The present invention relates to an image processing apparatus, a radiation imaging apparatus, an image processing method, and a non-transitory computer readable storage medium.
A radiation imaging apparatus using a flat panel detector (to be abbreviated as “FPD” hereinafter) is widely used as an imaging apparatus used for medical image diagnosis using radiation. The FPD can perform digital image processing on a captured image. Accordingly, various applications have been developed and practiced.
Japanese Patent No. 3476644 discloses, as a method of obtaining an image by an energy subtraction method, an arrangement that is provided with a scattered ray removal structure between a front detector and a rear detector, which are stacked on each other, to obtain, from the rear detector, a radiation image from which scattered rays are removed.
When a radiation image includes scattered rays, the contrast of the radiation image decreases. This can cause a reduction in diagnostic performance. In energy subtraction, the substance decomposition performance with respect to bones, soft tissues, and the like decreases, resulting in difficulty in generating an image with a target substance being separated.
According to the method disclosed in Japanese Patent No. 3476644, a rear detector needs to have a two layer structure composed of a high-energy detector (FPD) and a low-energy detector (FPD). Accordingly, this method requires detectors (FPDs) on at least three layers in total including the front detector, and hence complicates the configuration structure of FPDs and image processing. This can pose problems in terms of, for example, the costs and weights of FPDs.
The present invention provides an image processing technique that can more accurately estimate scattered rays included in a radiation image with a simpler structure and processing.
According to one aspect of the present invention, there is provided an image processing apparatus comprising: a region specifying unit configured to specify a region composed of one substance from radiation images corresponding to a plurality of energies and obtained by irradiating an object with radiation; a pixel value estimation unit configured to obtain an estimated pixel value of the radiation image based on a thickness or density of a substance in the region; and a scattered ray estimation unit configured to estimate a scattered ray included in the radiation image from a difference between a pixel value of the radiation image and the estimated pixel value.
Further features of the present invention will become apparent from the following description of exemplary embodiments with reference to the attached drawings.
accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and, together with the description, serve to explain principles of the invention.
Hereinafter, embodiments will be described in detail with reference to the attached drawings. Note, the following embodiments are not intended to limit the scope of the claimed invention. Multiple features are described in the embodiments, but limitation is not made to an invention that requires all such features, and multiple such features may be combined as appropriate. Furthermore, in the attached drawings, the same reference numerals are given to the same or similar configurations, and redundant description thereof is omitted.
The radiation generating apparatus 104 generates radiation by applying high-voltage pulses to the radiation tube 101 by a user operation on the exposure switch (not shown). Note that the term radiation can include, for example, α-rays, β-rays, and γ-rays, particle rays, and cosmic rays in addition to X-rays. In the first embodiment, although the type of radiation to be used is not specifically limited, X-rays are mainly used for medical image diagnosis. An object 103 is irradiated with radiation generated by the radiation tube 101. Part of the radiation is transmitted through the object 103 and reaches the FPD 102.
The FPD 102 includes a radiation detection unit having a pixel array for generating an image signal corresponding to radiation. The FPD 102 obtains a radiation image by accumulating electric charge based on an image signal and transfers the image to the information processing apparatus 120. The FPD 102 includes a first radiation detection unit 130 and a second radiation detection unit 131 each having a pixel array for generating a signal corresponding to a radiation intensity. The first radiation detection unit 130 and the second radiation detection unit 131 each detect radiation transmitted through the object 103 as an image signal.
The first radiation detection unit 130 and the second radiation detection unit 131 each have an array (two-dimensional region) of pixels that output signals corresponding to incident light. The photoelectric conversion element of each pixel converts radiation converted into visible light by a phosphor into an electrical signal and outputs it as an image signal. The first radiation detection unit 130 and the second radiation detection unit 131 each are configured to obtain an image signal (radiation image) by detecting radiation transmitted through the object 103 in this manner. Of the plurality of radiation detection units, the first radiation detection unit 130 arranged at a position near the radiation tube 101, which generates radiation, generates a low-energy radiation image corresponding to a low energy of a plurality of energies. The second radiation detection unit 131 arranged at a position away from the radiation tube 101 generates a high-energy radiation image corresponding to a high energy compared with a low energy.
The driving unit (not shown) of the FPD 102 outputs an image signal (radiation image) read out in accordance with an instruction from a control unit 105 to the control unit 105. A region specifying unit 110 performs the processing of specifying a region composed of one substance based on radiation images output from the plurality of radiation detection units (the first radiation detection unit 130 and the second radiation detection unit 131) stacked on each other by single irradiation with radiation.
A scattered ray removal grid 132 suppresses scattered rays generated by the object 103 from entering the FPD 102. This embodiment exemplifies the case in which the scattered ray removal grid 132 is arranged between the object 103 and the first radiation detection unit 130. However, this arrangement is not exhaustive, and the scattered ray removal grid 132 may be arranged between the first radiation detection unit 130 and the second radiation detection unit 131.
The information processing apparatus 120 processes information based on a radiation image captured by imaging an object. The information processing apparatus 120 includes the control unit 105, a monitor 106, an operation unit 107, a storage unit 108, an image processing unit 109, and a display control unit 116.
The control unit 105 includes one or a plurality of processors (not shown) and implements various types of control of the information processing apparatus 120 by executing programs stored in the storage unit 108. The storage unit 108 stores image processing results and various types of programs. The storage unit 108 is constituted by, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), and the like. The storage unit 108 can store images output from the control unit 105, images processed by the image processing unit 109, and the calculation results obtained by the image processing unit 109.
The image processing unit 109 processes the radiation image obtained from the FPD 102. The image processing unit 109 includes, as functional components, the region specifying unit 110, a substance density calculation unit 111, a pixel value estimation unit 112, a scattered ray estimation unit 113, and an image generating unit 114. These functional components may be implemented by causing the processor of the control unit 105 to execute predetermined programs or may be implemented by causing one or a plurality of processors of the image processing unit 109 to use programs read from the storage unit 108. The control unit 105, that is, the processor of the image processing unit 109, is formed from, for example, a CPU (Central Processing Unit). The respective components of the image processing unit 109 may be formed from integrated circuits and the like as long as they implement similar functions. The information processing apparatus 120 can be constituted by, as internal components, a graphic control unit such as a GPU (Graphics Processing Unit), a communication unit such as a network card, and input/output control units such as a keyboard and a display or touch panel.
The monitor 106 (display unit) displays the radiation image (digital image) received by the control unit 105 from the FPD 102 and the image processed by the image processing unit 109. The display control unit 116 controls display on the monitor 106 (display unit). The operation unit 107 can input instructions with respect to the image processing unit 109 and the FPD 102, and receives instructions with respect to the FPD 102 via a user interface (not shown).
In the above arrangement, the radiation generating apparatus 104 applies a high voltage to the radiation tube 101 to irradiate the object 103 with radiation. The FPD 102 functions as an obtaining unit to obtain a plurality of radiation images corresponding to a plurality of energies, which are obtained by irradiating the object 103 with radiation. The FPD 102 generates two radiation images with different radiation energies by irradiation with these types of radiation. The radiation images corresponding to the plurality of energies include a low-energy radiation image and a high-energy radiation image generated based on a higher radiation energy than the low-energy radiation image.
In this embodiment, the first radiation detection unit 130 generates a low-energy radiation image IL, and the second radiation detection unit 131 generates a high-energy radiation image IH. In general, the X-rays emitted from the radiation tube 101 has an X-ray spectrum spreading in a wide energy band because the X-rays are generated by bremsstrahlung of an electron beam.
Accordingly, when radiation is transmitted through the first radiation detection unit 130, low-energy components in the X-ray spectrum are absorbed, resulting in beam hardening. As a result, radiation with relatively high energies enters the second radiation detection unit 131.
The region specifying unit 110 specifies a region composed of one substance from radiation images corresponding to a plurality of energies obtained by irradiating an object with radiation. The region specifying unit 110 specifies a portion composed of one substance by using the high-energy radiation image IH and the low-energy radiation image IL. When the object 103 is a person, the object can be roughly separated into two substances, namely, a soft tissue composed of muscle, fat, organ, and the like and bone. A portion where a bone exists includes a soft tissue covering the bone, whereas a portion where no bone exists is composed of a soft tissue. Accordingly, specifying a region where no bone exists can specify a region composed of a soft tissue substance.
The region specifying unit 110 can use various methods as region extraction methods. For example, the region specifying unit 110 can use at least one of region extraction methods including binarization, region expansion, edge detection, and graph cut. Performing machine learning in advance by using many radiation images of the object 103 as teacher data allows the region specifying unit 110 to specify a region composed of one substance by using a region extraction method based on machine learning on the plurality of radiation images obtained by the FPD 102. When radiation images with two different energies are obtained as in this embodiment, generating in advance a bone image by separating a bone makes it possible to accurately execute the above series of processes of the region extraction method.
The substance density calculation unit 111 calculates the thickness or surface density of a soft tissue in the region specified by the region specifying unit 110 by using the high-energy radiation image IH and the low-energy radiation image IL. In this case, the surface density is the product of the thickness and the volume density, and hence the thickness and the surface density (to be also simply referred to as the “density” hereinafter) have equivalent meanings. The substance density calculation unit 111 calculates the thickness or density of a substance (soft tissue) by using a radiation image (the low-energy radiation image IL or the high-energy radiation image IH), of radiation images corresponding to a plurality of energies, which corresponds to one of the energies and the mass attenuation coefficient (μLA or μHA) of the substance (soft tissue) corresponding to one energy. Calculation processing by the substance density calculation unit 111 is based on equations (2) and (3) given below.
The pixel value estimation unit 112 obtains an estimated pixel value of a radiation image based on the thickness or density of a substance (soft tissue) in a region composed of one substance. The pixel value estimation unit 112 calculates estimated pixel values of the high-energy radiation image IH and the low-energy radiation image IL based on the thickness or density of the substance (soft tissue) calculated by the substance density calculation unit 111 and the mass attenuation coefficient of the substance (soft tissue). Calculation processing by the pixel value estimation unit 112 is based on, for example, equations (4) and (5) given blow.
The scattered ray estimation unit 113 estimates a scattered ray included in a radiation image from the difference between a pixel value of a radiation image and an estimated pixel value. The scattered ray estimation unit 113 estimates a scattered ray from a pixel value (measured pixel value) of a radiation image and the difference between an estimated pixel value IHE of the high-energy radiation image IH and an estimated pixel value ILE of the low-energy radiation image IL calculated by the pixel value estimation unit 112. Estimation processing by the scattered ray estimation unit 113 is based on equations (6) and (7) given below.
The image generating unit 114 generates images (a bone image indicating the density of the bone and a soft tissue image indicating the density of the soft tissue) upon reducing scattered rays from radiation images. Processing by the image generating unit 114 is based on, for example, equations (8) to (11) given below.
Processing by the image processing unit 109 according to the first embodiment will be described in detail next with reference to the flowchart shown in
In steps S201 to S205, the image processing unit 109 generates a soft tissue image indicating the density of the soft tissue in 3c of
In this case, 3a of
(Processing by Region Specifying Unit 110)
In step S201, the region specifying unit 110 calculates a bone image dB in 3d of
In this case, the bone image dB indicates a bone density, with the unit being g/cm2. In equation (1), the suffixes H and L respectively represent a high energy and a low energy, and the suffices A and B respectively represent substances to be separated (for example, A represents a soft tissue, and B represents a bone). In this case, the soft tissue and the bone are exemplified as substances to be separated. However, they are not exhaustive and arbitrary substances can be used. In this equation, μHA is the mass attenuation coefficient of the soft tissue at a high energy, μFIB is the mass attenuation coefficient of the bone at a high energy, μLA is the mass attenuation coefficient of the soft tissue at a low energy, μHB is the mass attenuation coefficient of the bone at low energy, x represents a pixel position in the image in the horizontal direction, and y represents a pixel position in the image in the vertical direction.
The bone image dB in 3d of
In this embodiment, the bone image dB is used to facilitate region extraction. However, a bone region and a region composed of only a soft tissue may be specified from the high-energy radiation image IH and the low-energy radiation image IL using a known technique.
(Processing by Substance Density Calculation Unit 111)
In step S202, the substance density calculation unit 111 calculates a soft tissue image dA in a region composed of only a soft tissue specified in step S201 using the low-energy radiation image IL according to equation (2) given below.
Since it is known that the region specified in step S201 is a region composed of a soft tissue, simple calculation like equation (2) holds. In addition, since the first radiation detection unit 130 is in contact with the scattered ray removal grid 132 in
As described above, when the scattered ray removal grid 132 is arranged between the first radiation detection unit 130 and the second radiation detection unit 131, the substance density calculation unit 111 can calculate the soft tissue image dA by using equation (3).
(Processing by Pixel Value Estimation Unit 112)
In step S203, the pixel value estimation unit 112 calculates the estimated pixel value IHE of the high-energy radiation image in the soft tissue according to equation (4) given below. The pixel value estimation unit 112 calculates an estimated pixel value of the high-energy radiation image in the substance (soft tissue) based on the soft tissue image dA (equation (2)) indicating the density of the substance (soft tissue), calculated based on the low-energy radiation image IL, and the mass attenuation coefficient μHA of the substance (soft tissue) at the high energy.
In this case, since dA(x, y) is calculated based on equation (2) from the low-energy radiation image IL that approximately suffer little influence of scattered rays, the estimated pixel value IHE(x, y) can also be considered to be a high-energy radiation image on which the influence of scattered rays is suppressed.
When the scattered ray removal grid 132 is arranged between the first radiation detection unit 130 and the second radiation detection unit 131, the pixel value estimation unit 112 calculates the estimated pixel value ILE of the low-energy radiation image according to equation (5) given below. The pixel value estimation unit 112 calculates an estimated pixel value of the low-energy radiation image of the substance (soft tissue) based on the soft tissue image dA (equation (3)) indicating the density of the substance (soft tissue) calculated based on the high-energy radiation image IH and the mass attenuation coefficient μLA of the substance (soft tissue) at the low energy.
(Processing by Scattered Ray Estimation Unit 113)
In step S204, the scattered ray estimation unit 113 calculates a scattered ray SH of the high-energy radiation image according to equation (6) given below. The scattered ray estimation unit 113 calculates the scattered ray SH of the high-energy radiation image of the substance (soft tissue) based on the difference between a measured pixel value IH(x, y) of the high-energy radiation image IH and the estimated pixel value IHE(x, y) of the high-energy radiation image IH.
When the scattered ray removal grid 132 is arranged between the first radiation detection unit 130 and the second radiation detection unit 131, a scattered ray SL of the low-energy radiation image is calculated according to equation (7). That is, the scattered ray estimation unit 113 calculates the scattered ray SL of the low-energy radiation image of the soft tissue based on the difference between a measured pixel value IL(x, y) of the low-energy radiation image IL and an estimated pixel value ILE(x, y) of the low-energy radiation image IL. In this case, the pixel value estimation unit 112 can calculate the estimated pixel value ILE(x, y) of the low-energy radiation image IL from the product of the mass attenuation coefficient μLA of the soft tissue at the low energy and dA(x, y) in the same manner as indicated by equation (4).
An estimated scattered ray SH(x, y) of the high-energy radiation image or an estimated scattered ray SL(x, y) of the low-energy radiation image is a scattered ray concerning a region composed of only the soft tissue. In the human body, in regions other than regions dominated by bones like the head portion, the areas of the bones are relatively small like the collarbones 303 and the vertebrae 304 in 3d of
(Processing by Image Generating Unit 114)
In step S205, the image generating unit 114 generates images (a bone image and a soft tissue image) obtained by reducing scattered rays from a radiation image. The image generating unit 114 generates an image (soft tissue image) indicating the density of the substance (soft tissue) and an image (bone image) indicating the densities of a plurality of substances (bones) constituting the object by reducing scattered rays from the radiation images by using the scattered rays estimated by the processing (step S204) performed by the scattered ray estimation unit 113.
The image generating unit 114 can calculate a scattered-ray-reduced bone image dBE(x, y) indicating the density of the bone by using a scattered ray S′H(x, y) of the high-energy radiation image or S′L(x, y) of the low-energy radiation image based on equation (8) or (9), which is estimated in the bone region. In this case, equation (8) represents the bone image dBE(x, y) which is obtained by reducing the scattered ray S′H(x, y) of the high-energy radiation image from the high-energy radiation image IH(x, y) and indicates the density of the bone. Equation (9) represents the bone image dBE(x, y) which is obtained by reducing the scattered ray S′L(x, y) of the low-energy radiation image from the low-energy radiation image IL(x, y).
The image generating unit 114 can calculate a scattered-ray-reduced soft tissue image dBA(x, y) indicating the density of the soft tissue by using the scattered ray SH(x, y) or SL(x, y), calculated according to equation (6) or (7), based on equation (10) or (11) given below. Equation (10) represents the soft tissue image dBE(x, y) which is obtained by reducing the scattered ray SH(x, y) of the high-energy radiation image from the high-energy radiation image IH(x, y) and indicates the density of the soft tissue. Equation (11) represents the soft tissue image dBE(x, y) which is obtained by reducing the scattered ray SL(x, y) of the low-energy radiation image from the low-energy radiation image IL(x, y) and indicates the density of the soft tissue.
The scattered ray removal grid 132 used in the imaging experiments is a cross grid having a focal length of 110 cm, a lattice density of 52/cm, and a lattice ratio of 24:1. As shown in
In
According to the standard for approval of X-ray bone density measuring apparatuses (Apr. 1, 2005, Pharmaceutical and Food Safety Bureau Notification No. 0401050), the variation coefficient of body thickness dependence is required to be 2% or less. The variation coefficient (4b of
In
As described above, according to the first embodiment, a soft tissue image and a bone image separated with higher accuracy can be generated by estimating scattered rays in an image obtained by energy subtraction and reducing the estimated scattered rays. In addition, a bone density can be calculated with higher accuracy.
The first embodiment has exemplified the case in which the FPD 102 is formed by stacking the first radiation detection unit 130 and the second radiation detection unit 131. The second embodiment will exemplify a case in which an FPD 502 (radiation detector) includes one radiation detection unit 530, as shown in
According to the first embodiment, the first radiation detection unit 130 and the second radiation detection unit 131 respectively obtain the low-energy radiation image IL and the high-energy radiation image IH by using the beam hardening effect. However, even when the FPD 502 includes only one radiation detection unit 530 as in the second embodiment, a low-energy radiation image IL and a high-energy radiation image IH can be obtained by irradiating an object with radiation twice upon changing the tube voltage of a radiation tube 101. In this case, a region specifying unit 110 performs the processing of specifying a region composed of one substance by irradiating an object with radiation a plurality of times with different tube voltages based on a plurality of radiation images (the low-energy radiation image IL and the high-energy radiation image IH) output from the one radiation detection unit 530.
In this case, the tube voltage can be changed within an allowable range of the radiation tube 101. In general, energy subtraction is known to increase the substance decomposition performance and the SN of separated images with an increase in energy difference. The dose of radiation that is transmitted through an object and reaches the FPD 502 decreases with a decrease in tube voltage. Accordingly, the second embodiment is advantageous over the first embodiment in that the difference between high and low energies of radiation can be increased, and imaging conditions such as a tube voltage, a tube current, and a pulse width can be individually selected.
The FPD 502 is constituted by only one radiation detection unit 530 and hence has an advantage in suppressing the cost and weight. On the other hand, the second embodiment differs from the first embodiment in that body motion due to the respiration, pulsation, and the like of an object can have some influence because imaging is required to be performed twice.
Processing by an image processing unit 109 according to the second embodiment will be described in detail with reference to the flowchart of
In steps S201 to S605 described below, the image processing unit 109 generates the substance decomposition image (soft tissue image) in 3c of
(Processing by Region Specifying Unit 110)
In step S201, the region specifying unit 110 specifies a region composed of only a soft tissue (specifying of a soft tissue region). The specifying of the soft tissue region in step S201 is the same as the processing by the region specifying unit 110 described above in the first embodiment.
(Processing by Substance Density Calculation Unit 111)
In step S602, the substance density calculation unit 111 calculates a soft tissue image dA of the region composed of only the soft tissue specified in step S201 by using the low-energy radiation image IL according to equation (12).
Since it is known that this region is composed of only the soft tissue, a simple calculation like equation (12) holds. In the second embodiment, the low-energy radiation image IL is often captured by imaging at a sufficiently low tube voltage as compared with the high-energy radiation image IH. In general, scattered rays generated by low-energy radiation and caused by an object tend to have large scattering angles, and hence a scattered ray removal grid 532 removes scattered rays more effectively. Accordingly, the low-energy radiation image IL is considered to be sufficiently subjected to the removal of scattered rays as compared with the high-energy radiation image IH, and hence is approximately considered to suffer little influence of scattered rays.
(Processing by Pixel Value Estimation Unit 112)
In step S603, the pixel value estimation unit 112 calculates the estimated pixel value IHE of the high-energy radiation image of the soft tissue according to equation (13).
In this case, dA(x, y) is calculated from the low-energy radiation image IL when the influence of scattered rays is approximately small, and hence an estimated pixel value IHE(x, y) can also be considered to be a high-energy radiation image on which the influence of scattered rays is suppressed.
(Processing by Scattered Ray Estimation Unit 113)
In step S604, a scattered ray estimation unit 113 calculates a scattered ray SH of the high-energy radiation image according to equation (14). The scattered ray estimation unit 113 calculates the scattered ray SH of the high-energy radiation image of the soft tissue based on the difference between the measured pixel value IH(x, y) of the high-energy radiation image IH and the estimated pixel value IHE(x, y) of the high-energy radiation image IH.
A scattered ray S′H(x, y) of an energy radiation image estimated in this case is a scattered ray concerning a region composed of only a soft tissue. However, In the human body, in regions other than regions dominated by bones like the head portion, the areas of the bones are relatively small like collarbones 303 and vertebrae 304 in 3d of
(Processing by Image Generating Unit 114)
In step S605, an image generating unit 114 can calculate a bone image dBE(x, y) which is obtained upon reducing scattered rays and indicates the density of the bone based on equation (15) by using a scattered ray S′H(x, y) of a high-energy radiation image which is estimated in the bone region. In this case, equation (15) is the bone image dBE(x, y) indicating the density of the bone which is obtained by reducing the scattered ray S′H(x, y) of the high-energy radiation image from the high-energy radiation image IH(x, y).
The image generating unit 114 can also calculate the soft tissue image dBE(x, y) which is obtained upon reducing scattered rays and indicates the density of the soft tissue based on equation (16) using the scattered ray SH(x, y) calculated by equation (14). Equation (16) is the soft tissue image dBE(x, y) which is obtained upon reducing the scattered ray SH(x, y) of the high-energy radiation image from the high-energy radiation image IH(x, y) and indicates the density of the soft tissue.
In the imaging experiments according to this embodiment, the sensor surface distance dependence of bone images indicating bone densities was checked while the distance (to be referred to as the sensor surface distance hereinafter) between the radiation detection unit 530 and the object 103 was changed to 10 cm, 12.5 cm, and 15 cm.
In
According to the standard for approval of X-ray bone density measuring apparatuses (Apr. 1, 2005, Pharmaceutical and Food Safety Bureau Notification No. 0401050), the variation coefficient of body thickness dependence is required to be 2% or less. The variation coefficient (7a of
In
As described above, according to the second embodiment, a soft tissue image and a bone image separated with higher accuracy can be generated by estimating scattered rays in an image obtained by energy subtraction and reducing the estimated scattered rays. In addition, a bone density can be calculated with higher accuracy.
According to each embodiment of the present invention, it is possible to more accurately estimate scattered rays included in a radiation image. This can generate a soft tissue image and a bone image separated with higher accuracy by estimating scattered rays in an image obtained in energy subtraction and reducing the estimated scattered rays.
Embodiment(s) of the present invention can also be realized by a computer of a system or apparatus that reads out and executes computer executable instructions (e.g., one or more programs) recorded on a storage medium (which may also be referred to more fully as a ‘non-transitory computer-readable storage medium’) to perform the functions of one or more of the above-described embodiment(s) and/or that includes one or more circuits (e.g., application specific integrated circuit (ASIC)) for performing the functions of one or more of the above-described embodiment(s), and by a method performed by the computer of the system or apparatus by, for example, reading out and executing the computer executable instructions from the storage medium to perform the functions of one or more of the above-described embodiment(s) and/or controlling the one or more circuits to perform the functions of one or more of the above-described embodiment(s). The computer may comprise one or more processors (e.g., central processing unit (CPU), micro processing unit (MPU)) and may include a network of separate computers or separate processors to read out and execute the computer executable instructions. The computer executable instructions may be provided to the computer, for example, from a network or the storage medium. The storage medium may include, for example, one or more of a hard disk, a random-access memory (RAM), a read only memory (ROM), a storage of distributed computing systems, an optical disk (such as a compact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, a memory card, and the like.
While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.
Number | Date | Country | Kind |
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2019-205686 | Nov 2019 | JP | national |
This application is a continuation of International Patent Application No. PCT/JP2020/039232 filed on Oct. 19, 2020, which claims priority to and the benefit of Japanese Patent Application No. 2019-205686 filed on Nov. 13, 2019, the entire disclosures of which are incorporated herein by reference.
Number | Date | Country | |
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Parent | PCT/JP2020/039232 | Oct 2020 | US |
Child | 17726596 | US |