JP6715165B2 - Magnetic resonance imaging apparatus and image processing method - Google Patents

Description

The present invention measures nuclear magnetic resonance (hereinafter, referred to as “NMR”) signals from hydrogen, phosphorus, and the like in a subject, and nuclear magnetic resonance imaging (hereinafter, referred to as “nucleus density distribution” or “relaxation time distribution”). An apparatus and an image processing method.

Conventionally, an MRI apparatus that measures an NMR signal generated by a nuclear spin that constitutes a tissue of a subject, in particular, a human body, and two-dimensionally or three-dimensionally images the shape and function of the head, abdomen, limbs, etc. It has been known. In imaging with an MRI apparatus, a gradient magnetic field is generated, a subject is irradiated with a high-frequency pulse (hereinafter referred to as “RF pulse”), and magnetic resonance is performed to measure an NMR signal obtained from the subject. An image is acquired by performing a two-dimensional or three-dimensional Fourier transform.

The measured NMR signal is arranged in a data space on the memory called k-space and is called k-space data. In basic MRI imaging, the k-space data acquired by one measurement is Fourier transformed and the reconstructed image is used for image interpretation. In recent years, for various purposes, there is a technique in which a plurality of pieces of k-space data are acquired by one measurement, Fourier-transformed into images, and then these images are combined to obtain an image. For example, in Patent Document 1, by acquiring a plurality of k-space data while changing the excitation frequency during one measurement and synthesizing a plurality of the obtained images, a metal such as an implant is detected in the subject. Even in some cases, an MRI apparatus has been disclosed that images even around the boundary of a metal (hereinafter, such a measurement technique is referred to as "metal-compatible measurement"). Further, Patent Document 1 discloses that MIP (Maximum Intensity Projection) or SOS (Sum Of Square) is used when synthesizing a plurality of images acquired for metal correspondence measurement. There is.
Here, the image composition by MIP is shown in Expression (1), and the image composition by SOS is shown in Expression (2).

U.S. Pat. No. 7,821,264

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

Generally, in the metal correspondence measurement, in a plurality of images acquired by one measurement, the pixel near the metal boundary is divided into a plurality of images due to the influence of the metal, and the pixel corresponding to the background noise is all the images of the plurality of images. Results in a random noise signal. The following problems occur when performing image synthesis on such a plurality of images.

For example, when image synthesis is performed by MIP, only the largest one of the divided tissue signals is reflected in the synthesized image, so that the synthesized image has less 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, the noise signal is squared and added, so that the background noise becomes an excessively high signal and the SNR of the synthesized image decreases. As described above, when performing the metal correspondence measurement, the image quality of the obtained combined image may be deteriorated due to the distribution of the tissue signal and the noise signal among the 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 included in the subject.

In order to solve the above problems, the present invention provides the following means.
One embodiment of the present invention irradiates a subject with a plurality of high-frequency pulses while changing a frequency band according to a predetermined imaging sequence, and acquires a plurality of images 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 the 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 a predetermined number of pixels are used in descending order of the pixel values of corresponding pixels in the plurality of images. Provided is a magnetic resonance imaging apparatus including an image combining unit that combines pixels to generate a combined image.

According to the present invention, even when a subject contains a metal, it is possible to correctly image the vicinity of the metal boundary and improve the SNR.

It is a block diagram which shows schematic structure of the MRI apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the reference example of the synthetic|combination image acquired by the metal corresponding 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 the distribution of the pixel value arranged in order of imaging, and an image number, (B) shows (A). It is a pixel value distribution obtained by sorting in order of pixel value. (A)-(C) is explanatory drawing for judging the characteristic of a pixel from the pixel value distribution obtained from the corresponding pixel of a some image. (A) And (B) is explanatory drawing for setting a threshold value to a metal peripheral pixel and determining the composite number. (A) And (B) is explanatory drawing for setting a threshold value to the pixel which is not a metal periphery, and determining the composite number. 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 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. 6 is a screen example showing an example of a user interface in the MRI apparatus according to the first and second embodiments of the present invention.

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

A magnetic resonance imaging apparatus according to an embodiment of the present invention (hereinafter, simply referred to as an MRI apparatus) irradiates a subject with a plurality of high-frequency pulses while changing a frequency band according to a predetermined imaging sequence, and obtains from the subject. An image acquisition unit that acquires a plurality of images based on a plurality of NMR signals and a pixel value of a corresponding pixel of a target pixel in the plurality of images, the target pixel detects a metal peripheral tissue in the subject. A pixel determining unit that determines whether the pixel is a metal peripheral pixel represented, and when the pixel determining 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 synthesizing unit that synthesizes the target pixel using pixel values of a predetermined number of pixels to generate a synthetic image.

In addition, when the pixel determining unit determines that the target pixel is not the metal peripheral pixel, the image combining unit determines the pixel value of the pixel in which the corresponding pixel of the target pixel in the plurality of images has a pixel value equal to or more than a predetermined threshold value. The target pixel is synthesized by using this.

<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 space around the subject 1 in the direction orthogonal to the body axis in the vertical magnetic field system, and in the body axis direction in the horizontal magnetic field system. The static magnetic field generation system 2 is realized by disposing a static magnetic field generation source of a permanent magnet type, a normal conduction type or a superconducting type around the subject 1.

The gradient magnetic field generation system 3 includes a gradient magnetic field coil 9 that applies a gradient magnetic field in the three axis directions of X, Y, and Z, which is a coordinate system (stationary coordinate system) of the MRI apparatus, and a gradient magnetic field that drives each gradient magnetic field coil 9. And a power supply 10. By driving the gradient magnetic field power supply 10 of each coil according to a command from the sequencer 4 which will be described later, the gradient magnetic fields Gx, Gy, Gz are applied in the three axial directions of X, Y, Z. 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 the slice plane for the subject 1, and the remaining 2 orthogonal to the slice plane and mutually orthogonal to each other. A phase encode direction gradient magnetic field pulse (Gp) and a frequency encode direction gradient magnetic field pulse (Gf) are applied in one direction to encode the position information in each direction in the echo signal.

The sequencer 4 controls to repeatedly apply a high frequency magnetic field pulse (hereinafter referred to as “RF pulse”) and a gradient magnetic field pulse in a predetermined pulse sequence. The sequencer 4 operates under the control of the CPU 8 to be 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 in the nuclear spins of the atoms forming the biological tissue of the subject 1, and includes a high-frequency oscillator 11, a modulator 12, and a high frequency wave. 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 the timing according to the command from the sequencer 4, and the amplitude-modulated high-frequency pulse is amplified by the high-frequency amplifier 13 and then arranged in the vicinity of the subject 1. The RF pulse is applied to the high-frequency coil 14a to irradiate the subject 1 with the RF pulse.

The reception system 6 detects an echo signal (NMR signal) emitted by nuclear magnetic resonance of nuclear spins that form the biological tissue of the subject 1, and includes a high-frequency coil (reception coil) 14b on the reception side and 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 emitted from the high-frequency coil 14 a on the transmission side is detected by the high-frequency coil 14 b 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 instructed by the sequencer 4, each of which is converted into a digital amount by the A/D converter 17 and sent to the signal processing system 7.

The signal processing system 7 performs various types of data processing and displays and saves processing results, and includes a 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, and a CRT. And a display 20 of.
The CPU 8 controls the entire MRI apparatus, and 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 a tomographic image of the subject 1 as a result thereof is obtained. It is displayed on the display 20 and recorded on the magnetic disk 18 or the like 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 synthesis unit 33. These functions can be realized as software by reading and executing the program in the storage device 18 by the CPU, or can be realized by hardware such as ASIC.

The imaging control unit 30 controls the sequencer 4 to control imaging according to an imaging sequence based on the imaging conditions input by the input unit 23 described later. In particular, in this embodiment, the imaging control unit 30 acquires a plurality of NMR signals by irradiating the subject while changing the high-frequency pulse in a single imaging (measurement) according to a predetermined imaging sequence in the present embodiment, as metal-compatible measurement. 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, the images are acquired by performing reconstruction for each of the plurality of images acquired in the metal correspondence measurement.
The pixel determination unit 32 determines to which tissue the target pixel to be processed belongs. Specifically, the pixel determination unit 32, based on the pixel value of the corresponding pixel of the target pixel in the plurality of images obtained in the metal correspondence measurement, the target pixel is a metal representing the metal peripheral tissue embedded in the subject. It is determined whether it is a peripheral pixel.

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

Further, when the pixel determination unit 32 determines that the pixel of interest 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 pixel of interest in a plurality of images is higher than a predetermined threshold value. Combining is performed by applying the pixel value of the pixel having a high pixel value to generate the pixel value of the target pixel. Then, the image composition unit 33 acquires a single composite image 100 as shown in FIG. 2, for example. In FIG. 2, the composite image 100 includes a region 101 showing a metal embedded in the subject, a region 102 showing a metal peripheral tissue, a region 103 separated from the metal, and a region 104 showing a background (noise). ing.

The operation unit 25 is for inputting various control information of the MRI apparatus and control information of processing performed by 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 in combination. In addition, the input unit 23 accepts the input of the imaging condition and transmits the input imaging condition to the CPU 8. Here, the imaging conditions include a part to be imaged, a sequence, a slice thickness, 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 via the operation unit 25 while looking at the display 20.

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

At present, the nuclides to be imaged by the MRI apparatus are hydrogen nuclei (protons), which are the main constituents of the subject, as clinically popular. By imaging the information on the spatial distribution of the proton density and the spatial distribution of the relaxation time of the excited state, the shape or function of the human head, abdomen, limbs, etc. is two-dimensionally or three-dimensionally imaged.

The metal corresponding measurement process 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-compatible measurement process, the subject is registered in the MRI apparatus. Specifically, the input unit 23 receives an input of information relating to the subject such as the name and age 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 to register the subject in the MRI apparatus. Then, the input unit 23 receives the input of the imaging condition related to the metal compatibility measurement by the operator, the CPU 8 receives the imaging condition from the input unit 23, sets the imaging sequence based on the imaging condition, and starts the imaging related to the metal compatibility measurement. To be done.

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

Subsequently, in step S13, the pixel determination unit 32 determines whether or not the half value width of the pixel value distribution is equal to or larger than 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-width is equal to or larger than the predetermined value, the process proceeds to step S14, and if the half-width is less than the predetermined value, the process proceeds to step S15.

By determining in step S13 whether or not the half value width of the pixel value distribution is equal to or larger than a predetermined value, it is possible to determine whether or not the pixel of interest is a metal peripheral pixel indicating a metal peripheral tissue. Here, as shown in FIG. 5A, the metal peripheral tissue has a characteristic that the pixel value of the corresponding pixel changes gently when a plurality of images are acquired while changing the frequency band of the high frequency pulse. On the other hand, for a pixel that is not a metal peripheral pixel, for example, a pixel distant from the metal peripheral, as shown in FIG. 5B, only a few specific images show high pixel values, and the pixel values of the corresponding pixels other than this. Indicates a pixel value that is negligible. In addition, as for the pixel corresponding to the background (noise), as shown in FIG. 5C, the corresponding pixels have almost the same pixel value.

Therefore, the pixel determination unit 32 can determine whether or not the pixel of interest is a metal peripheral pixel by determining whether or not the half value width of this pixel value distribution is equal to or larger than a predetermined value.
Therefore, in the determination in step S13, if the half width is equal to or larger than the predetermined value, it is determined to be a metal peripheral pixel (step S14), and if the half width is less than the predetermined value, it is not a metal peripheral pixel. It is determined (step S15).

In step S16, the image combining unit 33 applies the pixel values of a predetermined number of pixels in the order of increasing pixel value of the corresponding pixel in the plurality of images to the metal peripheral pixels to perform the combining. Specifically, image synthesis is performed as follows. A predetermined number of pixels are selected from the upper pixels of the pixel value distribution generated by sorting the pixel values of the corresponding pixels in the descending order, that is, the pixel values are sorted, and are applied to the combining, and the lower pixels are combined. Does not apply.

First, the order of boundaries used in the combining process is determined as the threshold T _order (FIG. _6A ). The number of higher- _order pixels that define the threshold T _order can be empirically determined as a constant, or can be determined based on the pixel value distribution in the pixel value forward direction. Then, in FIG. _6A , with the threshold T _order as a boundary, the pixels in the lower _order of the pixel value distribution are not applied to the composition, but only the pixels in the upper order are applied to the composition.

That is, as shown in Equation (3) below, which is set to 1.0 the weighting factors to the pixel to be the threshold value _{T order} or higher in the pixel value distribution, the weight coefficient for the pixels less than the threshold _{T order} 0.0 This is equivalent to that (FIG. 6(B)). By determining the weighting coefficient in this way, when the pixel value distribution is generated by sorting the pixels in descending order of pixel value, the pixel values in the lower order are not combined, and thus noise signals are prevented from being excessively combined. You can

It should be noted that, by using the pixel values of the pixels to be applied to the combination determined in this way, for example, the sum of squares combination is performed, the image combination when the target pixel is a metal peripheral pixel is completed.

On the other hand, in step S17, in response to the determination that the pixel of interest is not the metal peripheral pixel in step S15, the image in which the corresponding pixel of the pixel of interest of the plurality of images has a pixel value of a predetermined threshold value or more is applied. Image composition is performed for the pixel of interest.
Therefore, first, as shown in FIG. 7A, the threshold value T _value is determined. The threshold value T _value 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 is a discriminant analysis method that uses a histogram created from measured images, a method that uses the average value and standard deviation of the background noise area, a method that is determined based on the pixel value distribution in the 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 T _value can be determined by using all the corresponding pixels of the measured multiple images, or can be determined by using a part of the images showing the characteristics of the entire image.

Then, among the corresponding pixels in the plurality of measured images, the pixel having the pixel value equal to or _larger than the threshold value T _value is applied to the image combination. On the other hand, among the corresponding pixels in the plurality of measured images, the pixel whose pixel value is less than the threshold value T _value is not applied to the image combination. The image applied to the composition and the image not applied to the 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 It is equivalent to being present (FIG. 7(B)). By determining the weighting coefficient in this way, an image having a pixel value less than the threshold value is not combined, and thus it is possible to prevent the noise signal from being excessively combined.

By performing, for example, the sum of squares combination using the pixels applied to the combination determined in this way, the image combination when the target pixel is not a metal peripheral pixel is completed.

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

As described above, according to the present embodiment, by appropriately synthesizing images according to the characteristics of the pixel of interest, that is, the region to which the pixel of interest belongs, it is possible to synthesize images that contribute to the improvement of image quality without fail. At the same time, it is possible to suppress the synthesis of images that may deteriorate the image quality. Therefore, even when the subject contains a metal, the vicinity of the metal boundary can be correctly imaged and the SNR can be improved.

(Modification)
In the MRI apparatus according to the above-described first embodiment, regarding the metal peripheral pixels, a predetermined number of pixels that are higher in the pixel value distribution generated by sorting the pixel values of the corresponding pixels, that is, in the pixel value order. Is applied to the composition, and the other pixels are not applied to the image composition. In addition, for pixels that are not on the metal periphery, an image in which the corresponding pixel of the pixel of interest has a pixel value that is equal to or greater than a predetermined threshold is applied to image composition, and pixels that have pixel values lower than the threshold are not applied to image composition. ..

That is, in both cases, the weighting factor for pixels applied to image synthesis is set to 1.0 and the weighting factor for pixels not applied to image synthesis is set to 0, but the weighting factor can be appropriately determined. In this modified example, an example in which the weighting factor is appropriately determined will be described. For example, as shown in FIG. 8, the central processing unit (CPU) may further include a weight determining unit 34, and the weight determining unit 34 may calculate and determine the weight coefficient.

First, with respect to metal peripheral pixels, a weighting coefficient for corresponding pixels in a plurality of images applied to image synthesis is determined with the threshold T _order as a boundary. The weighting factor 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 corresponding weighting coefficient when the sorting order and the threshold T _order are input, and in the pixel value distribution arranged in descending order of the pixel value, the upper area (tissue signal) becomes a large weighting coefficient. , And the lower area (noise signal) has a smaller weighting coefficient. For example, as shown in FIG. 9, the weighting factor can be set so that the pixel value gradually decreases in a stepwise manner as the pixel value decreases. It can also be expressed as the following 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。

As described above, the tissue signal can be efficiently combined and the noise signal can be excessively combined by performing the image combining such as the sum-of-squares combining after weighting with the weighting factor determined based on the threshold value T _order . Can be prevented.

Further, in the case of a pixel that is not on the periphery of the metal (far from the periphery of the metal), the weighting factor of each corresponding pixel is determined using the pixel value of the corresponding pixel in the plurality of measured images and the threshold value T _value . The weighting factor of the corresponding pixel in each image is generalized as a function of the pixel value of the measured image and the threshold value T _value , and can be expressed as in equation (7) below.

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 coefficient corresponding to the pixel value of the measured image and the threshold value T _value , and a region having a high pixel value (tissue signal) is large and a region having a low pixel value (noise Signal) has a small weighting coefficient. For example, as shown in FIG. 9, the weighting factor can be set so that it becomes gradually smaller stepwise as the pixel value becomes lower. It can also be expressed as the following formula (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。

In this way, by performing weighting with the weighting coefficient determined based on the threshold value T _value and then performing image synthesis such as sum of squares synthesis, the tissue signal can be efficiently synthesized, and the noise signal is excessively synthesized. Can be prevented.

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

The configuration of the MRI apparatus according to the present embodiment is the same as that of the MRI apparatus according to the first embodiment described above, and is the same for processing other than background pixel determination and background pixel combination processing. 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, description of the same processing as the metal corresponding measurement processing in the MRI apparatus according to the first embodiment will be omitted.

First, prior to the start of the metal-corresponding measurement process, the subject is registered in the MRI apparatus, and in step S21, the image acquisition unit 31 makes a plurality of images based on the plurality of NMR signals obtained by the imaging for the metal-corresponding measurement. Get the image of. Then, in step S22, a graph showing the distribution of the pixel value and the image number in which the pixel of interest and the corresponding pixel in the plurality of images are arranged in the order of photographing is generated (FIG. 4A), and is further sorted in the order of pixel value. Then, a pixel value distribution is generated (FIG. 4(B)). In step S23, the pixel determination unit 32 determines whether or not the maximum pixel value of the corresponding pixels in the plurality of images exceeds a predetermined threshold value.

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 the characteristic that the corresponding pixels have almost the same pixel value as shown in FIG. 5C. For this reason, in step S24, a pixel determined to have a pixel value indicating the maximum pixel value that does not exceed a predetermined threshold value is determined to be a background pixel. When the pixel determination unit 32 determines that the pixel of interest is the background pixel, the process proceeds to step S26, and the image synthesis unit 33 performs maximum intensity projection on the pixel. That is, among the pixel values of the plurality of corresponding pixels, the pixel value indicating the maximum value is set as the pixel value of the target pixel.

On the other hand, when it is determined in step S23 that the pixel value of the pixel having the maximum pixel value exceeds the predetermined threshold value, in step S25, the pixel value distribution is calculated based on the pixel value distribution in FIG. It is determined whether the full width at half maximum of is greater than or equal to a predetermined value. As a result of the determination, if the half-value width is equal to or larger than the predetermined value, the process proceeds to step S27 to determine that the pixel is a metal peripheral pixel, and if the half-value width is less than the predetermined value, the process proceeds to step S29 to determine that the pixel is not a metal peripheral pixel.

If it is determined in step S27 that the pixel is a metal peripheral pixel, a predetermined number of pixels are applied in order from the higher pixel value of the corresponding pixel in the plurality of images to perform synthesis. If it is determined in step 29 that the pixel is not the metal peripheral pixel, the process proceeds to step S30, and the pixel corresponding to the pixel of interest has a pixel value of a predetermined threshold value or more among the plurality of images is applied to the pixel of interest. About image synthesis. The details of the image synthesizing process are the same as those in the above-described first embodiment, and thus the description thereof is omitted here.

In step S31, one composite image is finally generated based on the result of maximum intensity projection in step S26, the composite result of metal peripheral pixels in step S28, and the composite result of pixels that are not metal peripheral pixels in step S30. Finish metal-compatible measurement.

As described above, according to the present embodiment, by appropriately synthesizing images according to the characteristics of the pixel of interest, that is, the region to which the pixel of interest belongs, it is possible to synthesize images that contribute to the improvement of image quality without fail. At the same time, it is possible to suppress the synthesis of images that may deteriorate the image quality. Therefore, even when the subject contains a metal, the vicinity of the metal boundary can be correctly imaged and the SNR can be improved.

In the MRI apparatus according to each of the above-described embodiments, the above-described composition for each area can be automatically performed. Further, for example, the user can specify the composition method of each tissue through a user interface as shown in FIG. 11. In this case, the user allocates the most suitable one of the above-mentioned synthesizing methods to each tissue. This may be specified before measuring the image, but it is also possible to perform composition while checking the composition result after measuring the image. This allows the user to check the combined image while searching for the optimum combining method for the image.

In addition, in the above-mentioned example, an example in which the composition method is switched based on the pixel value distribution is shown, but in addition to the pixel value distribution, information acquired in advance for adjustment purposes, such as 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 switch the combining method (weighting coefficient) so that the combining 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 magnetic field coil, 10... Gradient magnetic field 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, 23... Input unit, 25... Operation unit, 30... Imaging control unit, 31... Image acquisition unit, 32... Pixel determination unit, 33... Image combining unit, 34... Weight determination unit

Claims (7)

An image acquisition unit that irradiates a subject with a plurality of high-frequency pulses while changing the frequency band according to a predetermined imaging sequence, and obtains 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 that represents 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 of interest is determined to be the metal peripheral pixel by the pixel determination unit, the pixel of interest is determined using the pixel values of a predetermined number of pixels in descending order of the pixel value of the corresponding pixel in the plurality of images. An image synthesizing unit that synthesizes the images to generate a synthetic image, and a magnetic resonance imaging apparatus. The magnetic resonance imaging apparatus according to claim 1,
When the image composition unit determines that the pixel of interest is not the metal peripheral pixel by the pixel determination unit, the pixel corresponding to the pixel of interest in the plurality of images is a pixel having a pixel value of a predetermined threshold value or more. A magnetic resonance imaging apparatus that synthesizes the 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,
The pixel of the pixel in which the pixel value of the plurality of corresponding pixels of the target pixel in the plurality of images is the maximum value when the image combining unit determines that the target pixel is the background pixel by the pixel determination unit. 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,
Further comprising a weight determining unit that determines a weighting coefficient for each pixel for an image applied when the image is synthesized by the image synthesizing unit,
A magnetic resonance imaging apparatus in which the image composition unit applies a weighting factor determined by the weight determination unit to generate a composition. 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 the descending order of pixel value 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 the corresponding pixels in the plurality of images are sorted in descending order of pixel value for the target pixel, and the target pixel is a metal based on the shape of the pixel value distribution. A magnetic resonance imaging apparatus that determines whether a pixel is a peripheral pixel. A step of irradiating a subject while changing the frequency band of 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, based on the pixel values of corresponding pixels of the target pixel in the plurality of images, the target pixel is a metal peripheral pixel representing a metal peripheral tissue in the subject,
When it is determined that the target pixel is the metal peripheral pixel, the target pixel is combined by using the pixel values of a predetermined number of pixels in descending order of the pixel value of the corresponding pixel in the plurality of images. An image processing method comprising: a step of generating a composite image.

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