim 1 or 2, wherein the information processing circuit determines whether or not a detection target object is included in the object on the basis of the image, and outputs information indicating the position of the detection target object or the object to an external terminal in a case where it is determined that the detection target object is included in the object.

20. A method of visualizing an external field response distribution, generating an image representing a distribution of responses to an external field, an external field response distribution, characterized by, comprises the steps of: inducing, using one or more induction circuits, a first field component successively from each of a plurality of actual induction positions which are determined to be a plurality of positions with respect to the object from the outside of the object; sensing, using one or more sensors, the intensity of a field including a second field component induced from the object as a result of inducing the first field component successively from each of the plurality of actual induction positions, at each of a plurality of actual sensing positions which are determined to be a plurality of positions with respect to the object from the outside of the object, thereby sensing the intensity of the field at the plurality of actual sensing positions with respect to each of the plurality of actual induction positions; and acquiring a sensing result of the intensity of the field, and generating the image indicating the external field response distribution of a region including the inside of the object on the basis of the sensing result, ​ in a step of generating the image, using the sensing result as a boundary condition, deriving a sensing position dependent field function which inputs a virtual sensing position and a virtual induction position and outputs an intensity of the field at the virtual sensing position, deriving an imaging function which inputs an imaging object position and outputs an intensity of an image at the imaging object position, is a function determined based on an intensity output from the sensing position dependent field function by inputting the imaging object position to the sensing position dependent field function as the virtual sensing position and the virtual induction position, generating the image based on the imaging function.

Images