JP2018068954A - Magnetic resonance imaging apparatus and image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a magnetic resonance imaging apparatus which, even when a metal piece is contained within a subject, can accurately image the vicinities of the boundaries with the metal piece, with the increased SNR.SOLUTION: The magnetic resonance imaging apparatus comprises: an image acquisition unit 31 which irradiates a subject with a plurality of high-frequency pulses according to a predetermined imaging sequence while changing the frequency band, and acquires a plurality of images based on a plurality of NMR signals obtained from the subject; a pixel determination unit 32 which, based on the pixel value of the corresponding pixel of a pixel of interest in the plurality of images, determines whether the pixel of interest is a pixel in the vicinity of a metal piece representing a tissue around the metal piece; and an image synthesis unit 33 which, when the pixel of interest is determined to be a pixel in the vicinity of the metal piece by the pixel determination unit, uses the pixel values of a predetermined number of pixels in the descending order of pixel values of the corresponding pixels in the plurality of images for performing synthesis with respect to the pixel of interest to generate a synthesized image.SELECTED DRAWING: Figure 1

Description

  The present invention measures nuclear magnetic resonance (hereinafter referred to as “NMR”) signals from hydrogen, phosphorus, etc. in a subject, and images nuclear density distribution, relaxation time distribution, etc. The present invention relates to an apparatus and an image processing method.

  2. Description of the Related Art Conventionally, an MRI apparatus that measures NMR signals generated by nuclear spins constituting a subject, particularly a human tissue, and visualizes the form and function of the head, abdomen, limbs, etc. two-dimensionally or three-dimensionally It has been known. In imaging with an MRI apparatus, a gradient magnetic field is generated, a high frequency pulse (hereinafter referred to as “RF pulse”) is irradiated to the subject, and an NMR signal obtained from the subject is measured by magnetic resonance. An image is acquired by two-dimensional or three-dimensional Fourier transform.

The measured NMR signal is arranged in a data space on a memory called k-space and is called k-space data. In basic MRI imaging, k-space data acquired by one measurement is Fourier-transformed, and a reconstructed image is used for interpretation. In recent years, for various purposes, there is a technique in which a plurality of k-space data is acquired by one measurement, each is subjected to Fourier transform and imaged, and then these images are combined to obtain an image. For example, in Patent Document 1, a plurality of k-space data is acquired while changing the excitation frequency during a single measurement, and a plurality of images obtained are synthesized, so that a metal such as an implant is contained in the subject. Even in some cases, an MRI apparatus that images to the periphery of a metal boundary has been disclosed (hereinafter, such a measurement technique is referred to as “metal measurement”). Patent Document 1 discloses that MIP (Maximum Intensity Projection) or SOS (Sum Of Square) is used when combining a plurality of images acquired for measurement corresponding to metal. Yes.
Here, image synthesis by MIP is shown in equation (1), and image synthesis by SOS is shown in equation (2).

US Pat. No. 7,821,264

  However, when synthesizing a plurality of images acquired by one measurement in the metal correspondence measurement like the MRI apparatus disclosed in Patent Document 1, depending on the pixel value distribution between the plurality of images, MIP or SOS may be used. There is a risk that the vicinity of the metal boundary cannot be imaged correctly, or the SNR (Signal to Noise Ratio) is lowered.

  In general, in metal-corresponding measurement, in a plurality of images acquired by one measurement, tissue signals are divided into a plurality of images for pixels near the metal boundary, and pixels corresponding to background noise are all images of the plurality of images. A random noise signal. When image synthesis is performed for such a plurality of images, there are the following problems.

  For example, when image synthesis is performed by MIP, only the largest of the divided tissue signals is reflected in the synthesized image, so that the synthesized image has fewer tissue signals that should originally be included in pixels near the boundary. . Therefore, in the composite image, the vicinity of the metal boundary is not correctly imaged.

  On the other hand, for example, when image synthesis is performed by SOS, noise signals are added in squares, so that background noise becomes excessively high and the SNR of the synthesized image is lowered. As described above, when performing metal-corresponding measurement, there is a possibility that the image quality of the obtained composite image may be deteriorated due to the distribution of tissue signals and noise signals among a plurality of images.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to correctly image the vicinity of a metal boundary and improve the SNR even when a metal is contained in a subject.

In order to solve the above problems, the present invention provides the following means.
In one embodiment of the present invention, a subject is irradiated with a plurality of high-frequency pulses while changing a frequency band according to a predetermined imaging sequence, and a plurality of images are acquired based on a plurality of NMR signals obtained from the subject. An image acquisition unit; and a pixel determination unit that determines whether the target pixel is a metal peripheral pixel representing a metal peripheral tissue in the subject based on pixel values of corresponding pixels of the target pixel in the plurality of images. When the pixel determination unit determines that the pixel of interest is the metal peripheral pixel, the pixel values of the predetermined number of pixels are used in descending order of the pixel values of the corresponding pixels in the plurality of images. There is provided a magnetic resonance imaging apparatus including an image composition unit that performs composition of pixels to generate a composite image.

  According to the present invention, even when a metal is contained in a subject, the vicinity of the metal boundary can be correctly imaged and the SNR can be improved.

1 is a block diagram showing a schematic configuration of an MRI apparatus according to a first embodiment of the present invention. It is a figure which shows the reference example of the synthesized image acquired by the metal corresponding | compatible measurement process in the MRI apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart of the metal corresponding | compatible measurement process in the MRI apparatus which concerns on the 1st Embodiment of this invention. It is a graph produced | generated by the MRI apparatus which concerns on the 1st Embodiment of this invention, (A) is a graph which shows distribution of the pixel value and image number which were arranged in imaging | photography order, (B) is (A). It is a pixel value distribution obtained by sorting in order of pixel values. (A)-(C) are explanatory drawings for judging the characteristic of a pixel from pixel value distribution obtained from the corresponding pixel of a plurality of images. (A) And (B) is explanatory drawing for setting a threshold value to a metal surrounding pixel, and determining a synthetic | combination number of sheets. (A) And (B) is explanatory drawing for setting a threshold value to the pixel which is not a metal periphery, and determining a synthetic | combination number of sheets. It is a block diagram which shows schematic structure of the MRI apparatus which concerns on the modification of the 1st Embodiment of this invention. It is a graph which shows the example of the weighting coefficient with respect to a synthetic | combination object pixel. It is a flowchart of the metal corresponding | compatible measurement process in the MRI apparatus which concerns on the 2nd Embodiment of this invention. It is an example of a screen which shows the example of the user interface in the MRI apparatus which concerns on the 1st and 2nd embodiment of this invention.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  A magnetic resonance imaging apparatus (hereinafter simply referred to as an MRI apparatus) according to an embodiment of the present invention irradiates a subject with a plurality of high-frequency pulses while changing the frequency band according to a predetermined imaging sequence, and is obtained from the subject. An image acquisition unit that acquires a plurality of images based on a plurality of NMR signals, and the pixel-of-interest in the subject based on pixel values of corresponding pixels of the pixel-of-interest in the plurality of images. A pixel determination unit that determines whether the pixel is a metal peripheral pixel to be represented, and when the pixel determination unit determines that the pixel of interest is the metal peripheral pixel, the pixel values of the corresponding pixels in the plurality of images are in descending order An image composition unit that composes the pixel of interest using pixel values of a predetermined number of pixels and generates a composite image.

  In addition, when the image synthesis unit determines that the target pixel is not the metal peripheral pixel by the pixel determination unit, the pixel value of the pixel in which the corresponding pixel of the target pixel in the plurality of images indicates a pixel value equal to or greater than a predetermined threshold value. And the target pixel is synthesized.

<First Embodiment>
Specifically, as shown in FIG. 1, the MRI apparatus according to the first embodiment of the present invention includes a static magnetic field generation system 2, a gradient magnetic field generation system 3, a transmission system 5, a reception system 6, and a signal processing system 7. A sequencer 4 and a central processing unit (CPU) 8.

  The static magnetic field generation system 2 generates a uniform static magnetic field in the direction perpendicular to the body axis in the space around the subject 1 when the vertical magnetic field method is used, and in the body axis direction when the horizontal magnetic field method is used. A static magnetic field generation system 2 is realized by disposing a permanent magnet type, normal conducting type or superconducting type static magnetic field generating source around the subject 1.

  The gradient magnetic field generation system 3 includes a gradient magnetic field coil 9 that applies gradient magnetic fields in the three-axis directions of X, Y, and Z, which are coordinate systems (stationary coordinate systems) of the MRI apparatus, and a gradient magnetic field that drives each gradient magnetic field coil 9. And a power supply 10. Gradient magnetic fields Gx, Gy, and Gz are applied in the three axial directions of X, Y, and Z by driving the gradient magnetic field power supply 10 of each coil in accordance with a command from the sequencer 4 described later. At the time of imaging, a slice direction gradient magnetic field pulse (Gs) is applied in a direction orthogonal to the slice plane (imaging cross section) to set a slice plane for the subject 1, and the remaining two orthogonal to the slice plane and orthogonal to each other. A phase encoding direction gradient magnetic field pulse (Gp) and a frequency encoding direction gradient magnetic field pulse (Gf) are applied in one direction, and position information in each direction is encoded in the echo signal.

  The sequencer 4 performs control so that a high-frequency magnetic field pulse (hereinafter referred to as “RF pulse”) and a gradient magnetic field pulse are repeatedly applied in a predetermined pulse sequence. The sequencer 4 operates under the control of the CPU 8 described later, and transmits various commands necessary for collecting tomographic image data of the subject 1 to the transmission system 5, the gradient magnetic field generation system 3, and the reception system 6.

  The transmission system 5 irradiates the subject 1 with an RF pulse in order to cause nuclear magnetic resonance to occur in the nuclear spins of the atoms constituting the biological tissue of the subject 1, and includes a high frequency oscillator 11, a modulator 12, and a high frequency. An amplifier 13 and a high frequency coil (transmission coil) 14a on the transmission side are provided. The high-frequency pulse output from the high-frequency oscillator 11 is amplitude-modulated by the modulator 12 at a timing according to a command from the sequencer 4, and after the amplitude-modulated high-frequency pulse is amplified by the high-frequency amplifier 13, the high-frequency pulse is arranged close to the subject 1. By supplying to the high frequency coil 14a, the subject 1 is irradiated with the RF pulse.

  The receiving system 6 detects an echo signal (NMR signal) emitted by nuclear magnetic resonance of nuclear spins constituting the biological tissue of the subject 1, and includes a receiving-side high-frequency coil (receiving coil) 14b, a signal amplifier. 15, a quadrature detector 16, and an A / D converter 17. After the NMR signal of the response of the subject 1 induced by the electromagnetic wave irradiated from the high frequency coil 14a on the transmission side is detected by the high frequency coil 14b arranged close to the subject 1 and amplified by the signal amplifier 15 The signals are divided into two orthogonal signals by the quadrature phase detector 16 at the timing according to the command from the sequencer 4, converted into digital quantities by the A / D converter 17, and sent to the signal processing system 7.

The signal processing system 7 performs various data processing and display and storage of processing results. The CPU 8, a storage device 18 such as a RAM and a ROM, an external storage device 19 such as a magnetic disk and an optical disk, a CRT, etc. Display 20.
The CPU 8 controls the entire MRI apparatus. When data from the receiving system 6 is input to the CPU 8, the CPU 8 executes processing such as signal processing and image reconstruction, and the resulting tomographic image of the subject 1 is obtained. The information is displayed on the display 20 and recorded on the magnetic disk 18 of the external storage device.

  That is, the CPU 8 realizes the functions of the imaging control unit 30, the image acquisition unit 31, the pixel determination unit 31, and the image composition unit 33. These functions can be realized as software by reading and executing a program in the storage device 18 by the CPU, and can also be realized by hardware such as an ASIC.

  The imaging control unit 30 controls the sequencer 4 to control imaging according to an imaging sequence based on imaging conditions input by the input unit 23 described later. In particular, in this embodiment, the imaging control unit 30 obtains a plurality of NMR signals by irradiating a subject while changing a high-frequency pulse in one imaging (measurement) according to a predetermined imaging sequence as a measurement corresponding to a metal. The sequencer 4 is controlled to do so.

The image acquisition unit 31 performs various processes such as reconstruction on the acquired NMR signal. In particular, each of the plurality of images acquired in the metal correspondence measurement is reconstructed to acquire an image.
The pixel determination unit 32 determines to which tissue the target pixel to be processed belongs. Specifically, the pixel determination unit 32 is based on the pixel value of the corresponding pixel of the target pixel in the plurality of images obtained in the metal correspondence measurement, and represents a metal surrounding tissue in which the target pixel is embedded in the subject. It is determined whether it is a peripheral pixel.

  The image synthesizing unit 33 synthesizes a plurality of images obtained in the metal correspondence measurement by the image acquisition unit 31 to generate one synthesized image. At this time, the image composition unit 33 applies the pixel values of a predetermined number of pixels in descending order of the pixel values of the corresponding pixels in the plurality of images for the pixels determined by the pixel determination unit 32 as the metal peripheral pixels. The pixel of interest is synthesized.

  In addition, when the pixel determination unit 32 determines that the target pixel is not a metal peripheral pixel (a pixel far from the metal periphery), the image composition unit 33 determines that the corresponding pixel of the target pixel in a plurality of images is less than a predetermined threshold value. Synthesis is performed by applying a pixel value of a pixel having a high pixel value to generate a pixel value for the pixel of interest. Then, the image composition unit 33 acquires, for example, a single composite image 100 as illustrated in FIG. In FIG. 2, the composite image 100 includes a region 101 indicating metal embedded in the subject, a region 102 indicating metal surrounding tissue, a region 103 away from the metal, and a region 104 indicating background (noise). ing.

The operation unit 25 inputs various control information of the MRI apparatus and control information of processing performed in the signal processing system 7, and includes an input unit 23. As the input unit 23, one or a plurality of input devices such as a mouse, a keyboard, or a trackball can be applied. Further, the input unit 23 receives input of imaging conditions and transmits the input imaging conditions to the CPU 8. Here, the imaging conditions include a site to be imaged, a sequence, a slice thickness, a GAP, an imaging range, and the like.
By disposing the operation unit 25 close to the display 20, the operator can interactively control various processes of the MRI apparatus through the operation unit 25 while looking at the display 20.

  In FIG. 1, the high-frequency coil 14a and the gradient magnetic field coil 9 on the transmission side are opposed to the subject 1 in the static magnetic field space of the static magnetic field generation system 2 into which the subject 1 is inserted. If the horizontal magnetic field method is used, the subject 1 is installed so as to surround it. The high-frequency coil 14b on the receiving side is installed so as to face or surround the subject 1.

  At present, the radionuclide to be imaged by the MRI apparatus is a hydrogen nucleus (proton) which is a main constituent material of the subject as widely used clinically. Information on the spatial distribution of the proton density and the spatial distribution of the relaxation time of the excited state is imaged, thereby imaging the form or function of the human head, abdomen, limbs, etc. two-dimensionally or three-dimensionally.

The metal measurement processing in the MRI apparatus configured as described above will be described with reference to the flowchart of FIG.
First, prior to the start of the metal-corresponding measurement process, the subject is registered in the MRI apparatus. Specifically, the input unit 23 receives input of information related to the subject such as the name, age, and the like of the subject by the operator. The input unit 23 transmits the input subject information to the CPU 8, and the CPU 8 stores the subject information in the storage device 18 or the like, thereby performing subject registration with the MRI apparatus. Then, the input unit 23 receives an imaging condition input related to the metal correspondence measurement by the operator, the CPU 8 receives the imaging condition from the input unit 23, sets an imaging sequence based on the imaging condition, and starts imaging related to the metal correspondence measurement. Is done.

In step S11, the image acquisition unit 31 performs necessary processing such as reconstruction based on a plurality of NMR signals obtained by a pulse sequence that irradiates high-frequency pulses of a plurality of different frequency bands by the reception system 6, Acquire multiple images.
In the next step S12, the pixel determination unit 32 includes pixel values and image numbers in which the corresponding pixels of the target pixel are arranged in the shooting order in the plurality of images acquired in step S11, for example, as illustrated in FIG. Generate a graph showing the distribution of. Furthermore, by sorting FIG. 4A in order of pixel values, for example, a pixel value distribution as shown in FIG. 4B is generated.

  Subsequently, in step S13, the pixel determination unit 32 determines whether or not the half value width of the pixel value distribution is greater than or equal to a predetermined value based on the pixel value distribution of FIG. 4B generated in step S12. . As a result of the determination, if the half-value width is greater than or equal to the predetermined value, the process proceeds to step S14, and if the half-value width is less than the predetermined value, the process proceeds to step S15.

  By determining whether or not the half value width of the pixel value distribution is greater than or equal to a predetermined value in step S13, it is possible to determine whether or not the target pixel is a metal peripheral pixel indicating a metal peripheral structure. Here, as shown in FIG. 5A, the metal surrounding structure has a characteristic that the pixel value of the corresponding pixel gently changes when a plurality of images are acquired while changing the frequency band of the high frequency pulse. On the other hand, pixels that are not metal peripheral pixels, for example, pixels that are away from the metal periphery, as shown in FIG. 5B, only a specific number of images show high pixel values, and pixel values of other corresponding pixels. Indicates a pixel value that is negligibly low. Further, the pixels corresponding to the background (noise) have characteristics that the corresponding pixels all have substantially the same pixel value as shown in FIG.

Therefore, the pixel determination unit 32 can determine whether or not the target pixel is a metal peripheral pixel by determining whether or not the half-value width of the pixel value distribution is equal to or greater than a predetermined value.
Therefore, in the determination in step S13, if the half-value width is greater than or equal to the predetermined value, it is determined that the pixel is a metal peripheral pixel (step S14). If the half-value width is less than the predetermined value, it is not a metal peripheral pixel. Determination is made (step S15).

  In step S16, the image composition unit 33 performs composition on the metal peripheral pixels by applying pixel values of a predetermined number of pixels in descending order of the pixel values of the corresponding pixels in the plurality of images. Specifically, image composition is performed as follows. Select a predetermined number of pixels from the top of the pixel value distribution generated by sorting in order of pixel values of the corresponding pixels, that is, the pixel value distribution generated by sorting in order of pixel values, and apply the lower pixels to the synthesis. Does not apply.

First, the rank of the boundary used for the synthesis process is determined as the threshold value T _order (FIG. _6A ). The number of upper pixels that determine the threshold T _order can be determined empirically as a constant, or can be determined based on a pixel value distribution in the forward direction of the pixel value. In FIG. _6A , with the threshold value _Torder as a boundary, the pixel lower in the pixel value distribution is not applied to the synthesis, and only the upper pixel is applied to the synthesis.

That is, as shown in the following equation (3), this sets the weighting factor to 1.0 for pixels that are greater than or equal to the threshold T _order in the pixel value distribution and 0.0 for the pixels that are less than the threshold T _order . (FIG. 6B). By determining the weighting factor in this way, when the pixel value distribution is generated by sorting in descending order of the pixel values, the lower pixel values are not synthesized, thus preventing the noise signal from being synthesized excessively. Can do.

  Note that, by using, for example, square sum synthesis using the pixel values of the pixels applied to the synthesis determined in this way, image synthesis when the pixel of interest is a metal peripheral pixel is completed.

On the other hand, in step S17, in response to the determination that the target pixel is not a metal peripheral pixel in step S15, an image in which the corresponding pixel of the target pixel in the plurality of images has a pixel value equal to or greater than a predetermined threshold is applied. Image synthesis is performed for the pixel of interest.
For this reason, first, as shown in FIG. 7A, a threshold _{value Tvalue} is determined. The threshold _{value Tvalue} is determined in order to prevent the noise signal from being excessively synthesized by distinguishing the tissue signal from the noise signal. This determination method includes a discriminant analysis method using a histogram created from a measured image, a method using an average value and standard deviation of a background noise region, a method of determining based on a pixel value distribution in a pixel value forward direction, and a simple method There is a method of obtaining from 10% of the maximum pixel value. Further, the threshold _{value Tvalue} can be determined using all the corresponding pixels of the plurality of measured images, or can be determined using a part of the images representing the characteristics of the entire image.

Then, among the corresponding pixels in the plurality of measured images, a pixel whose pixel value is greater than or equal to the threshold _{value Tvalue} is applied to image synthesis. On the other hand, among the corresponding pixels in the plurality of measured images, a pixel whose pixel value is less than the threshold _value Tvalue is not applied to image synthesis. An image applied to composition and an image not applied to composition are as shown in FIG.
In other words, as shown in Equation (4) shown below, a weighting factor to a pixel which indicates the threshold _{T value} or more pixel values 1.0, the weighting factor as 0.0 for pixels indicating the pixel values below the threshold _{T value} or more (FIG. 7B). By determining the weighting factor in this way, an image having a pixel value less than the threshold value is not synthesized, so that it is possible to prevent noise signals from being synthesized excessively.

  Image synthesis in the case where the pixel of interest is not a metal peripheral pixel is completed by performing, for example, square sum synthesis using the pixels applied to the synthesis determined in this way.

  In step S18, based on the synthesis result of the metal peripheral pixels in step S16 and the synthesis result of the pixels that are not metal peripheral pixels in step S17, finally one composite image is generated, and the metal correspondence measurement is terminated.

  As described above, according to the present embodiment, by combining appropriate images according to the characteristics of the target pixel, that is, the region to which the target pixel belongs, it is possible to combine all the images that contribute to the improvement of the image quality. In addition, it is possible to suppress the synthesis of images that may reduce the image quality. Therefore, even when a metal is contained in the subject, the vicinity of the metal boundary can be correctly imaged, and the SNR can be improved.

(Modification)
In the MRI apparatus according to the first embodiment described above, with respect to the metal peripheral pixels, a predetermined number of pixels corresponding to the top of the pixel value distribution generated by sorting the corresponding pixel values in descending order, that is, in order of pixel values. Is applied to composition, and other pixels are not applied to image composition. In addition, for pixels that are not around the metal, an image in which the pixel corresponding to the target pixel has a pixel value equal to or greater than a predetermined threshold is applied to image composition, and a pixel having a pixel value lower than the threshold is not applied to image composition. .

  That is, in all cases, the weighting coefficient for pixels applied to image composition is set to 1.0 and the weighting coefficient for pixels not applied to image composition is set to 0. However, the weighting coefficient can be determined as appropriate. In this modification, an example in which weighting factors are determined as appropriate will be described. For example, as shown in FIG. 8, the central processing unit (CPU) can further include a weight determination unit 34, and the weight determination unit 34 can calculate and determine the weight coefficient.

First, for metal peripheral pixels, the threshold T _order is used as a boundary to determine weighting factors for corresponding pixels in a plurality of images applied to image synthesis. The weighting coefficient of each corresponding pixel is generalized as a function of the sorted pixel value distribution and the threshold value, and can be expressed as the following Expression (5).

但し、ｇは、ソート順と閾値Ｔ_{ｏｒｄｅｒ}を入力したときに対応する重み係数を出力する関数であり、画素値が高い順に並べた画素値分布において上位の領域（組織信号）が大きい重み係数に、下位の領域（雑音信号）が小さい重み係数となるような関数とする。例えば、図９に示すように、画素値が低くなるにつれて階段状に徐々に小さくなるように重み係数を定めることができる。また、以下の式（６）のように表すこともできる。

However, g is a function that outputs a weighting coefficient corresponding to the input of the sort order and the threshold value T _order , and the higher region (tissue signal) in the pixel value distribution arranged in descending order of the pixel value is a weighting factor. The function is such that the lower area (noise signal) is a small weighting factor. For example, as shown in FIG. 9, the weighting factor can be determined so as to gradually decrease stepwise as the pixel value decreases. Moreover, it can also represent like the following formula | equation (6).

このように、閾値Ｔ_{ｏｒｄｅｒ}に基づいて定めた重み係数により重み付けした上で、二乗和合成等の画像合成を行うことにより、組織信号を効率良く合成でき、また雑音信号が過剰に合成されるのを防ぐことができる。

Thus, by weighting with a weighting factor determined based on the threshold T _order and performing image synthesis such as sum of squares synthesis, the tissue signal can be synthesized efficiently, and the noise signal is synthesized excessively. Can be prevented.

In the case of a pixel that is not a metal periphery (far from the metal periphery), the weight coefficient of each corresponding pixel is determined using the pixel value of the corresponding pixel and the threshold _value Tvalue in the plurality of measured images. The weighting coefficient of the corresponding pixel in each image is generalized as a function of the measured pixel value of the image and the threshold _{value Tvalue} , and can be expressed as the following equation (7).

但し、ｆは、計測した画像の画素値と閾値Ｔ_{ｖａｌｕｅ}を入力したときに対応する重み係数を出力する関数であり、画素値の高い領域（組織信号）が大きく、画素値の低い領域（雑音信号）が小さい重み係数となるような関数である。例えば、図９に示すように、画素値が低くなるにつれて階段状に徐々に小さくなるように重み係数を定めることができる。また、以下の式（８）のように表すこともできる。

However, f is a function that outputs a weighting factor corresponding to the input pixel value of the measured image and the threshold _{value Tvalue} , and has a high pixel value region (tissue signal) and a low pixel value region (noise). Signal) becomes a small weighting factor. For example, as shown in FIG. 9, the weighting factor can be determined so as to gradually decrease stepwise as the pixel value decreases. Moreover, it can also represent like the following formula | equation (8).

このように、閾値Ｔ_{ｖａｌｕｅ}に基づいて定めた重み係数により重み付けした上で、二乗和合成等の画像合成を行うことにより、組織信号を効率良く合成でき、また雑音信号が過剰に合成されるのを防ぐことができる。

As described above, by weighting with a weighting factor determined based on the threshold _{value Tvalue} and performing image synthesis such as sum of squares synthesis, the tissue signal can be synthesized efficiently, and noise signals are synthesized excessively. Can be prevented.

<Second Embodiment>
Hereinafter, a second embodiment of the present invention will be described. In the MRI apparatus according to the first embodiment described above, the pixel determination unit 32 determines whether or not the target pixel is a metal peripheral pixel, and the example in which the synthesis method is changed based on the result has been described. In the present embodiment, the pixel determination unit 32 determines whether the target pixel is a background pixel indicating a background region, and includes a region composed of metal peripheral pixels, a tissue region far from the metal periphery, and a region composed of background pixels. Apply a synthesis method suitable for each.

The configuration of the MRI apparatus in the present embodiment is the same as that of the MRI apparatus in the first embodiment described above, and the same applies to processes other than the background pixel determination and the synthesis process for the background pixels. Is omitted.
The metal corresponding measurement process in the MRI apparatus according to the present embodiment will be described with reference to the flowchart of FIG. In the following description, the description of the same process as the metal corresponding measurement process in the MRI apparatus according to the first embodiment will be omitted.

  First, prior to the start of the metal-corresponding measurement process, subject registration is performed in the MRI apparatus. In step S21, the image acquisition unit 31 performs a plurality of processes based on a plurality of NMR signals obtained by imaging related to the metal-corresponding measurement. Get the image. Subsequently, in step S22, a graph showing the distribution of pixel values and image numbers in which the target pixel and corresponding pixels in a plurality of images are arranged in the shooting order is generated (FIG. 4A), and this is further sorted in the pixel value order. Thus, a pixel value distribution is generated (FIG. 4B). In step S23, the pixel determination unit 32 determines whether or not the maximum pixel value exceeds a predetermined threshold among the corresponding pixels in the plurality of images.

  In this determination, if the maximum pixel value does not exceed the predetermined threshold value, the process proceeds to step S24, and if it exceeds, the process proceeds to step S25. As described above, the pixels corresponding to the background (noise) have characteristics that the corresponding pixels all have substantially the same pixel value as shown in FIG. For this reason, in step S24, a pixel determined to have a pixel value indicating a maximum pixel value not exceeding a predetermined threshold is determined as a background pixel. When the pixel determination unit 32 determines that the target pixel is a background pixel, the process proceeds to step S26, and the image composition unit 33 performs maximum value projection for the pixel. That is, the pixel value indicating the maximum value among the pixel values of the plurality of corresponding pixels is set as the pixel value of the target pixel.

  On the other hand, if it is determined in step S23 that the pixel value of the pixel indicating the maximum pixel value has exceeded a predetermined threshold value, in step S25, the pixel value distribution is based on the pixel value distribution in FIG. It is determined whether or not the half-value width is greater than or equal to a predetermined value. As a result of the determination, if the half-value width is greater than or equal to the predetermined value, the process proceeds to step S27 and is determined to be a metal peripheral pixel. If the half-value width is less than the predetermined value, the process proceeds to step S29 and is determined not to be a metal peripheral pixel.

  If it is determined in step S27 that the pixel is a metal peripheral pixel, in step S28, a predetermined number of pixels are applied in descending order of the corresponding pixel values in the plurality of images, and the images are combined. On the other hand, if it is determined in step 29 that the pixel is not a metal peripheral pixel, the process proceeds to step S30, and a pixel of interest corresponding to the pixel of interest having a pixel value equal to or greater than a predetermined threshold is applied from the plurality of images. Perform image composition for. The details of the image composition processing are the same as those in the first embodiment described above, and a description thereof is omitted here.

  In step S31, one composite image is finally generated based on the result of the maximum value projection in step S26, the composite result of the metal peripheral pixels in step S28, and the composite result of the non-metal peripheral pixels in step S30. End metal measurement.

  As described above, according to the present embodiment, by combining appropriate images according to the characteristics of the target pixel, that is, the region to which the target pixel belongs, it is possible to combine all the images that contribute to the improvement of the image quality. In addition, it is possible to suppress the synthesis of images that may reduce the image quality. Therefore, even when a metal is contained in the subject, the vicinity of the metal boundary can be correctly imaged, and the SNR can be improved.

  In the MRI apparatus according to each embodiment described above, the above-described synthesis for each region can be automatically performed. In addition, for example, the synthesis method of each organization can be designated by the user through a user interface as shown in FIG. In this case, the user allocates the combination method described above that seems to be optimal to each organization. This may be specified before measuring the image, but may be combined while confirming the combined result after measuring the image. Thereby, the user can also confirm the composite image while searching for an optimal composite method in the image.

  Further, in the above-described example, the example in which the synthesis method is switched based on the pixel value distribution has been described. However, in addition to the pixel value distribution, information acquired in advance for adjustment purposes, for example, the resonance frequency spectrum shape (height, half It is also possible to estimate the characteristics of the measurement image using the value width), the noise level, etc., and to switch the synthesis method (weighting factor) so that the synthesis result is optimal.

2 ... Static magnetic field generation system, 3 ... Gradient magnetic field generation system, 4 ... Sequencer, 5 ... Transmission system, 6 ... Reception system, 7 ... Signal processing system, 8 ... Central processing unit (CPU), 9 ... gradient coil, 10 ... gradient power supply, 11 ... high frequency oscillator, 12 ... modulator, 13 ... high frequency amplifier, 14a, 14b ... High frequency coil, 15 ... signal amplifier, 16 ... quadrature detector, 17 ... A / D converter, 18 ... storage device, 19 ... external storage device, 20 ... display, DESCRIPTION OF SYMBOLS 23 ... Input part, 25 ... Operation part, 30 ... Imaging control part, 31 ... Image acquisition part, 32 ... Pixel determination part, 33 ... Image composition part, 34 ... Weight determination unit

Claims (7)

An image acquisition unit that irradiates a subject while changing a frequency band with a plurality of high-frequency pulses according to a predetermined imaging sequence, and acquires a plurality of images based on a plurality of NMR signals obtained from the subject;
A pixel determination unit that determines whether the target pixel is a metal peripheral pixel representing a metal peripheral tissue in the subject based on pixel values of corresponding pixels of the target pixel in the plurality of images;
When the pixel determination unit determines that the pixel of interest is the metal peripheral pixel, the pixel of interest using the pixel values of a predetermined number of pixels in descending order of the pixel values of the corresponding pixels in the plurality of images And an image synthesizing unit that generates a synthesized image by synthesizing the magnetic resonance imaging apparatus. The magnetic resonance imaging apparatus according to claim 1.
When the image composition unit determines that the target pixel is not the metal peripheral pixel by the pixel determination unit, the corresponding pixel of the target pixel in the plurality of images has a pixel value equal to or greater than a predetermined threshold value. A magnetic resonance imaging apparatus that synthesizes a pixel of interest using pixel values. The magnetic resonance imaging apparatus according to claim 1 or 2,
The pixel determination unit determines whether the target pixel is a background pixel indicating a background region based on a pixel value of a corresponding pixel of the target pixel in the plurality of images;
When the image composition unit determines that the pixel of interest is a background pixel by the pixel determination unit, a pixel of a pixel in which pixel values of a plurality of corresponding pixels of the pixel of interest in the plurality of images have a maximum value A magnetic resonance imaging apparatus that synthesizes the pixel of interest using a value. The magnetic resonance imaging apparatus according to any one of claims 1 to 3,
A weight determining unit that determines a weighting coefficient for each pixel with respect to an image to be applied when the image is combined by the image combining unit;
The magnetic resonance imaging apparatus in which the image synthesis unit generates a synthesis by applying the weighting factor determined by the weight determination unit. The magnetic resonance imaging apparatus according to claim 4.
The magnetic resonance imaging apparatus, wherein the weight determination unit determines a larger weight coefficient in descending order of pixel values among a plurality of corresponding pixels of the target pixel. The magnetic resonance imaging apparatus according to any one of claims 1 to 5,
The pixel determination unit generates a pixel value distribution in which the pixel values of corresponding pixels in the plurality of images are rearranged in descending order of pixel values for the target pixel, and the target pixel is metal based on the shape of the pixel value distribution. A magnetic resonance imaging apparatus that determines whether a pixel is a peripheral pixel. Irradiating a subject while changing a frequency band with a plurality of high-frequency pulses according to a predetermined imaging sequence, and acquiring a plurality of images based on a plurality of NMR signals obtained from the subject;
Determining whether the target pixel is a metal peripheral pixel representing a metal peripheral tissue in the subject based on pixel values of corresponding pixels of the target pixel in the plurality of images;
When it is determined that the target pixel is the metal peripheral pixel, the target pixel is synthesized using pixel values of a predetermined number of pixels in descending order of the pixel values of the corresponding pixels in the plurality of images. An image processing method comprising: generating a composite image.

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