Scattering tomography apparatus and scattering tomography method

Abstract

The scattering tomography apparatus (100) includes: a transmitting antenna element (101) that transmits radio waves into the interior of an object; a receiving antenna element (102) that receives scattered waves of the radio waves outside the object; and an information processing circuit (103) that obtains a plurality of measurement results over multiple days and generates a reconstructed image based on the plurality of measurement results, the reconstructed image showing continuous elements inside the object. The information processing circuit (103) calculates a scattering field function for each of the plurality of measurement results, calculates an imaging function for each of the plurality of measurement results, generates a plurality of intermediate images for the plurality of measurement results, and generates a reconstructed image by calculating the minimum value of the image intensity at each position in the plurality of intermediate images through an "AND" operation.

Description

Technical Field

[0001] The present disclosure relates to a scattering tomography apparatus and the like that generate a reconstructed image showing elements inside an object by using scattered waves of radio waves. Background Art

[0002] As technologies related to a scattering tomography apparatus and the like that generate a reconstructed image showing elements inside an object by using scattered waves of radio waves, there are the technologies described in Patent Document 1, Patent Document 2, and Patent Document 3.

[0003] For example, in the technology described in Patent Document 1, a beam emitted from a microwave transmitter is incident on an inspection object, and the amplitude and phase of the scattered beam are detected by a microwave detector. Then, the distribution of the dielectric constant is calculated based on the output signal of the microwave detector, and thus tomography of the inspection object is performed.

[0004] (Prior Art Documents)

[0005] (Patent Documents)

[0006] Patent Document 1 Japanese Patent Application Laid-Open No. 62-66145

[0007] Patent Document 2 International Publication No. 2014 / 125815

[0008] Patent Document 3 International Publication No. 2015 / 136936 Summary of the Invention

[0009] Problems to be Solved by the Invention

[0010] However, it is not easy to generate a reconstructed image showing elements inside an object by using scattered waves of radio waves such as microwaves. Specifically, when the internal state of the object is known, for radio waves incident on the object, finding data measured (detected) as scattered waves is called a forward problem, and the forward problem is easy. However, when the measured data is known, finding the internal state of the object is called an inverse problem, and the inverse problem is not easy.

[0011] Moreover, even if it is possible to identify the presence of elements inside an object by using scattered waves, it is not easy to identify the characteristics of the elements. For example, it is not easy to identify whether the elements continuously exist inside the object. Specifically, when a persistent malignant tumor and other cells that randomly occur and disappear reflect radio waves in the same way, it is not easy to identify whether the elements inside the human body are malignant tumors or other cells by using scattered waves.

[0012] Therefore, the present disclosure provides a scattering tomography apparatus and the like that can generate a reconstructed image showing continuous elements inside an object by using scattered waves of radio waves.

[0013] Means for solving the problem

[0014] The scatter tomography apparatus according to one aspect of the present disclosure includes: a transmitting antenna element that transmits radio waves from the outside of an object to the inside of the object; a receiving antenna element that receives, outside the object, scattered waves of the radio waves transmitted from the transmitting antenna element to the inside of the object; and an information processing circuit that obtains a plurality of measurement results in a plurality of days by obtaining measurement results of the scattered waves each day in the plurality of days, and generates a reconstructed image based on the plurality of measurement results, the reconstructed image showing continuous elements inside the object. The information processing circuit performs the following operations: for each of the plurality of measurement results, uses the measurement result as a boundary condition to calculate a scattered field function, the scattered field function being input with the transmission position of the radio waves and the reception position of the scattered waves and outputting the amount of the scattered waves at the reception position; for each of the plurality of measurement results, calculates an imaging function, the imaging function being input with an imaging target position and outputting the image intensity at the imaging target position, and the imaging function being a function determined based on the amount output from the scattered field function by inputting the imaging target position as the transmission position and the reception position to the scattered field function; for each of the plurality of measurement results, generates an intermediate image based on the imaging function, thereby generating a plurality of intermediate images for the plurality of measurement results; and generates the reconstructed image by calculating the minimum value of the image intensity at each position in the plurality of intermediate images by an "AND" operation.

[0015] In addition, these general or specific aspects can be implemented by a system, a device, a method, an integrated circuit, a computer program, or a non-transitory recording medium such as a computer-readable CD-ROM, or can be implemented by any combination of a system, a device, a method, an integrated circuit, a computer program, and a recording medium.

[0016] Advantageous effects of the invention

[0017] According to one aspect of the present disclosure, it is possible to generate a reconstructed image showing continuous elements inside an object by using scattered waves of radio waves. Description of the drawings

[0018] Figure 1 It is a graph showing luteinizing hormone (progesterone) and other secretions during the menstrual cycle.

[0019] Figure 2A It is a graph showing the degree of cell proliferation (mitosis) of lobules with respect to the number of days in the menstrual cycle.

[0020] Figure 2B is a graph showing the degree of cell loss (apoptosis) relative to the number of days in the menstrual cycle.

[0021] Figure 3 is a conceptual diagram showing the concept of lobules and lactiferous ducts.

[0022] Figure 4 is a conceptual diagram showing an example in which the array antenna in the embodiment scans on a curved surface and measures scattering data.

[0023] Figure 5 is a conceptual diagram showing the timing measurement performed using the microwave mammography in the embodiment.

[0024] Figure 6 is a graph showing the timing data of the image intensity in the embodiment.

[0025] Figure 7 is a conceptual diagram showing the deviation of the measurement area in the embodiment.

[0026] Figure 8A is a diagram showing a display example of the image in the embodiment.

[0027] Figure 8B is a diagram showing a display example of a semi-transparent perspective image when looking at the inside of the breast in the embodiment from below the object upward.

[0028] Figure 8C is a diagram showing a display example of a semi-transparent perspective image when looking at the inside of the breast in the embodiment from the front of the object.

[0029] Figure 9A is a diagram showing a display example of the reconstructed image obtained from the measurement data on January 11 in Example 1.

[0030] Figure 9B is a diagram showing a display example of the reconstructed image obtained from the measurement data on January 18 in Example 1.

[0031] Figure 9C is a diagram showing a display example of the reconstructed image obtained from the measurement data on January 25 in Example 1.

[0032] Figure 9D is a diagram showing a display example of the reconstructed image obtained from the measurement data on February 1 in Example 1.

[0033] Figure 9E is a diagram showing a display example of the tumor probability image in Example 1.

[0034] Figure 10A is a diagram showing a display example of the reconstructed image obtained from the measurement data on June 1 in Example 2.

[0035] Figure 10B It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 5 in Example 2.

[0036] Figure 10C It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 8 in Example 2.

[0037] Figure 10D It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 12 in Example 2.

[0038] Figure 10E It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 15 in Example 2.

[0039] Figure 10F It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 19 in Example 2.

[0040] Figure 10G It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 22 in Example 2.

[0041] Figure 10H It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 26 in Example 2.

[0042] Figure 10I It is a diagram showing a display example of the tumor probability image in Example 2.

[0043] Figure 11A It is a diagram showing a display example of a reconstructed image obtained from the measurement data on October 23 in Example 3.

[0044] Figure 11B It is a diagram showing a display example of a reconstructed image obtained from the measurement data on October 30 in Example 3.

[0045] Figure 11C It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 6 in Example 3.

[0046] Figure 11D It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 13 in Example 3.

[0047] Figure 11E It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 20 in Example 3.

[0048] Figure 11F It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 27 in Example 3.

[0049] Figure 11G It is a figure showing a display example of a reconstructed image obtained from the measurement data on December 4 in Example 3.

[0050] Figure 11H It is a figure showing a display example of a reconstructed image obtained from the measurement data on December 11 in Example 3.

[0051] Figure 11I It is a figure showing a display example of a tumor probability image in Example 3.

[0052] Figure 12A It is a figure showing a display example of a reconstructed image obtained from the composite data of the measurement data of a cancer patient in Example 4 and the measurement data of a healthy person on February 26.

[0053] Figure 12B It is a figure showing a display example of a reconstructed image obtained from the composite data of the measurement data of a cancer patient in Example 4 and the measurement data of a healthy person on February 5.

[0054] Figure 12C It is a figure showing a display example of a reconstructed image obtained from the composite data of the measurement data of a cancer patient in Example 4 and the measurement data of a healthy person on February 12.

[0055] Figure 12D It is a figure showing a display example of a reconstructed image obtained from the composite data of the measurement data of a cancer patient in Example 4 and the measurement data of a healthy person on February 19.

[0056] Figure 12E It is a figure showing a display example of a tumor probability image in Example 4.

[0057] Figure 13 It is a block diagram showing the basic configuration of the scatter tomography apparatus in the embodiment.

[0058] Figure 14 It is a flowchart showing the basic operation of the scatter tomography apparatus in the embodiment.

[0059] Figure 15 It is a conceptual diagram showing the specific configuration of the scatter tomography apparatus in the embodiment. Detailed implementation mode

[0060] The scattering tomography device according to one aspect of the present disclosure includes: a transmitting antenna element that transmits radio waves from the outside of an object to the inside of the object; a receiving antenna element that receives, outside the object, scattered waves of the radio waves transmitted from the transmitting antenna element to the inside of the object; and an information processing circuit that obtains a plurality of measurement results over a plurality of days by obtaining measurement results of the scattered waves each day over the plurality of days, generates a reconstructed image based on the plurality of measurement results, the reconstructed image showing continuous elements inside the object, and the information processing circuit performs the following operations: for each of the plurality of measurement results, uses the measurement result as a boundary condition to calculate a scattered field function, the scattered field function being input with the transmission position of the radio waves and the reception position of the scattered waves and outputting the amount of the scattered waves at the reception position, for each of the plurality of measurement results, calculates an imaging function, the imaging function being input with an imaging target position and outputting the image intensity at the imaging target position, and the imaging function is a function determined based on the amount output from the scattered field function by inputting the imaging target position as the transmission position and the reception position into the scattered field function, for each of the plurality of measurement results, generates an intermediate image based on the imaging function, thereby generating a plurality of intermediate images for the plurality of measurement results, and generates the reconstructed image by calculating the minimum value of the image intensity at each position in the plurality of intermediate images through an AND operation.

[0061] Accordingly, the scattering tomography device can calculate an intermediate image that can show elements inside the object based on the scattered field function calculated using the measurement result of the scattered waves as a boundary condition. Thus, the scattering tomography device can generate a reconstructed image showing continuous elements inside the object from a plurality of intermediate images obtained using a plurality of measurement results over a plurality of days.

[0062] Therefore, the scattering tomography device can use the scattered waves of radio waves to generate a reconstructed image showing continuous elements inside the object. Accordingly, for example, it is possible to use the scattered waves to identify whether the elements inside the human body are continuous malignant tumors or other cells that occur randomly and disappear.

[0063] For example, the information processing circuit generates the reconstructed image by PN(r) = b1(r) ∧ b2(r) ∧ … ∧ bN(r), where PN(r) represents the reconstructed image, r represents a position, N represents the number of the plurality of intermediate images, bi related to i from 1 to N represents the imaging function, and ∧ represents a logical AND.

[0064] Accordingly, the scattering tomography device can simply generate a reconstructed image through the logical AND of the intermediate images corresponding to the output of the imaging function.

[0065] Further, for example, the information processing circuit generates the intermediate image based on the imaging function and the diffusion coefficient. When generating the intermediate image, the larger the diffusion coefficient, the greater the spatial diffusion of the image intensity at the position of the imaging object in the intermediate image.

[0066] Accordingly, the scatter tomography device can diffuse the image intensity through the diffusion coefficient. Therefore, the scatter tomography device can suppress the disappearance of continuous elements from the reconstructed image due to position deviation in the measurement of scattered waves through the diffusion coefficient.

[0067] Further, the information processing circuit generates the reconstructed image through PN(r) = eνΔb1(r) ∧ eνΔb2(r) ∧ … ∧ eνΔbN(r), where PN(r) represents the reconstructed image, r represents the position, N represents the number of the plurality of intermediate images, bi related to i from 1 to N represents the imaging function, eνΔbi(r) related to i from 1 to N represents the intermediate image, ν represents the diffusion coefficient, Δ represents a two-dimensional Laplace operator corresponding to two directions in which position deviation occurs in the measurement of the scattered wave, and ∧ represents logical AND.

[0068] Accordingly, the scatter tomography device can appropriately diffuse the image intensity through the relational expression based on the method of probability theory.

[0069] Further, for example, the information processing circuit performs a Fourier transform on bi(r), multiplies the result of the Fourier transform by exp(−ν(kx2 + ky2)), and performs an inverse Fourier transform on the result after multiplying by exp(−ν(kx2 + ky2)) to calculate eνΔbi(r), where kx and ky of exp(−ν(kx2 + ky2)) represent two wave numbers corresponding to the two directions of bi.

[0070] Accordingly, the scatter tomography device can quickly and appropriately diffuse the image intensity.

[0071] Further, for example, the diffusion coefficient is determined as a value proportional to the mean square error of the measurement position of the scattered wave.

[0072] Accordingly, the diffusion coefficient can be determined according to the magnitude of the error of the measurement position. Thus, the scatter tomography device can appropriately diffuse the image intensity according to the magnitude of the error of the measurement position.

[0073] Further, for example, the diffusion coefficient is determined as a value equal to the mean square error of the measurement position of the scattered wave.

[0074] Accordingly, the diffusion coefficient can be simply determined according to the magnitude of the error in the measurement position. Then, the scatter tomography apparatus can appropriately diffuse the image intensity according to the magnitude of the error in the measurement position.

[0075] And, for example, the diffusion coefficient is determined to be 0.

[0076] Accordingly, the scatter tomography apparatus can simply generate a reconstructed image by performing a logical AND operation on the intermediate image corresponding to the output of the imaging function, in the same manner as in the case where the diffusion coefficient is not used.

[0077] And, for example, the diffusion coefficient is determined to be a value greater than 0.

[0078] Accordingly, the scatter tomography apparatus can appropriately diffuse the image intensity with a diffusion coefficient greater than 0. Therefore, the scatter tomography apparatus can suppress the disappearance of continuous elements from the reconstructed image due to position deviation in the measurement of scattered waves, by means of a diffusion coefficient greater than 0.

[0079] And, for example, in a three-dimensional space composed of an X coordinate, a Y coordinate, and a Z coordinate, the X coordinate and the Z coordinate of the position of the transmitting antenna element are the same as the X coordinate and the Z coordinate of the position of the receiving antenna element, respectively, and the scatter field function is determined by [Mathematical Formula 1],

[0080] [Mathematical Formula 1]

[0081]

[0082] x represents the X coordinate of the transmitting position and the receiving position, y1 represents the Y coordinate of the transmitting position, y2 represents the Y coordinate of the receiving position, z represents the Z coordinate of the transmitting position and the receiving position, k represents the wave number of the radio wave, kx, ky1, and ky2 in the scatter field function respectively represent the wave numbers related to x, y1, and y2 of the scatter field function, and a(kx, ky1, ky2) is determined by [Mathematical Formula 2],

[0083] [Mathematical Formula 2]

[0084]

[0085] I represents the index of the transmitting position and the receiving position where the transmitting antenna element and the receiving antenna element are located, xI represents the X coordinate of the transmitting position and the receiving position where the transmitting antenna element and the receiving antenna element are located, and zI represents the Z coordinate of the transmitting position and the receiving position where the transmitting antenna element and the receiving antenna element are located.

[0086] [Mathematical Formula 3]

[0087]

[0088] Indicates Fourier transform imaging related to y1, y2, and t of Φ(x, y1, y2, t) showing the measurement results in x, y1, y2, and t. t represents time, and the imaging function is determined by [Mathematical Formula 4].

[0089] [Mathematical Formula 4]

[0090]

[0091] In the imaging function, x, y, and z respectively represent the X coordinate, Y coordinate, and Z coordinate of the imaging object position.

[0092] Accordingly, the scattering tomography apparatus can appropriately generate an intermediate image based on the above-described scattering field function and the above-described imaging function determined by the X coordinate and Z coordinate of the position of the transmitting antenna element being the same as the X coordinate and Z coordinate of the position of the receiving antenna element, respectively.

[0093] The scattering tomography method according to one aspect of the present disclosure includes: a transmitting step of transmitting radio waves from the outside of an object to the inside of the object by a transmitting antenna element; a receiving step of receiving, outside the object, scattered waves of the radio waves transmitted from the transmitting antenna element to the inside of the object by a receiving antenna element; and a generating step of obtaining a plurality of measurement results over a plurality of days by obtaining measurement results of the scattered waves each day over a plurality of days, and generating a reconstructed image based on the plurality of measurement results. The reconstructed image shows continuous elements inside the object. In the step of generating the reconstructed image, for each of the plurality of measurement results, the measurement result is used as a boundary condition to calculate a scattering field function. The scattering field function takes the transmission position of the radio waves and the reception position of the scattered waves as inputs and outputs the amount of the scattered waves at the reception position. For each of the plurality of measurement results, an imaging function is calculated. The imaging function takes the imaging object position as an input and outputs the image intensity at the imaging object position. The imaging function is a function determined based on the amount output from the scattering field function by inputting the imaging object position as the transmission position and the reception position into the scattering field function. For each of the plurality of measurement results, an intermediate image is generated based on the imaging function, so that a plurality of intermediate images are generated for the plurality of measurement results. The reconstructed image is generated by calculating the minimum value of the image intensity at each position in the plurality of intermediate images through an "AND" operation.

[0094] Accordingly, an intermediate image capable of showing elements inside an object can be generated based on a scattered field function calculated by using the measurement result of a scattered wave as a boundary condition. Then, a reconstructed image capable of showing continuous elements inside the object can be generated based on a plurality of intermediate images obtained by using a plurality of measurement results over multiple days.

[0095] Therefore, a reconstructed image capable of showing continuous elements inside an object can be generated by using the scattered wave of an electromagnetic wave. Then, for example, it is possible to use the scattered wave to identify whether an element inside the human body is a continuous malignant tumor or other cells that randomly occur and disappear.

[0096] The embodiments will be described below with reference to the accompanying drawings. In addition, all the embodiments to be described below are general or specific examples. The numerical values, shapes, materials, constituent elements, arrangement positions and connection manners of the constituent elements, steps, and the order of steps shown in the following embodiments are all examples, and their gist is not to limit the claims.

[0097] (Embodiment)

[0098] The scatter tomography apparatus in the present embodiment uses the scattered wave of an electromagnetic wave to generate a reconstructed image capable of showing continuous elements inside an object. The scatter tomography apparatus in the present embodiment will be described in detail below, including the technologies and theories on which it is based. In addition, microwave mammography is mainly assumed below, the electromagnetic wave uses microwaves, and the object is a breast as an example. However, the applicable field is not limited to microwave mammography, and electromagnetic waves different from microwaves can also be used, and objects different from breasts can also be used.

[0099]

[0100] The present disclosure provides a method for determining malignant tumors or the like, or a method for confirming the absence of tumors or the like, by using temporal probability theory.

[0101] For example, for a person with a menstrual cycle, measurements are taken multiple times. Then, by using the method of temporal probability theory, an image showing elements that are unchanged in the long term or medium term inside the breast is extracted from the measurement results obtained through multiple measurements. Specifically, for example, according to the scattered field theory, a 3D image showing elements inside the breast is obtained from a single measurement result. Multiple 3D images are obtained from multiple measurement results. From the temporal data of such images, a final reconstructed image is obtained by using a probability partial differential equation (also called a temporal probability partial differential equation).

[0102] The method of chronological probability theory in the present disclosure is an analytical method based on probabilistic partial differential equations. The method of chronological probability theory can also be combined with known scattering field theories. Specifically, the method of chronological probability theory in the present disclosure can be combined with the scattering field theories described in Patent Document 2 or Patent Document 3 above.

[0103] To date, the inventors have conducted clinical trials combining the scattering field theory and the method of chronological probability theory for a total of five individuals aged from their early twenties to before the age of fifty. In the 3D images obtained from the measurement results of each person once, although results showing a certain element in the breast were obtained, no malignant tumors were found in all of them.

[0104] In microwave mammography based on the scattering field theory, the imaging target element is imaged with high resolution and high contrast. As a typical example, the imaging target element is a cell that is generated and disappears within a short period, or a tumor (or monotonically proliferating tumor) that remains unchanged within a medium to long period. The combination of the scattering field theory and the method of chronological probability theory is particularly effective in a simple situation where the imaging target element is one of the above, constituting a powerful diagnostic technique in practice.

[0105] <II Preliminary Physiological Knowledge for Consideration>

[0106] Figure 1 It is a graph showing the secretion of luteinizing hormone (progesterone) and others during the menstrual cycle.

[0107] Cell proliferation (mitosis) and cell loss (apoptosis) occur inside the human breast. It can be considered that cell proliferation (mitosis) and cell loss (apoptosis) depend on environmental hormones accompanying the menstrual cycle, that is, on the secretion amounts of estrogen and progesterone.

[0108] Figure 2A It is a graph showing the degree of cell proliferation (mitosis) of lobules during each day of the menstrual cycle. Figure 2B It is a graph showing the degree of cell loss (apoptosis) during each day of the menstrual cycle.

[0109] Figure 2A and Figure 2BBased on 'D.J.P.FERGUSON AND T.J.ANDERSON "MORPHOLOGICAL EVALUATION OF CELL TURNOVER IN RELATION TO THE MENSTRUAL CYCLE IN THE "RESTING" HUMAN BREAST" Br.J.Cancer(1981)44,177' (non-patent literature).

[0110] Figure 3 It is a conceptual diagram showing lobules and mammary ducts. The mammary gland is composed of multiple mammary lobules. The mammary lobules are further composed of lobules and mammary ducts. Lobules are used to produce breast milk, and mammary ducts are used to transport breast milk to the nipple.

[0111] As Figure 2A shown, especially the degree of cell proliferation in lobules increases as the menstrual cycle approaches its end. Thus, the degree of cell proliferation in lobules reaches a high value on the 25th day of a 28-day menstrual cycle. This high value is related to an increase in the number of lobules.

[0112] The effect of cell proliferation in lobules is also present in the measurement results obtained by microwave mammography. It can be clearly known that an increase in lobules with a high dielectric constant will become an obstacle to the detection of malignant tumors. In addition, from Figure 2A it can also be known that cell proliferation is inactive from the 4th day to the 19th day of the menstrual cycle. Therefore, this period is suitable for measurement by microwave mammography. However, in fact, even during this period, there are some reflected signals from lobules, and these reflected signals will become an obstacle to the detection of small tumors.

[0113] Moreover, during the menstrual cycle, cell proliferation (mitosis) and cell death (apoptosis) occur in a short period, and this phenomenon occurs in a quite large arbitrary area within the breast. The lobules generated by this phenomenon also appear as quite strong signals in local areas in the measurement results obtained by microwave mammography.

[0114] The sites where cell proliferation in lobules occurs are irregular. The phenomenon of cell proliferation in lobules does not spread uniformly throughout the breast but occurs locally (dispersedly). That is, it can be considered that lobular cells occur and disappear locally and irregularly.

[0115] The elements imaged by microwave mammography can be considered to be these irregularly occurring and disappearing lobular cells, or tumors that do not disappear for a long time once formed (including benign tumors such as fibroadenomas). In the method of chronological probability theory of the present disclosure, these differences are utilized to the maximum extent to extract tumors and the like.

[0116] The method of chronological probability theory is a powerful method that far exceeds the above-mentioned method of using specific periods in the menstrual cycle. For young people with a menstrual cycle, even if only a few chronological measurements are performed in the experiment, it is possible to surely determine whether they are healthy.

[0117] In addition, regarding whether the method of chronological probability theory can be applied to intrabodily measurement techniques other than microwave mammography, in X-ray mammography, collagen, etc. are thick in the image and are stably represented for a long time, so it is not suitable for application. In an ultrasonic echo device, since the impedance is mechanically adjusted manually for measurement, it is very difficult to improve the reproducibility, and there are many reflections of the intrabodily boundary layer for a long time. And since the intrabodily boundary layer freely deforms during measurement, it is still difficult to apply.

[0118] Moreover, there are also many problems in applying the method of chronological probability theory to measurements using MRI (magnetic resonance imaging) or PET (positron emission tomography).

[0119] <Summary of Scattering Field Theory (Multistatic Inverse Scattering Theory on a Surface)>

[0120] In this chapter, a scattering field theory for analyzing measurement results and obtaining 3D images is shown. The 3D image obtained by the scattering field theory is analyzed using a probability partial differential equation in the following steps. In addition, the scattering field theory described in Patent Document 2 or Patent Document 3 can also be appropriately applied.

[0121] Figure 4 It is a conceptual diagram showing an example in which an array antenna scans a surface and measures scattering data. The array antenna 401 is a multistatic array antenna that scans a surface and includes a transmitting antenna element T and a receiving antenna element R. There are various variations in the scattering field theory (also called multistatic inverse scattering theory on a surface) corresponding to the multistatic array antenna that scans a surface.

[0122] Here, as an example of the surface adopted in the scattering field theory, it is a relatively simple surface. For the x direction, the curvature is finite, and for the y direction, the curvature is 0. And in this example, the array antenna 401 arranged linearly along the y direction scans in the x direction along a curve.

[0123] The array antenna 401 is configured on a straight line identical to the X coordinate. Among the two orthogonal principal curvature directions on the surface with a Gaussian curvature of 0, the y direction with a curvature of 0 is the direction in which the transmitting antenna elements T and the receiving antenna elements R of the array antenna 401 are arranged, and the other x direction is the antenna scanning direction. This example is a quite general and practical example in the application of microwave mammography. Additionally, the array antenna 401 may also include a plurality of transmitting antenna elements T and may also include a plurality of receiving antenna elements R.

[0124] The radio wave radiated from point P1(x, y1, z) is reflected at point P(ξ, η, ζ) and received at point P2(x, y2, z). When point P exists at any position within the entire region D, the signal received at point P2 is expressed by the following formula (3-1).

[0125] [Mathematical formula 5]

[0126]

[0127] In formula (3-1), it is assumed that the time factor is proportional to exp(-iωt). And, ω represents the angular frequency of the radio wave, k represents the wave number of the radio wave, and ε(ξ, η, ζ) represents the reflectivity at P(ξ, η, ζ). And, ω = ck holds. Here, c is the propagation speed of the radio wave. The function of formula (3-1) can also be expressed by the scattering field function. In the state where ε(ξ, η, ζ) is unknown, the scattering field function of formula (3-1) is unknown.

[0128] The scattering field function of formula (3-1) can be interpreted as a function into which any transmission position and any reception position having the same x coordinate and z coordinate are input, and the amount of scattered wave at the reception position is output. When the transmission position and the reception position input to the scattering field function are respectively consistent with the positions of the transmitting antenna element T and the receiving antenna element R, the output of the scattering field function is consistent with the measurement data obtained through the receiving antenna element R.

[0129] Then, by applying t→0, x→x, y1→y2(=y), and z→z to the scattering field function, it is possible to consider the amount of scattered wave received immediately after the radio wave is transmitted, shown at (x, y, z), that is, the amount of reflection at (x, y, z).

[0130] Specifically, for example, in the scattering field function, if an arbitrary same position is input as both the transmission position and the reception position, the value output from the scattering field function as the amount of scattered wave can be considered such that the larger the reflection at that position, the larger the output value. That is, by inputting an arbitrary same position as both the transmission position and the reception position in the scattering field function, the value output from the scattering field function can show the amount of reflection at that position. The imaging function for generating an image showing the interior of an object, as a function showing such an amount, can be derived as follows.

[0131] The following equation (3-2) is the equation satisfied by the scattering field function of equation (3-1).

[0132] [Mathematical formula 6]

[0133]

[0134] As a general solution of the equation shown in equation (3-2), the following equation (3-3) can be obtained. That is, the following equation (3-3) can be obtained as the scattering field function.

[0135] [Mathematical formula 7]

[0136]

[0137] Here, k x , k y1 and k y2 respectively represent the wave numbers of the scattering field function related to x, y1, and y2. The scattering data measured on the boundary of the measurement object region (i.e., the measurement result) is represented by Φ(x, y1, y2, t), and the Fourier transform imaging related to y1, y2, t of Φ(x, y1, y2, t) is

[0138] [Mathematical formula 8]

[0139]

[0140] In this case, as a(k x , k y1 , k y2 ), the following equation (3-4) can be obtained.

[0141] [Mathematical formula 9]

[0142]

[0143] The above x I represented by x j represents the common X coordinate of the transmitting antenna element T and the receiving antenna element R, and the above z I represented by zj represents the common Z coordinate of the transmitting antenna element T and the receiving antenna element R. x j and z j satisfy the relationship shown by the following formula (3-5). Additionally, the function f in the following formula (3-5) is the shape function of the boundary surface.

[0144] [Mathematical formula 10]

[0145] z j = f(x j )

[0146] ···(3-5)

[0147] Formulas (3-3) and (3-4) are the scattered field functions calculated by using the measurement results as boundary conditions. Finally, the following formula (3-6) is obtained as the imaging function.

[0148] [Mathematical formula 11]

[0149]

[0150] ρ(r) represents the image. More specifically, r represents the imaging object position, and ρ(r) represents the image intensity at the imaging object position. The image intensity at the imaging object position corresponds to the output of the scattered field function for the imaging object position, that is, it corresponds to the magnitude of the reflection at the imaging object position. For example, since the elements in the breast reflect radio waves, a large image intensity is obtained at the positions of the elements in the breast.

[0151] The ρ(r) in formula (3-6) constitutes the probability field in the next chapter. And, the ρ(r) at t = t i corresponding to the i-th measurement is denoted as b i (r).

[0152] <IV Probability Partial Differential Equation>

[0153] <IV-1 Temporal Measurement>

[0154] Figure 5 is a conceptual diagram showing the temporal measurement (also called temporal 3D measurement) of the same region of the same person using microwave mammography.

[0155] The most standard method for temporal measurement is to consider about 28 days corresponding to the menstrual cycle as 4 weeks, perform a measurement once a week, and perform a total of four to five measurements in 4 to 5 weeks. The 3D image ρ(r) obtained in this way is determined as b i (r) (for example, i = 1, 2,..., 5).

[0156] <IV-2 Basic Equation>

[0157] When \(t\) represents time, \(r=(x,y,z)\) represents a three-dimensional vector, and \(\rho(t,r)\) represents the image intensity (specifically, the image intensity of the temporal probability), the spatio-temporal variation of the image intensity is described by the probability partial differential equation of the following formula (4-1).

[0158] [Mathematical formula 12]

[0159]

[0160] Here, \(\nu\) represents the diffusion coefficient, corresponding to the noise that enters each time a measurement is made. The noise is assumed to be arbitrary and can occur due to deviations in the position accompanying the scale and deviations in the measurement area due to the scanning deviation of the probe. And, \(\delta\) represents the \(\delta\) function. And, \(\land\) is a symbol representing logical AND, meaning the minimum value shown in the following formula (4-2).

[0161] [Mathematical formula 13]

[0162] \(a\land b=\min\{a,b\}\)

[0163] ···(4-2)

[0164] In the equation of formula (4-1), \(\rho(t\) i- ,r)\) means the lower limit of the following formula (4-3).

[0165] [Mathematical formula 14]

[0166]

[0167] \(\alpha\) represents a constant that depends on \(\nu\) and \(\Delta t=t\) i -t i-1 , and it can also be \(\alpha = 1\). \(b\) i (r) represents the image intensity of the probability of the position of the spatial coordinate \(r\) at time \(t\) i .

[0168] That is, the first term on the right side of formula (4-1) corresponds to the deviation of the measurement area. The second term on the right side of formula (4-1) corresponds to the change in the image intensity during the measurement, corresponding to the difference (changing part) between the fixed part and the whole part of the image intensity. The spatio-temporal change of the image intensity corresponds to the sum of these.

[0169] Figure 6 is a curve graph showing the temporal data of the image intensity of the probability at \(r = r_0\), showing the discrete \(b\) at \(r = r_0\) j (r0)(j = 1, 2, 3, …, N). \(b\) i (r) is an image obtained from the \(i\)-th measurement result in microwave mammography. In the above scattering field theory, \(b\)i (r) is recorded as ρ(r). That is, b i represents the imaging function, b i (r) represents the image obtained from the imaging function.

[0170] By integrating the probability partial differential equation shown in Equation (4-1) near t = t i the following Equation (4-4) is obtained.

[0171] [Mathematical formula 15]

[0172]

[0173] By performing the integration of Equation (4-4), the following Equation (4-5) is obtained.

[0174] [Mathematical formula 16]

[0175]

[0176] If we set Δt = t i -t i-1 , then the following Equation (4-6) holds in the limit as Δt → 0.

[0177] [Mathematical formula 17]

[0178]

[0179]

[0180] According to Equation (4-5) and Equation (4-6), the following Equation (4-7) holds.

[0181] [Mathematical formula 18]

[0182] ρ(t i , r) = αb i (r) ∧ ρ(t i- , r)

[0183] ···(4-7)

[0184] And, when t is not near t i , according to Equation (4-1), the following Equation (4-8) holds.

[0185] [Mathematical formula 19]

[0186]

[0187] <IV-3 Solution of the Probability Partial Differential Equation>

[0188] Regarding the singularity t = t of the probability partial differential equation in Equation (4-1) iThe solutions other than that are the solutions of Equation (4-8), and are obtained using the Fourier transform shown in the following Equation (4-9).

[0189] [Mathematical formula 20]

[0190]

[0191] Here, Q(t, k) represents the Fourier transform image of ρ(t, r).

[0192] [Mathematical formula 21]

[0193]

[0194] represents the Fourier transform image of ρ(t, x, y, z). k x 、k y and k z respectively represent the wave numbers related to x, y, and z. As shown in Equation (4-9), k of Q(t, k) corresponds to (k x , k y , k z ). According to Equation (4-8) and Equation (4-9), the differential equation of the following Equation (4-10) is obtained.

[0195] [Mathematical formula 22]

[0196]

[0197] The differential equation of Equation (4-10) can be easily solved to obtain the solution shown in the following Equation (4-11). Here, c(k x , k y , k z ) corresponds to the value of Q(t, k) in t = t j →t i , that is, corresponds to Q(t j →t i in the limit of j , k).

[0198] [Mathematical formula 23]

[0199]

[0200]

[0201] According to Equation (4-11), as the solution other than the singularity t = t i of the probability partial differential equation of Equation (4-1), the following Equation (4-12) is obtained.

[0202] [Mathematical formula 24]

[0203]

[0204] Scope of application t i <t<t i+1 (i = 1, 2, 3, …, N - 1)

[0205] ···(4 - 12)

[0206] <Physical meaning of the diffusion term ν of <V diffusion term ν>>

[0207] Figure 7 It is a conceptual diagram showing the deviation of the measurement area. For example, a single-sided adhesive film is attached to the subject, and measurement is performed on the surface of the attached film. That is, the area of the attached film is used as the measurement area. And, for example, this film is composed of a transparent or translucent member (specifically, synthetic resin, etc.) that allows radio waves to pass through. And, a 32×32 grid is printed on the film, and in the time-sequential measurement, the film is attached so that the nipple or mole of the subject is located within the same grid.

[0208] Here, the measurement area in the time-sequential measurement is represented as D i (i = 1, 2, 3, …, N). Even with the above-mentioned grid of the film, it is difficult to make each D i be at the same position of the subject. Deviation occurs each time. This deviation is assumed to be random and is represented by the diffusion term.

[0209] For example, the measurement area randomly deviates by Δσ in the (x, y) plane every Δt. Δσ can be represented as Δσ = (Δx, Δy). And, Δσ can also correspond to a combination of rotation and translation.

[0210] Since the deviation occurs in the above-mentioned two-dimensional plane, the Laplace operator Δ in Equation (4 - 8) becomes a two-dimensional operator. The fundamental solution of Equation (4 - 8) related to the deviation of the measurement area is represented by the following Equation (5 - 1).

[0211] [Mathematical formula 25]

[0212]

[0213] The deviation of the measurement area does not have the characteristic of increasing with the number of measurements. The measurement area generally changes randomly near the same position due to the position error. If the deviation of the measurement area is assumed to be a normal distribution, it is the same as the well-known Brownian motion, and the distribution function of the deviation of the measurement area is represented by the diffusion equation. Here, if r0 is set as the reference position and r is set as the position of the particle in Brownian motion, the mean square error of these is proportional to νt. This relationship is represented by the following Equation (5 - 2).

[0214] [Mathematical formula 26]

[0215] <(r - r0) 2 > ∝νt

[0216] ···(5 - 2)

[0217] As described above, the deviation of the measurement area does not have the characteristic of increasing with the number of measurements. Therefore, t in Equation (5 - 2) can be interpreted as representing the time from a certain measurement time to the next measurement time. For example, it can be determined that a certain measurement time is t = 0 and the next measurement time is t = 1. At this time, Equation (5 - 2) is obtained as the following Equation (5 - 3).

[0218] [Mathematical formula 27]

[0219] <(r - r0) 2 > ∝v

[0220] ···(5 - 3)

[0221] For example, the diffusion coefficient v can be estimated as the deviation amount of the measurement area between two measurements.

[0222] <Method for identifying tumors and lobular cells by VI>

[0223] The solution of Equation (4 - 8) is determined in the form of the following Equation (6 - 1).

[0224] [Mathematical formula 28]

[0225] ρ(t, r) = e (vΔ)t ρ(0, r)

[0226] ···(6 - 1)

[0227] Moreover, the assumed time interval between each measurement in the time - series measurement is determined to be δt = 1 (i.e., t i - t i-1 = 1). Then, when the time - series measurement images are represented by b i (r) (i = 1, 2, 3, …, N), the following Equation (6 - 2) represents the time - series measurement image considering the error of the measurement area at the time of measurement. That is, the following Equation (6 - 2) represents the time - series measurement image in which the image intensity at each position is diffused in its periphery considering the error of the measurement area at the time of measurement.

[0228] [Mathematical formula 29]

[0229] e vΔ b1(r), e vΔ b2(r), e vΔ b3(r), …·e vΔ b N (r)

[0230] ···(6 - 2)

[0231] e vΔ b i (r) is obtained by performing the Fourier transform of b with respect to x, y, and z according to Equation (4 - 12), and multiplying by exp(-v(k i (r) and performing the inverse Fourier transform. That is, e x 2 +k y 2 )) vΔ b i (r) is obtained from the following Equation (6 - 3).

[0232] [Mathematical formula 30]

[0233]

[0234]

[0235] The final tumor probability image is obtained from the following Equation (6 - 4) based on Equation (4 - 7).

[0236] [Mathematical formula 31]

[0237] ρ N (r) = e vΔ b1(r) ∧ e vΔ b2(r) ∧ e vΔ b3(r) ∧ … ∧ e vΔ b N (r)

[0238] ν = <(r - r0) 2 >

[0239] ···(6 - 4)

[0240] In Equation (6 - 4), in order to clearly define v, an equation is adopted in the ratio of Equation (5 - 3) of v.

[0241] By calculating the minimum value of the image intensity at each position in the temporal measurement image, in the tumor probability image, the temporary lobules disappear while the tumor persists. Additionally, in the case of deviation in the measurement area, due to the deviation of the position, there is also a possibility of the tumor disappearing in the tumor probability image. By spreading the image intensity at each position in the temporal measurement image to its periphery, even if there is a deviation in the measurement area, the above disappearance can be suppressed.

[0242] <VII Verification with actual data>[

[0243] For the validity of the above theory, clinical trials and synthetic data based on clinical trial data will be used for verification. Four examples, Example 1 to Example 4, are shown below.

[0244] The subjects of Example 1 to Example 3 are all young people regarded as healthy. In the time-series clinical trial, the measurement frequency is 4 to 8 times per person considering the menstrual cycle. The data of each person is all sorted by the same image intensity. That is, the scale of the image intensity between images is unified, and the maximum value and the minimum value of the image intensity between images are also unified respectively. The most ideal ν = 0 is adopted in the analysis.

[0245] Example 4 is an example of simulation in the case of having cancer. Synthetic data made from the clinical trial data of two people, cancer patients and healthy people, is used for verification. Specifically, synthetic data made by overlapping the clinical trial data of a cancer patient once to the time-series clinical trial data of a healthy person 4 times respectively is adopted.

[0246] For example, obtained from 1 time of clinical data Figure 8A 、 Figure 8B or Figure 8C the images shown.

[0247] Figure 8A is a figure showing a display example of an image showing the inside of the breast. As Figure 8A shown, the inside of the breast is semi-transparent and represented in three dimensions. The upper side of the image corresponds to the upper side of the subject, and the lower side of the image corresponds to the lower side of the subject. And, the left side of the image corresponds to the right side of the subject, and the right side of the image corresponds to the left side of the subject.

[0248] Figure 8B is a figure showing a display example of a semi-transparent perspective image when looking at the inside of the breast from the lower side to the upper side of the subject. The left side of the image corresponds to the right side of the subject, and the right side of the image corresponds to the left side of the subject.

[0249] Figure 8C is a figure showing a display example of a semi-transparent perspective image when looking at the inside of the breast from the front of the subject. The left side of the image corresponds to the right side of the subject, and the right side of the image corresponds to the left side of the subject.

[0250] As Figure 8A 、 Figure 8B or Figure 8C shown, by obtaining the displayed image each time a measurement is made, a time-series of multiple images is obtained. Then, a tumor probability image for identifying tumors and the like is generated from the time-series of multiple images.

[0251] <VII-1 Example 1>

[0252] Figure 9AIt is a diagram showing a display example of a reconstructed image obtained from the measurement data on January 11 in Example 1. This image corresponds to b1(r) described above.

[0253] Figure 9B It is a diagram showing a display example of a reconstructed image obtained from the measurement data on January 18 in Example 1. This image corresponds to b2(r) described above.

[0254] Figure 9C It is a diagram showing a display example of a reconstructed image obtained from the measurement data on January 25 in Example 1. This image corresponds to b3(r) described above.

[0255] Figure 9D It is a diagram showing a display example of a reconstructed image obtained from the measurement data on February 1 in Example 1. This image corresponds to b4(r) described above. And in Example 1, February 1 corresponds to the start day of the menstrual cycle.

[0256] Figure 9E It is a diagram showing a display example of the tumor probability image in Example 1. This image corresponds to ρ4(r) described above. In Example 1, no tumors were seen at all, which was identified by the tumor probability image.

[0257] <VII-2 Example 2>

[0258] Figure 10A It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 1 in Example 2. This image corresponds to b1(r) described above. And in Example 2, June 1 corresponds to the start day of the menstrual cycle.

[0259] Figure 10B It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 5 in Example 2. This image corresponds to b2(r) described above.

[0260] Figure 10C It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 8 in Example 2. This image corresponds to b3(r) described above.

[0261] Figure 10D It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 12 in Example 2. This image corresponds to b4(r) described above.

[0262] Figure 10E It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 15 in Example 2. This image corresponds to b5(r) described above.

[0263] Figure 10F It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 19 in Example 2. This image corresponds to b6(r) described above.

[0264] Figure 10G It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 22 in Example 2. This image corresponds to b7(r) described above.

[0265] Figure 10H It is a diagram showing a display example of a reconstructed image obtained from the measurement data on June 26 in Example 2. This image corresponds to b8(r) described above.

[0266] Figure 10I It is a diagram showing a display example of the tumor probability image in Example 2. This image corresponds to ρ8(r) described above. In Example 2, no tumors or the like were seen at all, which was identified by the tumor probability image.

[0267] <VII-3 Example 3>

[0268] Figure 11A It is a diagram showing a display example of a reconstructed image obtained from the measurement data on October 23 in Example 3. This image corresponds to b1(r) described above.

[0269] Figure 11B It is a diagram showing a display example of a reconstructed image obtained from the measurement data on October 30 in Example 3. This image corresponds to b2(r) described above.

[0270] Figure 11C It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 6 in Example 3. This image corresponds to b3(r) described above.

[0271] Figure 11D It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 13 in Example 3. This image corresponds to b4(r) described above.

[0272] Figure 11E It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 20 in Example 3. This image corresponds to b5(r) described above.

[0273] Figure 11F It is a diagram showing a display example of a reconstructed image obtained from the measurement data on November 27 in Example 3. This image corresponds to b6(r) described above.

[0274] Figure 11G It is a diagram showing a display example of a reconstructed image obtained from the measurement data on December 4 in Example 3. This image corresponds to b7(r) described above.

[0275] Figure 11H It is a diagram showing a display example of a reconstructed image obtained from the measurement data on December 11 in Example 3. This image corresponds to b8(r) described above.

[0276] Figure 11I It is a diagram showing a display example of the tumor probability image in Example 3. This image corresponds to ρ8(r) described above. In Example 3, no tumor or the like was seen at all, which was recognized by the tumor probability image.

[0277] <VII-4 Example 4>

[0278] Figure 12A It is a diagram showing a display example of a reconstructed image obtained from the composite data of the measurement data of the cancer patient in Example 4 and the measurement data of a healthy person on February 26th.

[0279] This image corresponds to b1(r) described above.

[0280] Figure 12B It is a diagram showing a display example of a reconstructed image obtained from the composite data of the measurement data of the cancer patient in Example 4 and the measurement data of a healthy person on February 5th. This image corresponds to b2(r) described above.

[0281] Figure 12C It is a diagram showing a display example of a reconstructed image obtained from the composite data of the measurement data of the cancer patient in Example 4 and the measurement data of a healthy person on February 12th. This image corresponds to b3(r) described above.

[0282] Figure 12D It is a diagram showing a display example of a reconstructed image obtained from the composite data of the measurement data of the cancer patient in Example 4 and the measurement data of a healthy person on February 19th. This image corresponds to b4(r) described above. And in Example 4, February 19th corresponds to a date within 10 days from the start date of the menstrual cycle of a healthy person.

[0283] Figure 12E It is a diagram showing a display example of the tumor probability image in Example 4. This image corresponds to ρ4(r) described above. In Example 4, a tumor was present on the right side of the breast, which was recognized by the tumor probability image.

[0284] <VIII Configuration and Operation of the Scattering Tomography Device>

[0285] Based on the above content, the configuration and operation of a scattering tomography device that generates a reconstructed image showing continuous elements inside an object using scattered waves of radio waves are shown below. Here, continuous elements are elements that do not disappear during a specified period such as 4 weeks.

[0286] Figure 13 It is a basic configuration diagram of the scattering tomography device in this embodiment. Figure 13The shown diffuse tomography device 100 includes: a transmitting antenna element 101, a receiving antenna element 102, and an information processing circuit 103. Also, the diffuse tomography device 100 may include a display 104.

[0287] The transmitting antenna element 101 is a circuit that transmits electric waves. Specifically, the transmitting antenna element 101 transmits electric waves from the outside of the object to the inside of the object. The electric waves can be microwaves, millimeter waves, terahertz waves, etc. The object can be a living body, a manufactured product, or a natural material, etc. In particular, the object can be a breast. The diffuse tomography device 100 may also include a plurality of transmitting antenna elements 101.

[0288] The receiving antenna element 102 is a circuit that receives electric waves such as scattered waves that are electric waves. Specifically, the receiving antenna element 102 receives the scattered waves of the electric waves transmitted to the inside of the object outside the object. The diffuse tomography device 100 may also include a plurality of receiving antenna elements 102. Also, the receiving antenna element 102 may be substantially arranged at the same position as the transmitting antenna element 101, or may be arranged at a position different from the transmitting antenna element 101.

[0289] Also, the transmitting antenna element 101 and the receiving antenna element 102 may form a multistatic antenna or a monostatic antenna.

[0290] The information processing circuit 103 is a circuit that performs information processing. Specifically, the information processing circuit 103 generates a reconstructed image showing the continuous elements inside the object based on a plurality of measurement results obtained by the transmitting antenna element 101 and the receiving antenna element 102 over multiple days. For example, when generating a reconstructed image based on the measurement results, the information processing circuit 103 performs the arithmetic processing shown in the above theory.

[0291] Also, the information processing circuit 103 may be a computer or a processor of a computer. The information processing circuit 103 may read a program from a memory and perform information processing by executing the program. Also, the information processing circuit 103 may be a dedicated circuit that generates a reconstructed image showing the continuous elements inside the object based on a plurality of measurement results over multiple days.

[0292] Also, the information processing circuit 103 can also output the generated reconstructed image to a display 104 or the like. For example, the information processing circuit 103 can display the reconstructed image on the display 104 by outputting the reconstructed image to the display 104. Alternatively, the information processing circuit 103 can print the reconstructed image by a printer (not shown) by outputting the reconstructed image to the printer. Alternatively, the information processing circuit 103 can also transmit the reconstructed image as electronic data to another device (not shown) through wired or wireless communication.

[0293] The display 104 is a display device such as a liquid crystal display. In addition, the display 104 can be any component and is not an essential component. Also, the display 104 can be a device external to the scattering tomography apparatus 100 that does not form part of it.

[0294] Figure 14 is a flowchart showing Figure 13 the basic operation of the scattering tomography apparatus 100 shown. Specifically, Figure 13 the transmitting antenna element 101, the receiving antenna element 102, and the information processing circuit 103 of the scattering tomography apparatus 100 shown perform Figure 14 the operations shown.

[0295] First, the transmitting antenna element 101 transmits radio waves from the outside of the object to the inside of the object (S201). Next, the receiving antenna element 102 receives the scattered waves of the radio waves transmitted to the inside of the object outside the object (S202). Then, the information processing circuit 103 generates a reconstructed image showing the continuous elements inside the object based on the multiple measurement results obtained by the transmitting antenna element 101 and the receiving antenna element 102 over multiple days (S203).

[0296] When the information processing circuit 103 generates a reconstructed image based on multiple measurement results, first for each of the multiple measurement results, the measurement result is used as a boundary condition to calculate the scattering field function. The scattering field function is a function that takes the transmission position of the input radio wave and the reception position of the scattered wave and outputs the amount of the scattered wave at the reception position. That is, the scattering field function is a function that shows the amount of the scattered wave at the reception position for arbitrarily determined transmission and reception positions.

[0297] Then, the information processing circuit 103 calculates the imaging function based on the scattering field functions calculated for each of the multiple measurement results. The imaging function is a function that takes the imaging object position as input and outputs the image intensity at the imaging object position, and is a function determined based on the amount obtained by inputting the transmission position and the reception position as the imaging object position into the scattering field function and outputting from the scattering field function.

[0298] Then, the information processing circuit 103 generates intermediate images based on the imaging functions calculated for each of the multiple measurement results, thereby generating multiple intermediate images for the multiple measurement results. Then, the information processing circuit 103 calculates the minimum value of the image intensity at each position in the multiple intermediate images through an "AND" operation, thereby generating a reconstructed image. The information processing circuit 103 can output the generated reconstructed image to the display 104 or the like.

[0299] Accordingly, the scattering tomography apparatus 100 can calculate an intermediate image that can show the internal elements of an object based on the scattering field function calculated using the measurement results of the scattered waves as boundary conditions. Then, the scattering tomography apparatus 100 generates a reconstructed image that shows the continuous elements inside the object from the multiple intermediate images obtained using the multiple measurement results over multiple days.

[0300] Therefore, the scattering tomography apparatus 100 can use the scattered waves of the radio wave to generate a reconstructed image that shows the continuous elements inside the object. Then, for example, the scattered waves can be used to identify whether the internal elements of the human body are continuous malignant tumors or other cells that occur randomly and disappear.

[0301] For example, the information processing circuit 103 can generate a reconstructed image through P N (r) = b1(r) ∧ b2(r) ∧ … ∧ b N (r). Here, P N (r) represents the reconstructed image. And r represents the position. And N represents the number of multiple intermediate images. And b i related to i from 1 to N represents the imaging function. And ∧ represents logical AND.

[0302] Accordingly, the scattering tomography apparatus 100 can simply generate a reconstructed image through the logical AND of the intermediate images corresponding to the output of the imaging function.

[0303] And, for example, the information processing circuit 103 generates an intermediate image based on the imaging function and the diffusion coefficient. When generating the intermediate image, the larger the diffusion coefficient, the greater the spatial diffusion of the image intensity at the imaging target position in the intermediate image.

[0304] Accordingly, the scattering tomography apparatus 100 can diffuse the image intensity through the diffusion coefficient. Therefore, the scattering tomography apparatus 100 can suppress the disappearance of continuous elements from the reconstructed image due to position deviation in the measurement of scattered waves through the diffusion coefficient.

[0305] And, for example, the information processing circuit 103 can generate a reconstructed image through P N (r) = e νΔ b1(r) ∧ eνΔ b2(r) ∧ ··· ∧ e νΔ b N (r) is used to generate a reconstructed image. Here, P N (r) represents the reconstructed image. Also, r represents a position. Also, N represents the number of multiple intermediate images. And, b related to i from 1 to N i represents an imaging function. And, e related to i from 1 to N νΔ b i (r) represents an intermediate image. Also, ν represents a diffusion coefficient. And, Δ represents a two-dimensional Laplacian operator corresponding to two directions in which a position deviation occurs in the measurement of a scattered wave. And, ∧ represents a logical AND.

[0306] Accordingly, the scattering tomography apparatus 100 can appropriately diffuse the image intensity through a relational expression based on a probabilistic method.

[0307] And it can also be, for example, that the information processing circuit 103 performs a Fourier transform on b i (r), multiplies the result of the Fourier transform by exp(-ν(k x 2 + k y 2 ))), and performs an inverse Fourier transform on the result after multiplying by exp(-ν(k x 2 + k y 2 ))). Accordingly, the information processing circuit 103 can also calculate e νΔ b i (r). Here, k x 2 and k y 2 in exp(-ν(k x + k y ) represent two wave numbers corresponding to two directions of b i .

[0308] Accordingly, the scattering tomography apparatus 100 can quickly and appropriately diffuse the image intensity.

[0309] And, for example, the diffusion coefficient can be determined as a value proportional to the mean square error of the measurement position of the scattered wave. Accordingly, the diffusion coefficient can be determined according to the magnitude of the error of the measurement position. Thus, the scattering tomography apparatus 100 can accurately diffuse the image intensity according to the magnitude of the error of the measurement position.

[0310] Further, for example, the diffusion coefficient can be determined to be equal to the mean square error of the measurement position of the scattered wave. Accordingly, the diffusion coefficient can be simply determined according to the magnitude of the error of the measurement position. Then, the scatter tomography apparatus 100 can accurately diffuse the image intensity according to the magnitude of the error of the measurement position.

[0311] Further, for example, the diffusion coefficient can also be determined to be 0. Accordingly, the scatter tomography apparatus 100 simply generates a reconstructed image by performing a logical AND operation on the intermediate image corresponding to the output of the imaging function, in the same manner as when not using the diffusion coefficient.

[0312] Further, for example, the diffusion coefficient is determined to be a value greater than 0. Accordingly, the scatter tomography apparatus 100 can surely diffuse the image intensity by the diffusion coefficient greater than 0. Therefore, the scatter tomography apparatus 100 can surely suppress the disappearance from the reconstructed image due to the position deviation in the measurement of the scattered wave of the continuous element.

[0313] Further, for example, it may also be that in the three-dimensional space composed of the X coordinate, the Y coordinate, and the Z coordinate, the X coordinate and the Z coordinate of the position of the transmitting antenna element 101 are the same as the X coordinate and the Z coordinate of the position of the receiving antenna element 102, respectively.

[0314] Then, the scattered field function can be determined by

[0315] [Mathematical formula 32]

[0316]

[0317] as follows.

[0318] Here, x represents the X coordinate of the transmission position and the reception position. Further, y1 represents the Y coordinate of the transmission position. Further, y2 represents the Y coordinate of the reception position. Further, z represents the Z coordinate of the transmission position and the reception position. Further, k represents the wave number of the radio wave. And k in the scattered field function x 、k y1 and k y2 represent the wave numbers related to x, y1, and y2 of the scattered field function, respectively.

[0319] Further, a(k x 、k y1 、k y2 ) can be determined by

[0320] [Mathematical formula 33]

[0321]

[0322] as follows.

[0323] Here, I represents the index of the transmission position and the reception position where the transmission antenna element 101 and the reception antenna element 102 are located. And, x I represents the X coordinate of the transmission position and the reception position where the transmission antenna element 101 and the reception antenna element 102 are located. And, z I represents the Z coordinate of the transmission position and the reception position where the transmission antenna element 101 and the reception antenna element 102 are located.

[0324] And,

[0325] [Mathematical formula 34]

[0326]

[0327] represents the Fourier transform imaging related to y1, y2, and t in Φ(x, y1, y2, t) showing the measurement results in x, y1, y2, and t. And, t represents time.

[0328] Then, the imaging function can also be determined by

[0329] [Mathematical formula 35]

[0330]

[0331] Here, x, y, and z of the imaging function respectively represent the X coordinate, Y coordinate, and Z coordinate of the imaging object position.

[0332] Accordingly, the scatter tomography apparatus 100 can accurately generate an intermediate image based on the above-described scatter field function and the above-described imaging function. The above-described scatter field function and the above-described imaging function can be accurately determined when the X coordinate and Z coordinate of the position of the transmission antenna element 101 are the same as the X coordinate and Z coordinate of the position of the reception antenna element 102, respectively.

[0333] And, for example, in the transmission antenna element 101, reception antenna element 102, information processing circuit 103, scatter field function, imaging function, and parameters shown in the above-described basic configuration and basic operation, the constituent elements, mathematical formulas, and variables shown in the present embodiment can be appropriately used.

[0334] And, the scatter field function and imaging function shown in the present embodiment can also be appropriately deformed for application. For example, the content substantially the same as the above-described mathematical formula can be used as a mathematical formula shown in other expressions, or other mathematical formulas derived based on the above theory can be adopted.

[0335] Figure 15 shows Figure 13Conceptual diagram of the specific configuration of the scattering tomography device 100 shown.

[0336] Figure 13 The transmitting antenna element 101 and the receiving antenna element 102 of the scattering tomography device 100 shown may be included in a multistatic array antenna 1008. Figure 13 The information processing circuit 103 of the scattering tomography device 100 shown may correspond to Figure 15 one or more of the multiple components shown. Specifically, for example, the information processing circuit 103 may correspond to the signal processing computer 1005. And it may also be Figure 13 the display 104 shown corresponding to the signal monitoring device 1006.

[0337] The microwave signal used in the scattering tomography device 100 is a pseudo-random code sequence signal (PN code: Pseudo Noise Code) having frequency components from DC to 20 GHz. This signal is output from the FPGA board 1002 for PN code generation. More specifically, there are two such signals. One of the signals (LO signal: local oscillator signal) passes through a delay circuit (digital control board 1003) and is sent to the RF detection circuit (RF detection board 1007).

[0338] The other signal (RF signal: Radio Frequency Signal) is sent to the transmitting microwave UWB antenna of the multistatic array antenna 1008 and is radiated. The scattered microwave signal is received by the receiving UWB antenna of the multistatic array antenna 1008 and is sent to the RF detection circuit (RF detection board 1007). Here, the transceiver signals pass through the antenna element selection switch (UWB antenna RF switch 1004).

[0339] And the delayed signal (LO signal) is delayed by a time that is 1 / 2 n times (n is an integer greater than 2) the time when the value of each PN code changes. The detected signal is used as an IF signal (Intermediate Frequency Signal), undergoes A / D conversion in the signal processing computer 1005 and is stored. And the information showing the detected signal can be displayed on the signal monitoring device 1006.

[0340] The timing of this series of operations is controlled by the microprocessor in the digital control board 1003 in a manner synchronized with the signal (distance signal or free oscillation signal) from the rangefinder 1001. For example, the microprocessor in the digital control board 1003 sends switch switching signals and PN code scan triggers, etc.

[0341] Furthermore, the signal processing computer 1005 uses the signals that have been A / D converted and stored to perform three-dimensional reconstruction and three-dimensional image display. Also, the signal processing computer 1005 can perform signal correction. Additionally, the signal processing computer 1005 can also perform original waveform display.

[0342] Furthermore, for example, the signal processing computer 1005 saves the three-dimensional images obtained from each measurement to the memory 1009, and thus saves multiple three-dimensional images to the memory 1009. These three-dimensional images correspond to the above-mentioned time-sequential measurement images. The signal processing computer 1005 uses these three-dimensional images to generate a final tumor probability image, and displays the generated tumor probability image on the signal monitoring device 1006 or the like.

[0343] Figure 15 The configuration shown is an example, and the configuration of the scatter tomography device 100 is not limited by Figure 15 the shown configuration. Figure 15 A part of the shown configuration can be omitted or changed.

[0344] (Supplement)

[0345] The form of the scatter tomography device has been described above based on the embodiments. However, the form of the scatter tomography device is not limited by the embodiments. Modifications that can be conceived by those skilled in the art can be made to the embodiments, and arbitrary combinations of multiple constituent elements in the embodiments can also be made. For example, in the embodiments, for the processing performed by specific constituent elements, the specific constituent elements can be replaced by other constituent elements to perform the processing. Also, the order of multiple processes can be changed, and multiple processes can be executed in parallel.

[0346] Also, although an example of identifying lobules and tumors in the breast in microwave mammography is shown in the above description, the application of the scatter tomography device shown in the embodiments is not limited by this example. The scatter tomography device can extract continuous elements within an object without damaging the object, and other objects and other elements having the same relationship as the relationship between the breast and the tumor can also be applied.

[0347] Furthermore, the scatter tomography method including the steps performed by each constituent element of the scatter tomography device can be executed by any device or system. For example, a part or all of the scatter tomography method can be executed by a computer having a processor, a memory, and input / output circuits, etc. At this time, the scatter tomography method is executed by the computer executing a program for causing the computer to execute the scatter tomography method.

[0348] Further, the above-described program can be recorded on a non-transitory computer-readable recording medium.

[0349] Further, each component of the scatter tomography apparatus can be configured by dedicated hardware, can be configured by general-purpose hardware that executes the above-described program or the like, or can be configured by a combination of these hardware components. The general-purpose hardware can be configured by a memory that stores a program and a general-purpose processor that reads and executes the program from the memory. Here, the memory can be a semiconductor memory, a hard disk, or the like, and the general-purpose processor can be a CPU or the like.

[0350] The dedicated hardware can be configured by a memory and a dedicated processor or the like. For example, the dedicated processor can execute the above-described scatter tomography method with reference to the memory for recording measurement data.

[0351] Further, each component of the scatter tomography apparatus can be a circuit. These circuits can be configured as a single circuit as a whole, or can be configured as individual circuits. Further, these circuits can correspond to dedicated hardware, or can correspond to general-purpose hardware that executes the above-described program or the like.

[0352] Industrial Applicability

[0353] One aspect of the present invention can be effectively applied to a scatter tomography apparatus that generates an image showing the interior of an object using scattered waves of radio waves, and can be applied to physical exploration, medical diagnosis, or the like.

[0354] Symbol Explanation

[0355] 100 Scatter Tomography Apparatus

[0356] 101 Transmitting Antenna Element

[0357] 102 Receiving Antenna Element

[0358] 103 Information Processing Circuit

[0359] 104 Display

[0360] 401 Array Antenna

[0361] 1001 Rangefinder

[0362] 1002 FPGA Board for PN Code Generation

[0363] 1003 Digital Control Board

[0364] 1004 UWB Antenna RF Switch

[0365] 1005 Signal Processing Computer

[0366] 1006 Signal Monitoring Device

[0367] 1007 RF Detection Substrate

[0368] 1008 Multistatic Array Antenna

[0369] 1009 Memory

Claims

1. A scattering tomography device, The scattering tomography device includes: A transmitting antenna element that transmits radio waves from the outside of an object to the inside of the object; A receiving antenna element that receives, outside the object, scattered waves of the radio waves transmitted from the transmitting antenna element to the inside of the object; and An information processing circuit that obtains a plurality of measurement results over a plurality of days by obtaining measurement results of the scattered waves each day over the plurality of days, and generates a reconstructed image based on the plurality of measurement results, the reconstructed image showing continuous elements inside the object, The information processing circuit operates as follows: For each of the plurality of measurement results, using the measurement result as a boundary condition, calculates a scattering field function that is input with the transmission position of the radio wave and the reception position of the scattered wave and outputs a value representing the amount of the scattered wave at the reception position, For each of the plurality of measurement results, calculates an imaging function that is input with an imaging target position and outputs an image intensity at the imaging target position, and the imaging function is a function determined based on the amount output from the scattering field function by inputting the imaging target position as the transmission position and the reception position into the scattering field function, For each of the plurality of measurement results, generates a plurality of intermediate images for the plurality of measurement results by generating an intermediate image based on the imaging function, Generates the reconstructed image by calculating the minimum value of the image intensity at each position in the plurality of intermediate images through an "AND" operation.

2. The scattering tomography device according to claim 1, The information processing circuit generates the reconstructed image through P N (r) = b1(r) ∧ b2(r) ∧ … ∧ b N (r). P N (r) represents the reconstructed image, r represents the position of the imaged object, N represents the number of the plurality of intermediate images, and b related to i from 1 to N i represents the imaging function, and ∧ represents logical AND.

3. The scattering tomography device according to claim 1, The information processing circuit, Generates the intermediate image based on the imaging function and a diffusion coefficient, When generating the intermediate image, the larger the diffusion coefficient, the greater the spatial diffusion of the image intensity at the imaging target position in the intermediate image.

4. The scattering tomography device according to claim 3, The information processing circuit generates the reconstructed image through P N (r) = e νΔ b1(r) ∧ e νΔ b2(r) ∧ … ∧ e νΔ b N (r). P N (r) represents the reconstructed image, r represents the position of the imaged object, N represents the number of the plurality of intermediate images, and b related to i from 1 to N i represents the imaging function, and e related to i from 1 to N νΔ b i (r) represents the intermediate image, ν represents the diffusion coefficient, Δ represents the two-dimensional Laplacian operator corresponding to two directions in which position deviation occurs in the measurement of the scattered wave, and ∧ represents logical AND.

5. The scattering tomography device according to claim 4, The information processing circuit performs a Fourier transform on b i (r), multiplies the result of the Fourier transform by exp(-ν(k x 2 +k y 2 ))), performs an inverse Fourier transform on the result after multiplying by exp(-ν(k x 2 +k y 2 ))), and thus calculates e νΔ b i (r). exp(-ν(k x 2 +k y 2 )) of k x and k y represent two wavenumbers corresponding to the two directions of b i respectively.

6. The scattering tomography device according to any one of claims 3 to 5, The diffusion coefficient is determined to be a value proportional to the mean square error of the measurement positions of the scattered waves.

7. The scattering tomography device according to any one of claims 3 to 5, The diffusion coefficient is determined to be a value equal to the mean square error of the measurement positions of the scattered waves.

8. The scattering tomography device according to any one of claims 3 to 5, The diffusion coefficient is determined to be 0.

9. The scattering tomography device according to any one of claims 3 to 5, The diffusion coefficient is determined to be a value greater than 0.

10. The scattering tomography device according to any one of claims 1 to 5, In a three-dimensional space composed of an X coordinate, a Y coordinate, and a Z coordinate, the X coordinate and the Z coordinate of the position of the transmitting antenna element are the same as the X coordinate and the Z coordinate of the position of the receiving antenna element, The scattering field function is determined by [Equation 1], [Equation 1] x represents the X coordinate of the said transmission position and the said reception position, y1 represents the Y coordinate of the said transmission position, y2 represents the Y coordinate of the said reception position, z represents the Z coordinate of the said transmission position and the said reception position, k represents the wave number of the said radio wave, and k in the said scattered field function x , k y1 and k y2 respectively represent the wave numbers related to x, y1 and y2 of the said scattered field function, a(k x , k y1 , k y2 ) is determined by [Mathematical formula 2]. [Equation 2] I represents the index, x, of the transmission position and the reception position where the transmission antenna element and the reception antenna element are located I represents the X coordinate, z, of the transmission position and the reception position where the transmission antenna element and the reception antenna element are located I represents the Z coordinate of the transmission position and the reception position where the transmission antenna element and the reception antenna element are located [Equation 3] indicating Fourier transform imaging related to y1, y2, and t of Φ(x, y1, y2, t) representing the measurement results in x, y1, y2, and t, and t represents time, The imaging function is determined by [Equation 4], [Equation 4] In the imaging function, x, y, and z respectively represent the X coordinate, Y coordinate, and Z coordinate of the imaging object position.

11. A scattering tomography method, The scattering tomography method includes: A transmitting step of transmitting an electric wave from the outside of an object to the inside of the object by a transmitting antenna element; A receiving step of receiving, outside the object, a scattered wave of the electric wave transmitted from the transmitting antenna element to the inside of the object by a receiving antenna element; And A generating step of obtaining a plurality of measurement results in multiple days by obtaining measurement results of the scattered wave every day in multiple days, and generating a reconstructed image according to the plurality of measurement results, the reconstructed image showing continuous elements inside the object, In the step of generating the reconstructed image, For each of the plurality of measurement results, using the measurement result as a boundary condition to calculate a scattering field function, the scattering field function is input with the transmission position of the electric wave and the reception position of the scattered wave and outputs a value representing the amount of the scattered wave at the reception position; For each of the plurality of measurement results, calculating an imaging function, the imaging function is input with an imaging object position and outputs the image intensity of the imaging object position, and the imaging function is a function determined according to the amount output from the scattering field function by inputting the imaging object position as the transmission position and the reception position into the scattering field function; For each of the plurality of measurement results, generating a plurality of intermediate images for the plurality of measurement results by generating an intermediate image according to the imaging function; Generating the reconstructed image by calculating the minimum value of the image intensity at each position in the plurality of intermediate images through an "AND" operation.

Images