JP5156958B2 - Magnetic resonance imaging system - Google Patents

Description

  The present invention relates to a aliasing removal technique for nuclear magnetic resonance imaging (hereinafter referred to as “MRI”). In particular, the present invention relates to aliasing removal technology in the parallel imaging method.

  An MRI apparatus measures a nuclear magnetic resonance (hereinafter referred to as “NMR”) signal from a subject, particularly hydrogen, phosphorus, etc. constituting a tissue of a human body, and forms and functions of the head, abdomen, limbs, and the like. Are imaged two-dimensionally or three-dimensionally. The NMR signal is phase-encoded and frequency-encoded by an applied gradient magnetic field and acquired as time series data. The acquired NMR signal is two-dimensional or three-dimensional Fourier transformed and reconstructed into an image.

  One technique for shortening the imaging time in an MRI apparatus is a technique called a parallel imaging method. In the parallel imaging method, echo data is measured while thinning out the phase encoding step of a measurement space (hereinafter abbreviated as “k space”) using a plurality of high frequency reception coils (hereinafter abbreviated as “reception coil”). To reduce imaging time. A folding artifact (hereinafter abbreviated as “folding”) generated on the reconstructed image by thinning out the phase encoding step is a reception sensitivity distribution (hereinafter abbreviated as “sensitivity distribution”) of each receiving coil. An image is developed and removed by performing a matrix operation using it (see, for example, Non-Patent Document 1).

  In the parallel imaging method, since the sensitivity distribution of the receiving coil is used for the calculation of the folding expansion, in order to obtain a good image without the folding, it is necessary to obtain the sensitivity distribution of the receiving coil as accurately as possible. In order to obtain a more accurate sensitivity distribution, there is a technique for improving the S / N ratio of the sensitivity distribution by performing complex addition, complex addition averaging, or complex geometric averaging on each reception coil sensitivity distribution in at least two imaging slices (for example, , See Patent Document 1).

  In the parallel imaging method, if a matrix operation is performed while including a low signal region such as the background, an error at the time of unfolding increases due to noise, and artifacts of bright spots occur on the image. In order to prevent this, there is a technique using a mask for removing a low signal region (see, for example, Patent Document 2).

JP 2005-168868 A JP 2002-315731 A SENSE: Sensitivity Encoding for Fast MRI (Klaas P. Prussmann et al.), Magnetic Resonance in Medicine 42: 952-962 (1999)

  Since signals having various phases in the slice direction such as noise cancel each other out by complex addition, the S / N ratio is improved as a result. According to the technique disclosed in Patent Document 1, since the sensitivity distribution of a plurality of slices is complex-added, the S / N ratio of the sensitivity distribution is improved. Therefore, even when the S / N ratio of the sensitivity distribution obtained from each slice is low, the aliasing removal process can be performed using the sensitivity distribution with a good S / N ratio, and a result image with few artifacts can be obtained. .

  However, for example, when the region to be imaged includes a region having a large phase change, such as a region where magnetic susceptibility artifacts occur, such as the sinuses, the signals cancel each other when the sensitivity distribution of multiple slices is complex-added. The size is reduced. When the sensitivity distribution in which the signal of the subject region is reduced is used in the technique using the mask disclosed in Patent Document 2, the accuracy of separation between the subject region and the background region is deteriorated, and artifacts are generated in the result image. To do.

  As described above, when the imaging target includes an area having a large phase change, the sensitivity distribution of a plurality of imaging slices, which is effective for aliasing removal, is obtained by calculation such as complex addition to improve the S / N ratio of the sensitivity distribution. It is difficult to make the technology compatible with the technology that removes the low signal region using a mask. For this reason, when the S / N ratio of the morphological image is low, artifacts cannot be effectively removed and the quality of the image cannot be improved.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to effectively remove artifacts and obtain a high-quality image even when the acquired sensitivity distribution has a low S / N ratio.

  The present invention creates a mask image from an image obtained by adding absolute values of acquired sensitivity images of a plurality of slices. A sensitivity distribution of the receiving coil is obtained by multiplying the image obtained by complex addition of the acquired sensitivity images of a plurality of slices by the created mask image. The image quality of the morphological image is improved using the obtained sensitivity distribution.

  Specifically, using a multiple receiving coil composed of a plurality of RF receiving coils, the morphological image data of the subject for each RF receiving coil, and the sensitivity image data for each RF receiving coil, using the multiple receiving coils. Measuring means for measuring one or more slices, and signal processing means for reconstructing the morphological image and the sensitivity image from the morphological image data and the sensitivity image data, respectively. The signal processing means includes an image creation means for creating an image for each RF reception coil based on the sensitivity image data for one or more slices for each RF reception coil, and one or more slices for each RF reception coil. A mask image for synthesizing images of all RF receiving coils based on the sensitivity image data and separating the subject region and the background region Using mask image creating means to create, sensitivity distribution creating means for creating a sensitivity distribution for each RF receiving coil by applying the mask image to an image for each RF receiving coil, and using the morphological image and the sensitivity distribution And a result image generating means for generating an image.

  According to the present invention, even when the S / N ratio of the acquired sensitivity distribution is low, artifacts can be effectively removed and a high-quality image can be obtained.

<< First Embodiment >>
Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. Note that components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiment of the invention, and the repetitive description thereof is omitted.

  First, the configuration of the MRI apparatus of this embodiment will be described. FIG. 1 is a schematic diagram of a configuration of an MRI apparatus 100 of the present embodiment. The MRI apparatus 100 includes a magnet 102 that generates a static magnetic field around a subject 101, a gradient coil 103 that generates a gradient magnetic field, an irradiation coil 104 that irradiates the subject with RF waves, and an NMR signal from the subject. A receiving coil 105 to be detected, a bed 106 on which the subject 101 lies, a gradient magnetic field power source 107, an RF transmission unit 108, a signal detection unit 109, a signal processing unit 110, a display unit 120, a control unit 130, Is provided.

  The magnet 102 is composed of a permanent magnet, a superconducting magnet, or a normal conducting magnet disposed in a wide space around the subject 101, and has a uniform static magnetic field in a direction parallel to or perpendicular to the body axis. Is generated. The gradient coil 103 applies a gradient magnetic field in the X, Y, and Z directions to the subject 101 in accordance with a signal from the gradient magnetic field power source 107. The imaging cross section of the subject is set depending on how the gradient magnetic field is applied. The irradiation coil 104 generates a high-frequency magnetic field according to the signal from the RF transmission unit 108. This high-frequency magnetic field is generated in order to cause nuclear magnetic resonance by exciting the atomic nuclei constituting the biological tissue of the imaging cross section of the subject 101 set by the gradient magnetic field coil 103.

  The reception coil 105 is disposed in the vicinity of the subject 101 and receives an NMR signal that is an echo signal by magnetic resonance of atomic nuclei constituting the living tissue of the subject 101 by the high-frequency magnetic field irradiated from the irradiation coil 104. To do. The received NMR signal is detected by the signal detection unit 109, processed by the signal processing unit 110, and converted into an image. The converted image is displayed on the display unit 120.

  Note that a multiple RF coil (phased array coil) including a plurality of RF receiving coils is used as the receiving coil 105. Multiple RF coils are a set of multiple high-sensitivity small RF receiver coils, and by combining the signals acquired by each coil, the field of view is expanded while maintaining high sensitivity, and high sensitivity is achieved. This is a dedicated RF coil.

  The control unit 130 repeatedly generates slice gradient, phase encode, and frequency encode gradient magnetic fields and high-frequency magnetic field pulses according to a predetermined pulse sequence and receives an NMR signal, and a gradient magnetic field power source 107 and an RF transmitter 108. And the signal processing unit 110 are controlled. In this embodiment, each part is controlled to perform measurement of morphological image data and measurement of sensitivity image data for obtaining a sensitivity distribution of the receiving coil. In addition, each unit is controlled to measure a plurality of slices.

  Further, the signal processing unit 110 of the present embodiment includes a complex image creation processing unit 111, a mask image creation processing unit 112, a sensitivity distribution creation processing unit 113, a measurement image creation processing unit 114, and a aliasing removal processing unit 115. . Prior to the description of each function, an artifact removal method called aliasing in a parallel imaging method using a conventional multiple RF coil will be described below. Hereinafter, each receiving coil constituting the multiple RF coil is referred to as an RF receiving coil.

  FIG. 2 is a diagram for explaining folding by the parallel imaging method. The parallel imaging method is a method that realizes high-speed imaging by using multiple RF coils and measuring the number of repetitions (number of steps) of phase encoding at a constant rate. The ratio of thinning out the number of phase encoding steps is represented by a reciprocal number and is generally called a double speed number. For example, in the case of the double speed number 2, thinning is performed so that the number of phase encoding steps is halved. This is called measurement by thinning out the number of steps of phase encoding at double speed. When the phase encoding step count is thinned out at double speed, the phase encoding step interval is doubled, and the data in the k space is filled every other line as indicated by 201 in FIG. For example, in the case of 202 shown in FIG. 2, an image reconstructed by performing two-dimensional Fourier transformation on the data obtained by measurement without thinning out is reconstructed from the embedded k-space data as indicated by 201. The image to be generated is one that has been folded several times as indicated by 203 in FIG. In the parallel imaging method, signal processing is performed on an image in which such folding has occurred to remove the folding.

  When measurement is performed with thinning at equal intervals so that the number of steps of phase encoding becomes 1 / N, as described above, N-folding occurs in the image after the two-dimensional Fourier transform. When M (M ≧ N) RF receiving coils are used to perform measurement by thinning out the number of steps of phase encoding at N times speed, M images in which N diffraction has occurred can be acquired. Using the sensitivity distribution of M RF receiving coils, N folded images are developed, and one image from which the folding is removed is acquired. Hereinafter, the method of expansion will be described.

The image matrix numbers in the x and y directions are set to X and Y, respectively, and the pixel value of the coordinates (x, y) (x: 1 ≦ x ≦ X, y: 1 ≦ y ≦ Y) in the image is set to s _i (x, y). y) When the sensitivity of the i-th RF receiving coil is c _i (x, y) and the density of the subject is p (x, y), each pixel constituting the image is measured without thinning out. The value s _i (x, y) is expressed by the product of the magnetization density p (x, y) of the subject and the sensitivity c _i (x, y) of the RF receiving coil as in the following (Equation 1). Is done. Here, the subscript i is 1 ≦ i ≦ M.

簡単に表現するために、（式３）に示す、画像内の画素値ｓ_ｉの分布Ｓ_ｉ、感度分布Ｃ_ｉｊ、磁化密度分布Ｐ_ｊ

を用いて、（式２）を変形すると、

と表される。（式４）はＭ個のＲＦ受信コイルそれぞれについて同様に成り立つため、画素値の分布Ｓ_ｉおよび被検体の磁化密度分布Ｐ_ｊは、Ｍ行１列の、感度分布Ｃ_ｉｊはＭ行Ｎ列の行列として、（式５）のように表すことができる。

それぞれ、

である。 On the other hand, when measurement is performed by thinning out the number of phase encoding steps at N times speed, the matrix number Δy in the phase encoding direction of the image is Y / N. Each pixel value s _i (x, y) constituting the obtained image is expressed by the following (formula 2).

In order to express simply, the distribution S _i of the pixel value s _i in the image, the sensitivity distribution C _ij , and the magnetization density distribution P _j shown in (Equation 3).

When (Equation 2) is transformed using

It is expressed. Since (Equation 4) holds similarly for each of the M RF receiving coils, the pixel value distribution S _i and the magnetization density distribution P _j of the subject are M rows and 1 column, and the sensitivity distribution C _ij is M rows and N columns. As a matrix of (Expression 5).

Each,

It is.

である。ここで、Ｈは随伴行列、-１は逆行列を示す。 The unfolded image is the magnetization density distribution P of the subject. From (Equation 6), the magnetization density distribution P of the subject is obtained as follows.

It is. Here, H is an adjoint matrix, and -1 is an inverse matrix.

  Thus, if the sensitivity distribution C of the coil is known, the magnetization density distribution P of the subject can be obtained by calculating its adjoint matrix and inverse matrix. In the conventional parallel imaging method, this is used, and the density distribution C of the coil is used to calculate an image from which aliasing is removed.

  In the present embodiment, similarly to the technique described in Patent Document 1, a plurality of slices are measured, and the sensitivity distribution of each RF receiving coil is calculated from each sensitivity image data acquired there. Hereinafter, each function of the signal processing unit 110 of the present embodiment will be described on the assumption that image data of a plurality of slices acquired by a plurality of RF receiving coils is processed.

  The complex image creation processing unit 111 creates a complex addition image from sensitivity image data for creating a sensitivity distribution for each slice acquired by each RF receiving coil. Specifically, the sensitivity image data for each slice is subjected to two-dimensional Fourier transform to obtain a sensitivity image. Each sensitivity image is complex-added in the slice direction for each receiving coil to obtain a complex-added image. Note that adding in the slice direction means adding pixel values at the same position in each slice acquired by one RF receiving coil.

  The mask image creation processing unit 112 creates a mask image from the sensitivity image generated by the complex image creation processing unit 111. Specifically, the absolute value of the sensitivity image for each slice is added in the slice direction for each RF receiving coil to obtain an absolute value added image for each RF receiving coil. The absolute value addition images of all the RF receiving coils are synthesized, and a mask image creation process is performed on the synthesized absolute value addition image to create a mask image. In the mask image creation process, the subject region is extracted by threshold processing, and the image is binarized by a method such as 1 for the extracted subject region and 0 for the other regions as the background region. This binarized image is called a mask image. Note that one mask image is created for all the RF receiving coils and slices for addition in the slice direction.

  The sensitivity distribution creation processing unit 113 multiplies the complex addition image created by the complex image creation processing unit 111 by the mask image created by the mask image creation processing unit 112 to create a sensitivity distribution. Specifically, a complex addition image of all RF receiving coils is synthesized to obtain a whole complex addition image. The complex addition image for each RF reception coil is divided by the entire complex addition image, and further multiplied by the mask image to obtain a sensitivity distribution for each RF reception coil. As described above, since the background area is 0 in the mask image, the signal value of the background portion including noise is 0 in the obtained sensitivity distribution. As a result, a sensitivity distribution of only the subject region can be created.

  The measurement image creation processing unit 114 performs two-dimensional Fourier transform on the morphological image data for each slice of each RF reception coil, and creates a measurement image that is folded several times as fast.

  The aliasing removal processing unit 115 removes aliasing from the measurement image created by the measurement image creation processing unit 114 using the sensitivity distribution created by the sensitivity distribution creation processing unit 113. A conventional method is used for removing aliasing, and an adjoint matrix and an inverse matrix are calculated from the sensitivity distribution matrix of the RF receiving coil, and a result image is obtained according to (Equation 8).

  The complex image creation processing unit 111, the mask image creation processing unit 112, the sensitivity distribution creation processing unit 113, the measurement image creation processing unit 114, and the aliasing removal processing unit 115 described above are included in the memory (non-deletion) of the MRI apparatus 100. This is realized by executing a program stored in (shown) by an arithmetic unit that realizes the signal processing unit 110.

  Next, the flow of the aliasing removal process performed by each function of the signal processing unit 110 according to the present embodiment will be described. As described above, in this embodiment, a plurality of RF receiving coils respectively measure a plurality of slices and acquire sensitivity image data and morphological image data. Hereinafter, in the text, it is assumed that the number of RF receiving coils is M, and the number of acquired slices in each receiving coil is L. M and L are natural numbers of 2 or more, respectively.

FIG. 3 is a diagram for explaining the flow of the aliasing removal processing of the present embodiment. In this figure, as an example, the flow of processing when an image of three slices is picked up by two RF receiving coils, that is, when M = 2 and L = 3 is shown. That is, 301 ₁₁ and 307 ₁₁ , 301 ₂₁ and 307 ₂₁ , 301 ₁₂ and 307 ₁₂ , 301 ₂₂ and 307 ₂₂ , 301 ₁₃ and 307 ₁₃ , and 301 ₂₃ and 307 ₂₃ are for sensitivity images of the same slice by the same receiving coil, respectively. Data and morphological image data.

  Here, representative methods for acquiring the sensitivity distribution of the receiving coil in the parallel imaging method include an SCM method and a PCM method. In the PCM method, the sensitivity distribution of the receiving coil is measured prior to the main measurement for measuring the image reconstruction data. On the other hand, in the SCM method, only the low spatial frequency region of the k space is measured without thinning out the number of steps of phase encoding, and the sensitivity distribution is measured during the main measurement. In the present embodiment, the sensitivity distribution may be acquired by any method.

First, the complex image creation processing unit 111 performs two-dimensional Fourier transform 302 on the sensitivity image data 301 ₁₁ , 301 ₁₂ , 301 ₁₃ , 301 ₂₁ , 301 ₂₂ , and 301 ₂₃ acquired at each slice of each RF receiving coil. To obtain sensitivity images 303 ₁₁ , 303 ₁₂ , 303 ₁₃ , 303 ₂₁ , 303 ₂₂ , and 303 ₂₃ . Then, the complex image creation processing unit 111 transfers the obtained sensitivity images 303 ₁₁ , 303 ₁₂ , and 303 ₁₃ to the mask image creation processing unit 112, and at the same time, the sensitivity images 303 ₁₁ , 303 ₁₂ , 303 ₁₃ , 303 ₂₁ , 303 _{22, 303 23} and complex addition 304 in the slice direction for each receiver coil to obtain a complex addition image ₃₀₅ 1, 305 _2.

The real part of the pixel value of the coordinates (x, y) of the sensitivity image 303 _ij of the l (≦ L) th slice of the i (≦ M) th RF receiving coil is represented by r _{real, i, l} (x, y), _{Assuming that the} imaginary part is r _{img, i, l} (x, y), the real part r _{real, i, sum} (x, y) of the pixel value of the coordinates (x, y) of the complex addition image 305 _i after the complex addition 304 is performed. And the imaginary part r _{img, i, sum} (x, y) is obtained by the following (formula 9).

The complex image creation processing unit 111 passes the obtained complex addition image 305 _i to the sensitivity distribution creation processing unit 113.

When the mask image creation processing unit 112 receives the sensitivity images 303 ₁₁ , 303 ₁₂ , 303 ₁₃ , 303 ₂₁ , 303 ₂₂ , and 303 ₂₃ from the complex image creation processing unit 111, the mask image creation processing unit 112 performs absolute value addition 320 in the slice direction to obtain the absolute value. Addition images 321 ₁ and 321 ₂ are obtained. The pixel values r _{abs, i, sum} (x, y) of the coordinates (x, y) of the absolute value addition image 321 _i obtained by the absolute value addition 320 are as shown in the following (Equation 10).

Then, the mask image creation processing unit 112 performs a mask image creation process 323 to obtain a mask image 324. Here, first, the absolute value added images 321 ₁ and 321 ₂ of the respective receiving coils are synthesized to obtain a synthesized image. At this time, the pixel value r _{abs, sum} (x, y) of the coordinates (x, y) of the composite image is as shown in (Expression 11).

Then, the composite image is subjected to threshold processing using a predetermined threshold th to obtain a mask image 324. Here, assuming that the subject area of the mask image 324 is 1 and the background area is 0, the pixel value m (x, y) of the coordinates (x, y) of the mask image 324 is as shown in (Expression 12).

  The mask image creation processing unit 112 passes the obtained mask image 324 to the sensitivity distribution creation processing unit 113.

Next, the sensitivity distribution creation processing unit 113 performs sensitivity distribution creation processing 325 using the complex addition images 305 ₁ and 305 ₂ and the mask image 324 received from the complex image creation processing unit 111 and the mask image creation processing unit 112, respectively. To obtain sensitivity distributions 326 ₁ , 326 ₂ for each RF receiving coil.

そして、感度分布作成処理部１１３は、ＲＦ受信コイル毎の複素加算画像３０５_ｉを全体複素加算画像で除算し、さらにマスク画像３２４を乗算することにより、感度分布３２６_ｉを得る。感度分布３２６_ｉの座標（ｘ、ｙ）の値ｃ_ｉ（ｘ、ｙ）は（式１４）のとおりである。

ただし、ｊは虚数を示す。このように、本実施形態では、被検体領域のみで感度分布３２６_ｉを作成できる。 Here, the sensitivity distribution creation processing unit 113 first synthesizes the complex addition images 305 _i of M RF receiving coils to obtain an overall complex addition image r _body (x, y). The pixel value r _body (x, y) of the coordinates (x, y) of the whole complex addition image is as shown in (Expression 13).

Then, the sensitivity distribution creation processing unit 113 divides the complex addition image 305 _i for each RF reception coil by the entire complex addition image and further multiplies the mask image 324 to obtain a sensitivity distribution 326 _i . The value c _i (x, y) of the coordinate (x, y) of the sensitivity distribution 326 _i is as shown in (Expression 14).

However, j shows an imaginary number. Thus, in the present embodiment, the sensitivity distribution 326 _i can be created only from the subject region.

The sensitivity distribution creation processing unit 113 passes the obtained sensitivity distribution 326 _i to the aliasing removal processing unit 115.

On the other hand, the measurement image creation processing unit 114 performs two-dimensional Fourier transform 308 on the morphological image data 307 ₁₁ , 307 ₁₂ , 307 ₁₃ , 307 ₂₁ , 307 ₂₂ , and 307 ₂₃ for each slice of each receiving coil, and receives each reception. Measurement images 309 ₁₁ , 309 ₁₂ , 309 ₁₃ , 309 ₂₁ , 309 ₂₂ , and 309 ₂₃ are obtained for each slice of the coil. The measurement image creation processing unit 114 transfers the obtained measurement images 309 ₁₁ , 309 ₁₂ , 309 ₁₃ , 309 ₂₁ , 309 ₂₂ , and 309 ₂₃ to the aliasing removal processing unit 115.

The aliasing removal processing unit 115 creates a matrix 310 as shown in (Formula 5) from the sensitivity distribution 326 _i received from the sensitivity distribution creation processing unit 113, calculates 311 its adjoint matrix and inverse matrix, and follows (Formula 8). By multiplying each measurement image 309 received from the measurement image creation processing unit 114, a result image 312 from which aliasing has been removed is obtained. That is, 309 ₁₁ , 309 ₂₁ to 312 ₁ , 309 ₁₂ , 309 ₂₂ to 312 ₂ , and 309 ₁₃ , 309 ₂₃ to 312 ₃ are obtained. In this case, the measurement image _{309 11,} 309 12, _{309 13} sensitivity distribution 326 _1, the measurement image _{309 21,} 309 22, _{309 23} The use of the sensitivity distribution 326 _2. That is, the same sensitivity distribution is used for the measurement image of each slice at the same position as the sensitivity image of a plurality of slices used for creating the sensitivity distribution of the same RF receiving coil.

  Heretofore, the procedure for removing aliasing according to the present embodiment has been described.

  As described above, according to the present embodiment, in the parallel imaging method, a mask image is created from an image obtained by adding absolute values of sensitivity images of a plurality of slices acquired for creating a sensitivity distribution. In an absolute value-added image, even if the subject region includes a region with a large phase change, the signal region does not cancel out due to the phase change, so the subject region and the background region are separated accurately. it can. Therefore, according to the present embodiment, since the mask image is created from the image from which the influence of the phase difference is eliminated by adding the absolute values, it is possible to obtain a mask image that can accurately extract only the subject region regardless of the subject region. it can.

  According to the present embodiment, the sensitivity distribution is created by multiplying the complex image obtained by complex addition of the sensitivity image by the mask image. Therefore, according to the present embodiment, it is possible to obtain a sensitivity distribution in which the S / N ratio is good and the low signal region such as the background region is efficiently removed regardless of the subject region. Then, the aliasing is removed from the morphological image using the obtained sensitivity distribution. Therefore, the folding can be developed with high accuracy, and the artifact can be removed.

  In the present embodiment, in order to obtain a complex image that improves the S / N ratio of the sensitivity distribution and an absolute value image for excluding the low signal region, from the sensitivity images of a plurality of slices acquired for creating the same sensitivity distribution. , Efficiency is also good. On the other hand, since complex addition for obtaining a complex image and absolute value addition for creating a mask image are performed independently, each does not affect.

  In addition, each measurement image of a plurality of slices is processed by one sensitivity distribution created using a plurality of slices at the same position. For this reason, the number of times of calculating the sensitivity distribution can be reduced.

  In the above embodiment, the parallel imaging method has been described as a premise, but the application of the present invention is not limited to this. As described above, according to the present embodiment, it is possible to obtain a highly accurate sensitivity distribution of each receiving coil in imaging using a plurality of receiving coils. Therefore, it can be widely applied to general imaging using the sensitivity distribution of the receiving coil.

  Hereinafter, an example in which the mask image obtained by the procedure of the present embodiment is superior to that of the conventional procedure will be described. FIG. 4 is a diagram for explaining a mask image obtained by the procedure of this embodiment, and FIG. 5 is a diagram for explaining a mask image obtained by a conventional procedure.

  An image 401 in FIG. 4 is a composite of the absolute value images 321 of the receiving coils. An image 402 is a mask image 324 obtained as a result of the mask image creation process 323. In the image 402, a subject region from which a white portion is extracted is a background region, and a black portion is a background region. As shown in this figure, according to the procedure of this embodiment, it can be seen that the subject region and the background region can be accurately separated. For comparison, a mask image creation process is performed on an image obtained by synthesizing the complex image 305 after the complex addition, and the obtained result is shown in FIG. As shown in this figure, it can be confirmed that the center area of the image extracted as the subject area in the image 402 is recognized as the background area in the image 502.

It is the schematic of the structure of the MRI apparatus of this embodiment. It is a figure for demonstrating the folding | turning by a parallel imaging method. It is a figure for demonstrating the flow of a process of the aliasing removal process of this embodiment. It is a figure for demonstrating the mask image obtained by the procedure of this embodiment. It is a figure for demonstrating the mask image obtained by the conventional procedure.

Explanation of symbols

100: MRI apparatus, 101: subject, 102: magnet, 103: gradient coil, 104: irradiation coil, 105: reception coil, 106: bed, 107: gradient magnetic field power supply, 108: RF transmitter, 109: signal detector 110: signal processing unit, 111: complex image creation processing unit, 112: mask image creation processing unit, 113: sensitivity distribution creation processing unit, 114: measurement image creation processing unit, 115: aliasing removal processing unit, 120: display unit , 130: control unit

Claims (7)

Using a multiple receiving coil composed of a plurality of RF receiving coils and the multiple receiving coils, the morphological image data of the subject for each RF receiving coil and the sensitivity image data for each RF receiving coil are measured for each slice. A magnetic resonance imaging apparatus comprising: measuring means for performing; and signal processing means for reconstructing the morphological image and the sensitivity image from the morphological image data and the sensitivity image data, respectively.
The signal processing means includes
From the RF receiving each of the sensitivity image data of a plurality of slices obtained for each coil, and an image generating means for generating the sensitivity image of each slice for each of the RF receiver coil,
A sensitivity image for each slice is created from each of the sensitivity image data of a plurality of slices obtained for each RF receiver coil, and the sensitivity image is added with an absolute value in the slice direction for each RF receiver coil. A mask image creating means for creating a mask image that is synthesized between the RF receiving coils and separates the subject region and the background region;
The sensitivity image created by the image creating means is added in the slice direction for each RF receiving coil to obtain a sensitivity added image for each RF receiving coil, and the mask image is applied to each of the obtained sensitivity added images. A sensitivity distribution creating means for creating a sensitivity distribution for each RF receiving coil;
A magnetic resonance imaging apparatus comprising: a result image generating unit configured to generate an image using the morphological image and the sensitivity distribution. The magnetic resonance imaging apparatus according to claim 1,
The sensitivity addition image is a complex addition image obtained by complex addition of the sensitivity image in the slice direction.
A magnetic resonance imaging apparatus . The magnetic resonance imaging apparatus according to claim 2,
The sensitivity distribution is created by dividing the complex addition image for each RF receiving coil by the whole complex image obtained by synthesizing all the complex addition images and multiplying the mask image.
A magnetic resonance imaging apparatus . The magnetic resonance imaging apparatus according to any one of claims 1 to 3 ,
The control means measures the morphological image data so as to thin out the encoding step,
The result image generation means includes, for each of the RF reception coils, aliasing removal means for removing aliasing of the morphology image from the morphology image of each of the one or more slices and the sensitivity distribution of the RF reception coil. A magnetic resonance imaging apparatus. The magnetic resonance imaging apparatus according to any one of claims 1 to 4 ,
The magnetic resonance imaging apparatus, wherein the sensitivity image data used by the image creating means and the sensitivity image data used by the mask image creating means are the same sensitivity image data. The magnetic resonance imaging apparatus according to any one of claims 1 to 5 ,
The magnetic resonance imaging apparatus, wherein the sensitivity image data is measured during measurement of the morphological image data. The magnetic resonance imaging apparatus according to any one of claims 1 to 5 ,
The magnetic resonance imaging apparatus, wherein the sensitivity image data is measured prior to measurement of the morphological image data.

Images