CN104107045B - MR imaging method and device - Google Patents

Abstract

The embodiment of the invention discloses a kind of MR imaging method.The method includes: original image carries out plural number high-pass filtering, it is thus achieved that filtered image；From filtered image, obtain view data, the imaginary numbers in described view data is carried out segmentation, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds；Numerical value after processing is multiplied as weighted value with the gray value of magnitude image, finally gives MRI.According to embodiments of the present invention, can be while ensureing image definition, it is provided that one MR imaging method quickly and easily.Solve the problem that in prior art, magnetic susceptibility weighted image processing procedure is excessively complicated.The embodiment of the present invention additionally provides a kind of MR imaging apparatus.

Description

MR imaging method and device

Technical field

The present invention relates to field of medical image processing, particularly relate to MR imaging method and device.

Background technology

Magnetic susceptibility-weighted imaging (Susceptibility Weighted Imaging, SWI) technology is a kind of magnetic resonance contrast's Enhanced Imaging technology that new development in recent years is got up.Proton density different from the past, T1 or T2 weighted imaging, SWI provides image comparison to strengthen according to magnetic susceptibility (magnetic susceptibility can the be quantified as magnetic susceptibility) difference between different tissues.

Research finds, owing to the Main Ingredients and Appearance of venous blood is paramagnetic deoxyhemoglobin, the Main Ingredients and Appearance of arterial blood is then diamagnetic oxyhemoglobin, therefore, magnetic susceptibility difference is there is between vein blood vessel and arteries, the signal strength signal intensity that this species diversity can ultimately result in two kinds of blood vessels is different, thus can provide possibility independent of arteries blur-free imaging for vein blood vessel.In clinical practice, SWI technology can be applicable in brain tumor, cerebral hemorrhage or other focus research relevant with vein blood vessel.

At present, SWI image also cannot be directly obtained by existing MR imaging apparatus, but need that the original image (that is, actually detected to image) obtained based on T2* weighted gradient echo sequence is carried out complicated image procossing and just can obtain SWI image.

In the prior art, it is provided that a kind of image processing method obtaining SWI image, its handling process is: first generate phase image and magnitude image (or referred to as magnetic is away from image) according to raw image data；Then phase image is carried out high-pass filtering, to remove due to the uneven low-frequency excitation caused of background magnetic field, obtain filtered phase image；Phase image mask (or phase place frisket) is calculated again with filtered phase image；Finally phase image mask is applied to magnitude image n time, obtains final SWI image.

During realizing the present invention, the inventors found that in prior art, at least there are the following problems: owing to existing this image processing method needs to calculate phase image, and calculate phase place frisket n power according to phase image, and the value of power exponent n is determined (i.e. by signal noise ratio (snr) of image, under different signal noise ratio (snr) of image, the value of n also can be different), therefore, image processing process also needs to first determine signal noise ratio (snr) of image, thus add the complexity of whole image processing process.Further, the calculating of n power itself also makes whole image processing process the most loaded down with trivial details.

Summary of the invention

In order to solve above-mentioned technical problem, embodiments provide MR imaging method and device, with while ensureing image definition, solve the problem that in prior art, image processing process is excessively complicated.

The embodiment of the invention discloses following technical scheme:

A kind of MR imaging method, including:

Original image is carried out plural number high-pass filtering, it is thus achieved that filtered image；

From filtered image, obtain view data, the imaginary numbers in described view data is carried out segmentation, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds；

Numerical value after processing is multiplied as weighted value with the gray value of magnitude image, finally gives MRI.

Preferably, described method also includes:

MRI described in the every aspect obtained is carried out minimum signal strength projection.

Preferably, the high-pass filtering of described plural number is homomorphism high-pass filtering.

Preferably, described from filtered image, obtain view data, the imaginary numbers in described view data is carried out segmentation, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds, including:

When the imaginary numbers in described view data is more than or equal to 0, the real part numerical value in described view data is normalized to 1；When imaginary numbers is less than 0, the value that the real part numerical value in described view data is normalized between 0 and 1；

Or,

When the imaginary numbers in described view data is more than or equal to 0, the value that the real part numerical value in described view data is normalized between 0 and 1；When imaginary numbers is less than 0, the real part numerical value in described view data is normalized to 1；

Or,

The value directly the real part numerical value in described view data being normalized between 0 and 1.

It is further preferred that the described value that real part numerical value in described view data is normalized between 0 and 1 particularly as follows:

According toThe value that real part numerical value in described view data is normalized between 0 and 1；

Wherein, W (r) is the numerical value after processing, R (ρ_HF(r)) it is real part numerical value.

A kind of MR imaging apparatus, including:

High pass filter unit, for carrying out plural number high-pass filtering, it is thus achieved that filtered image to original image；

Normalized unit, for obtaining view data from filtered image, carries out segmentation, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds the imaginary numbers in described view data；

Weight calculation unit, the numerical value after processing is multiplied as weighted value with the gray value of magnitude image, obtains MRI.

Preferably, described device also includes:

Projecting cell, for carrying out minimum signal strength projection to MRI described in the every aspect obtained.

Preferably, the high-pass filtering of described plural number is homomorphism high-pass filtering.

Preferably, described normalized unit includes:

First arranges subelement, for when the imaginary numbers in described view data is more than or equal to 0, the real part numerical value in described view data being normalized to 1；

First varitron unit, for being less than 0 when the imaginary numbers in described view data, the value that the real part numerical value in described view data is normalized between 0 and 1；

Or,

Described normalized unit includes:

Second arranges subelement, for when the imaginary numbers in described view data is less than 0, the real part numerical value in described view data being normalized to 1；

Second varitron unit, for being more than or equal to 0 when the imaginary numbers in described view data, the value that the real part numerical value in described view data is normalized between 0 and 1；

Or,

Described normalized unit includes:

3rd varitron unit, the value directly the real part numerical value of described view data being normalized between 0 and 1.

It is further preferred that described first varitron unit, the second varitron unit or the 3rd varitron unit specifically for,

According toThe value that real part numerical value in described view data is normalized between 0 and 1；

Wherein, W (r) is the numerical value after processing, R (ρ_HF(r)) it is real part numerical value.

As can be seen from the above-described embodiment, compared with prior art, the advantage of technical solution of the present invention is:

View data filtered for original image is carried out different normalizeds, the weighting function after utilization process and power exponential function (that is, (φ of phase place frisket in prior art_MASK(r))ⁿSimilitude between), is replaced the power exponential function of phase place frisket in prior art by the weighting function after processing.Owing to the weighting function after this process does not changes with the change of signal noise ratio (snr) of image, stability is preferable.Therefore, the weighting function after using this process replaces the power exponential function of phase place frisket, need not calculate phase image, it is not necessary to determine power by signal noise ratio (snr) of image, thus simplify whole image processing process in image processing process.And, it is not necessary to carry out the calculating of n power, also make whole image processing process relatively easy easily.

Accompanying drawing explanation

In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, the accompanying drawing used required in embodiment or description of the prior art will be briefly described below, apparently, accompanying drawing in describing below is only some embodiments of the present invention, for those of ordinary skill in the art, on the premise of not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.

The flow chart of a kind of MR imaging method that Fig. 1 provides for the embodiment of the present invention one；

Fig. 2 is the weighting curve a kind of Similar contrasts figure with the power exponent curve of prior art of the present invention；

Fig. 3 is the weighting curve another kind of Similar contrasts figure with the power exponent curve of prior art of the present invention；

Fig. 4 is the weighting curve another kind of Similar contrasts figure with the power exponent curve of prior art of the present invention；

The flow chart of a kind of MR imaging method that Fig. 5 provides for the embodiment of the present invention two；

The structured flowchart of a kind of MR imaging apparatus that Fig. 6 provides for the embodiment of the present invention three；

The structured flowchart of the another kind of MR imaging apparatus that Fig. 7 provides for the embodiment of the present invention three；

Fig. 8 is a kind of structured flowchart of normalized unit in the present invention；

Fig. 9 (a)-(b) is respectively the image after original image processes with the present invention.

Detailed description of the invention

In order to remove the uneven low frequency phase interference caused of background magnetic field, and further enhance the magnetic susceptibility contrast between tissue, thus more clearly from show anatomical structure, need original image is carried out a series of post processing.

In the prior art, phase image and magnitude image can be obtained respectively according to the view data (this view data is plural number) of original image.Wherein,

Phase image is:

φ (r)=arctan (I (r)/R (r))

Magnitude image is:

${\mathrm{\ρ}}_m\left(r\right)=\sqrt{(R{\left(r\right)}^2+I{\left(r\right)}^2)}$

I (r) and R (r) is respectively imaginary part and the real part of view data, and r is phase value.

Conventional magnetic resonance imaging (Magnetic Resonance Imaging, MRI) only make use of single amplitude information, SWI technology then make use of the most uncared-for phase information, and through a series of image procossing, phase image is applied in magnitude image, form unique image comparison and strengthen.This processing procedure includes:

1, first phase image is carried out high-pass filtering, remove the low-frequency excitation caused owing to background magnetic field is uneven.

Such as, first phase image being carried out LPF, then in complex field, with original image divided by the k-space data after LPF, finally give is exactly the phase image after high-pass filtering.

2, more filtered phase image is normalized, generates phase place frisket φ_MASK(r)。

3, finally according to phase place frisket and magnitude image, generation SWI image:

ρ_SWI(r)=(φ_MASK(r))ⁿ×ρ_mR (), n determines the size of weight, and general n takes 3～6 can obtain the image that signal to noise ratio is higher.

The present inventor finds under study for action, by original image after plural number high-pass filtering processes, if the real part numerical value in the view data of the image after processing is according to the segmentation to imaginary numbers, carry out different normalizeds respectively, weighting function obtained by after process and power exponential function (that is, (φ of above-mentioned phase place frisket_MASK(r))ⁿ) approximate very much, and, this weighting function does not changes with the change of signal noise ratio (snr) of image, and stability is preferable.Therefore, when the power exponential function using this weighting function to replace phase place frisket, avoid the need for calculating phase image and phase place frisket in image processing process, and determine signal noise ratio (snr) of image, thus simplify whole image processing process.And, it is not necessary to carry out the calculating of n power, also make whole image processing process relatively easy easily.

Understandable for enabling the above-mentioned purpose of the present invention, feature and advantage to become apparent from, below in conjunction with the accompanying drawings the embodiment of the present invention is described in detail.

Embodiment one

Refer to Fig. 1, the flow chart of its a kind of MR imaging method provided for the embodiment of the present invention one, the method comprises the following steps:

Step 101: original image is carried out plural number high-pass filtering, it is thus achieved that filtered image.

Wherein, in order to eliminate the uneven low-frequency excitation caused due to background magnetic field, it is thus achieved that the image become apparent from, need first original image to be carried out high-pass filtering.Owing to the view data in original image is plural number, therefore, this high-pass filtering is the high-pass filtering of plural form.

In a preferred embodiment of the present invention, homomorphism high-pass filtering can be used to realize the high-pass filtering of plural form.

Such as, original image is ρ (r), original image carries out the image after homomorphism high-pass filtering and is:

ρ_HF(r)=exp (FFT^-1(Han(r)×FFT(ln(ρ(r)))))

Wherein, ρ_HFR () is the view data of the image after high-pass filtering, Han (r) is Hanning function, $\mathrm{Han}\left(r\right)=0.5\×(1-\cos \left(2\mathrm{\π}\frac{r}{N}\right)),0\≤r\≤N.$

Step 102: obtain view data from filtered image, carries out segmentation, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds the imaginary numbers in described view data.

Due in phase image, the phase value of paramagnet (such as vein blood vessel) shows as obvious negative value, and the phase value of major part brain essence and cerebrospinal fluid etc. usually on the occasion of or less negative value, therefore, in the prior art, need phase image is calculated phase mask (or phase place frisket), and the n power of phase mask is multiplied with magnitude image amplitude, the observability of prominent little structure.

Owing to the imaginary numbers in high-pass filtering view data comprises the SIN function information of phase value, real part comprises the cosine function information of phase value, therefore, when the phase value of paramagnet (such as vein blood vessel) shows as obvious negative value, imaginary numbers in the view data of this portion of tissue also can correspondingly show as obvious negative value, and when major part brain essence and cerebrospinal fluid etc. phase value usually on the occasion of or during less negative value, the imaginary numbers of the view data of this portion of tissue also can correspondingly show as on the occasion of.It is to say, the imaginary numbers of the view data of different tissues is different.The imaginary numbers that therefore, it can utilize the view data of different tissues is different characteristic, and the imaginary numbers in the view data obtained is carried out segmentation, and after segmentation, is positioned at the imaginary numbers that the imaginary numbers of same segmentation is the view data of same tissue.Then the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds.That is, for the real part numerical value of view data of different tissues, the normalization mode of differentiation is taked, in order to be finally reached the effect of different histological differenceization displays.

How follow-up will be described in carries out different normalizeds.

Step 103: the numerical value after processing is multiplied as weighted value with the gray value of magnitude image, finally gives MRI.

Obviously, the final MRI obtained can highlight the little structure in original image, e.g., vein blood vessel.

In the prior art, generally there are three kinds phase image is masked process, the method generating phase place frisket.

First method: when phase value is positioned between [0, π], phase value is set to 1；When phase value be positioned at [-π, 0) between time, the value that phase value is transformed between 0 and 1, e.g.,φ (r) is phase value.

Second method: when phase value be positioned at [-π, 0) between time, phase value is set to 1；When phase value is positioned between [0, π], the value that phase value is transformed between 0 and 1.

The third method: when phase value is positioned between [-π, π], the value that phase value is transformed between 0 and 1.

Corresponding to above-mentioned three kinds of methods, the different normalized mode in above-mentioned steps 102 can be:

First method, when the imaginary numbers in described view data more than or equal to 0 time, the real part numerical value in described view data is normalized to 1；When imaginary numbers is less than 0, the value that the real part numerical value in described view data is normalized between 0 and 1；

Second method, when the imaginary numbers in described view data more than or equal to 0 time, the value that the real part numerical value in described view data is normalized between 0 and 1；When imaginary numbers is less than 0, the real part numerical value in described view data is normalized to 1.

The third method, the value directly the real part numerical value in described view data being normalized between 0 and 1.

In a preferred embodiment of the present invention, the value that the real part numerical value in described view data is normalized between 0 and 1 particularly as follows:

According toThe value that real part numerical value in described view data is normalized between 0 and 1；

Wherein, W (r) is the numerical value after normalized, R (ρ_HF(r)) it is real part numerical value.

Such as, as a example by first method, the weighted value after segmentation normalized is:

$W\left(r\right)=\left\{\begin{array}{cc}1& I\left({\mathrm{\&rho;}}_{\mathrm{HF}}\left(r\right)\right)\&GreaterEqual;0)\\ 1-\sqrt{\frac{1-R\left({\mathrm{\&rho;}}_{\mathrm{HF}}\left(r\right)\right)}{2}}& I\left({\mathrm{\&rho;}}_{\mathrm{HF}}\left(r\right)\right)<0\end{array}\right.$

Wherein, ρ_HFR () is the view data of the image after high-pass filtering, I (ρ_HF(r)) it is the imaginary numbers of this view data, R (ρ_HF(r)) it is the real part numerical value of this view data.

Finally using the W (r) after segmentation normalized as weighted value, with magnitude image ρ_MR () carries out point-to-point product, finally give and highlight the MRI of little structure and be:

${\mathrm{\&rho;}}_{\mathrm{HFI}}={\mathrm{\&rho;}}_M\left(r\right)\&times;W\left(r\right)=\left\{\begin{array}{cc}{\mathrm{\&rho;}}_M\left(r\right)& I\left({\mathrm{\&rho;}}_{\mathrm{HF}}\left(r\right)\right)\&GreaterEqual;0)\\ {\mathrm{\&rho;}}_M\left(r\right)\&times;(1-\sqrt{\frac{1-R\left({\mathrm{\&rho;}}_{\mathrm{HF}}\left(r\right)\right)}{2}})& I\left({\mathrm{\&rho;}}_{\mathrm{HF}}\left(r\right)\right)<0\end{array}\right.$

When using this formula to carry out conversion process, for the first normalization processing method, the Similar contrasts of the power exponent curve of the weighting curve of the present invention and prior art schemes as shown in Figure 2, for the second normalization processing method, the Similar contrasts of the power exponent curve of the weighting curve of the present invention and prior art schemes as shown in Figure 3, Similar contrasts for the power exponent curve of the third normalization processing method, the weighting curve of the present invention and prior art schemes as shown in Figure 4.Wherein, line 1 is 1 power function of phase place frisket, and line 2 is the SIN function being made up of the imaginary numbers after normalized, and line 3 is 4 power functions of phase place frisket.

As can be seen from the above-described embodiment, compared with prior art, the advantage of technical solution of the present invention is:

Using the imaginary numbers of the view data in filtered image as the segmentation foundation of this view data, utilize real part numerical value that view data is carried out different normalizeds, weighting function after utilization process and power exponential function (that is, (φ of phase place frisket in prior art_MASK(r))ⁿSimilitude between), is replaced the power exponential function of phase place frisket in prior art by the weight after processing.Owing to the weighting function after this process does not changes with the change of signal noise ratio (snr) of image, stability is preferable.Therefore, the weighting function after using this process replaces the power exponential function of phase place frisket, avoids the need for calculating phase image and phase place frisket, it is not necessary to determine power by signal noise ratio (snr) of image, thus simplify whole image processing process in image processing process.And, it is not necessary to carry out the calculating of n power, also make whole image processing process relatively easy easily.

Embodiment two

By MR imaging method in embodiment one, it is possible to obtain the MRI of every aspect.In order to make to be dispersed in the magnetic susceptibility signal serialization of the vein blood vessel of every aspect further, finally demonstrate continuous print vein blood vessel structure, the present embodiment two, on the basis of embodiment one, carries out minimum signal strength projection to the MRI of the every aspect obtained.

Refer to Fig. 5, the flow chart of its a kind of MR imaging method provided for the embodiment of the present invention two, the method comprises the following steps:

Step 501: original image is carried out plural number high-pass filtering, it is thus achieved that filtered image.

Step 502: obtain view data from filtered image, carries out segmentation, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds the imaginary numbers in described view data.

Step 503: the numerical value after processing is multiplied as weighted value with the gray value of magnitude image, finally gives MRI.

Step 504: MRI described in the every aspect obtained is carried out minimum signal strength projection.

As can be seen from the above-described embodiment, compared with prior art, the advantage of technical solution of the present invention is:

Using the imaginary numbers of the view data in filtered image as the segmentation foundation of this view data, utilize real part numerical value that view data is carried out different normalizeds, weighting function after utilization process and power exponential function (that is, (φ of phase place frisket in prior art_MASK(r))ⁿSimilitude between), is replaced the power exponential function of phase place frisket in prior art by the weight after processing.Owing to the weighting function after this process does not changes with the change of signal noise ratio (snr) of image, stability is preferable.Therefore, the weighting function after using this process replaces the power exponential function of phase place frisket, avoids the need for calculating phase image and phase place frisket, it is not necessary to determine power by signal noise ratio (snr) of image, thus simplify whole image processing process in image processing process.And, it is not necessary to carry out the calculating of n power, also make whole image processing process relatively easy easily.

Embodiment three

Corresponding with above-mentioned a kind of MR imaging method, the embodiment of the present invention additionally provides a kind of MR imaging apparatus.Referring to Fig. 6, the structured flowchart of its a kind of MR imaging apparatus provided for the embodiment of the present invention three, this device includes: high pass filter unit 601, normalized unit 602 and weight calculation unit 603.Operation principle below in conjunction with this device is further described its internal structure and annexation.

High pass filter unit 601, for carrying out plural number high-pass filtering, it is thus achieved that filtered image to original image.

Normalized unit 602, for obtaining view data from filtered image, carries out segmentation, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds the imaginary numbers in described view data.

Weight calculation unit 603, the numerical value after processing is multiplied as weighted value with the gray value of magnitude image, obtains MRI.

In a preferred embodiment of the present invention, as it is shown in fig. 7, this device also includes:

Projecting cell 604, for carrying out minimum signal strength projection to MRI described in the every aspect obtained.

In another preferred embodiment of the present invention, the high-pass filtering of described plural number is homomorphism high-pass filtering.

In another preferred embodiment of the present invention, as shown in Figure 8, normalized unit 602 includes:

First arranges subelement 6021, for when the imaginary numbers in described view data is more than or equal to 0, the real part numerical value in described view data being normalized to 1.

First varitron unit 6022, for being less than 0 when the imaginary numbers in described view data, the value that the real part numerical value in described view data is normalized between 0 and 1.

Alternatively, normalized unit 602 includes:

Second arranges subelement, for when the imaginary numbers in described view data is less than 0, the real part numerical value in described view data being normalized to 1.

Second varitron unit, for being more than or equal to 0 when the imaginary numbers in described view data, the value that the real part numerical value in described view data is normalized between 0 and 1.

Or, alternatively, normalized unit 602 includes:

3rd varitron unit, the value directly the real part numerical value of described view data being normalized between 0 and 1.

In another preferred embodiment of the present invention, described first varitron unit, the second varitron unit or the 3rd varitron unit specifically for,

According toThe value that real part numerical value in described view data is normalized between 0 and 1；

Wherein, W (r) is the numerical value after processing, R (ρ_HF(r)) it is real part numerical value.

As can be seen from the above-described embodiment, compared with prior art, the advantage of technical solution of the present invention is:

The imaginary numbers of the view data in filtered image is carried out segmentation, the different normalized utilizing real part numerical value obtains weighted image data, weighting function after utilization process and power exponential function (that is, (φ of phase place frisket in prior art_MASK(r))ⁿSimilitude between), is replaced the power exponential function of phase place frisket in prior art by the weight after processing.Owing to the weighting function after this process does not changes with the change of signal noise ratio (snr) of image, stability is preferable.Therefore, the weighting function after using this process replaces the power exponential function of phase place frisket, avoids the need for calculating phase image and phase place frisket, it is not necessary to determine power by signal noise ratio (snr) of image, thus simplify whole image processing process in image processing process.And, it is not necessary to carry out the calculating of n power, also make whole image processing process relatively easy easily.

By the experimental data of health volunteer, checking technical scheme can obtain highlighting the effect of little structure.Fructufy is such as shown in Fig. 9, and wherein Fig. 9 (a) is original image；Fig. 9 (b) is image treated by the present method, is highlighted vein.

The technical staff in described field is it can be understood that arrive, for convenience of description and succinctly, the specific works process of the system of foregoing description, device and unit, it is referred to the corresponding process in preceding method embodiment, does not repeats them here.

In several embodiments provided by the present invention, it should be understood that disclosed system, apparatus and method, can realize by another way.Such as, the device embodiment arrived described above is only schematically, such as, the division of described unit, be only a kind of logic function to divide, actual can have when realizing other dividing mode, the most multiple unit or assembly can in conjunction with or be desirably integrated into another system, or some features can ignore, or do not perform.Another point, shown or discussed coupling each other or direct-coupling or communication connection can be the INDIRECT COUPLING by some interfaces, device or unit or communication connection, can be being electrical, mechanical or other form.

The described unit that illustrates as separating component can be or can also be physically separate, and the parts shown as unit can be or may not be physical location, i.e. may be located at a place, or can also be distributed on multiple NE.Some or all of unit therein can be selected according to the actual needs to realize the purpose of the present embodiment scheme.

It addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it is also possible to be that unit is individually physically present, it is also possible to two or more unit are integrated in a unit.Above-mentioned integrated unit both can realize to use the form of hardware, can realize to use the form of SFU software functional unit.

It should be noted that, one of ordinary skill in the art will appreciate that all or part of flow process realizing in above-described embodiment method, can be by computer program and complete to instruct relevant hardware, described program can be stored in a computer read/write memory medium, this program is upon execution, it may include such as the flow process of the embodiment of above-mentioned each method.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-Only Memory, ROM) or random store-memory body (Random Access Memory, RAM) etc..

Above MR imaging method provided by the present invention and device are described in detail, principle and the embodiment of the present invention are set forth by specific embodiment used herein, and the explanation of above example is only intended to help to understand method and the core concept thereof of the present invention；Simultaneously for one of ordinary skill in the art, according to the thought of the present invention, the most all will change, in sum, this specification content should not be construed as limitation of the present invention.

Claims (10)

1. a MR imaging method, it is characterised in that including:

Original image is carried out plural number high-pass filtering, it is thus achieved that filtered image；

From filtered image, obtain view data, the imaginary numbers in described view data is carried out point Section, and the real part numerical value in the described view data in each segmentation limit is carried out different normalizeds；

Numerical value after processing is multiplied as weighted value with the gray value of magnitude image, finally gives magnetic resonance Image.

Method the most according to claim 1, it is characterised in that described method also includes:

MRI described in the every aspect obtained is carried out minimum signal strength projection.

Method the most according to claim 1, it is characterised in that the high-pass filtering of described plural number is homomorphism High-pass filtering.

Method the most according to claim 1, it is characterised in that described obtain from filtered image Obtain view data, the imaginary numbers in described view data is carried out segmentation, and in each segmentation limit Real part numerical value in described view data carries out different normalizeds, including:

When the imaginary numbers in described view data is more than or equal to 0, by the reality in described view data Portion's numerical value is normalized to 1；When imaginary numbers is less than 0, to the real part numerical value normalizing in described view data Turn to the value between 0 and 1；

Or,

When the imaginary numbers in described view data is more than or equal to 0, by the reality in described view data Portion's numerical value is normalized to the value between 0 and 1；When imaginary numbers is less than 0, by described picture number Real part numerical value according to is normalized to 1；

Or,

The value directly the real part numerical value in described view data being normalized between 0 and 1.

Method the most according to claim 4, it is characterised in that described by described view data Value that real part numerical value is normalized between 0 and 1 particularly as follows:

According toIt is normalized to be positioned at 0 by the real part numerical value in described view data And the value between 1；

Wherein, W (r) is the numerical value after processing, R (ρ_HF(r)) it is real part numerical value.

6. a MR imaging apparatus, it is characterised in that including:

High pass filter unit, for carrying out plural number high-pass filtering, it is thus achieved that filtered image to original image；

Normalized unit, for obtaining view data, to described picture number from filtered image Imaginary numbers according to carries out segmentation, and to the real part numerical value in the described view data in each segmentation limit Carry out different normalizeds；

Weight calculation unit, the numerical value after processing is as the gray value phase of weighted value with magnitude image Take advantage of, obtain MRI.

Device the most according to claim 6, it is characterised in that described device also includes:

Projecting cell, for carrying out minimum signal strength throwing to MRI described in the every aspect obtained Shadow.

Device the most according to claim 6, it is characterised in that the high-pass filtering of described plural number is homomorphism High-pass filtering.

Device the most according to claim 6, it is characterised in that

Described normalized unit includes:

First arranges subelement, for when the imaginary numbers in described view data is more than or equal to 0, by institute The real part numerical value stated in view data is normalized to 1；

First varitron unit, for when the imaginary numbers in described view data is less than 0, by described image The value that real part numerical value in data is normalized between 0 and 1；

Or,

Described normalized unit includes:

Second arranges subelement, for when the imaginary numbers in described view data is less than 0, by described image Real part numerical value in data is normalized to 1；

Second varitron unit, for when the imaginary numbers in described view data is more than or equal to 0, by institute State the value that the real part numerical value in view data is normalized between 0 and 1；

Or,

Described normalized unit includes:

3rd varitron unit, directly is normalized to be positioned at 0 and 1 by the real part numerical value of described view data Between value.

Device the most according to claim 9, it is characterised in that described first varitron unit, Second varitron unit or the 3rd varitron unit specifically for,

According toIt is normalized to be positioned at 0 by the real part numerical value in described view data And the value between 1；

Wherein, W (r) is the numerical value after processing, R (ρ_HF(r)) it is real part numerical value.