CN108287325B - Image reconstruction method, device and equipment - Google Patents
Image reconstruction method, device and equipment Download PDFInfo
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- CN108287325B CN108287325B CN201810004857.9A CN201810004857A CN108287325B CN 108287325 B CN108287325 B CN 108287325B CN 201810004857 A CN201810004857 A CN 201810004857A CN 108287325 B CN108287325 B CN 108287325B
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Abstract
The invention discloses an image reconstruction method, device and equipment, wherein first coil data acquired by an array coil is acquired, first sensitivity spectrum data are obtained through calculation according to the first coil data, second coil data of a preset second visual field acquired by the array coil and third coil data of a preset second visual field acquired by a general coil are further acquired, second sensitivity spectrum data are obtained through calculation according to the second coil data and the third coil data, the second sensitivity spectrum data are combined with the first sensitivity spectrum data to obtain sensitivity spectrum data, and a reconstructed image with good uniformity and no artifact can be obtained through image reconstruction by using the sensitivity spectrum data.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a method, an apparatus, and a device for image reconstruction.
Background
The magnetic resonance apparatus is characterized by a long scanning time, and the imaging speed of the magnetic resonance apparatus needs to be increased in both aspects of fast imaging and improvement of imaging quality.
SENSE is a popular parallel imaging technique in the industry that utilizes the spatially distributed nature of the coil channel receivers to reduce scan time. Specifically, when scanning is performed, the imaging speed of the magnetic resonance device is increased by reducing the number of phase encoding steps, a folded image is scanned, and then the folded image is subjected to unfolding processing by utilizing the spatial distribution characteristic of the coil channel receiver, so that a complete image is reconstructed.
The quality of the reconstructed image is determined by performing de-rolling processing on the folded image by using the spatial distribution characteristic of the coil channel receiver, and the spatial distribution characteristic of the coil channel receiver is generally characterized by sensitivity spectrum data, so how to obtain accurate sensitivity spectrum data is a key influence factor of image reconstruction.
Disclosure of Invention
In view of this, the present application provides an image reconstruction method, apparatus and device, which can obtain more accurate sensitivity spectrum data, and further obtain a reconstructed image with better quality.
In a first aspect, the present invention provides an image reconstruction method for use in a magnetic resonance apparatus having an array coil and a general coil, the magnetic resonance apparatus being used for scanning a target object, the method comprising:
acquiring first coil data of a preset first view field acquired by the array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data;
acquiring second coil data of a preset second field of view acquired by the array coil and third coil data of the preset second field of view acquired by the general coil, and calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
calculating sensitivity spectrum correction data according to the second sensitivity spectrum data;
correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
and reconstructing an image by using the corrected sensitivity spectrum data.
Optionally, the calculating sensitivity spectrum data based on the first coil data as first sensitivity spectrum data includes:
calculating a sum of squares of absolute values of the first coil data as a first intermediate value;
and taking the quotient of the first coil data and the first intermediate value as first sensitivity spectrum data.
Optionally, the calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data includes:
and taking the quotient of the second coil data and the third coil data as second sensitivity spectrum data.
Optionally, the calculating sensitivity spectrum correction data according to the second sensitivity spectrum data includes:
calculating a sum of squares of absolute values of the second sensitivity spectrum data as a second intermediate value;
and performing square opening processing on the second intermediate value to obtain sensitivity spectrum correction data.
Optionally, the correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data includes:
and performing dot multiplication on the first sensitivity spectrum data and the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data.
Optionally, before the correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data, the method further includes:
and preprocessing the sensitivity spectrum correction data, wherein the preprocessing comprises polynomial fitting, low-pass filtering and/or threshold processing.
In a second aspect, the present invention provides an image reconstruction apparatus for use in a magnetic resonance device having an array coil and a general coil, with which a target object is scanned, the apparatus comprising:
the first sensitivity spectrum data acquisition unit is used for acquiring first coil data of a preset first visual field acquired by the array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data;
a second sensitivity spectrum data acquisition unit configured to acquire second coil data of a preset second field of view acquired by the array coil and third coil data of the preset second field of view acquired by the general coil, and calculate sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
the sensitivity spectrum correction data acquisition unit is used for calculating sensitivity spectrum correction data according to the second sensitivity spectrum data;
the sensitivity spectrum data correction unit is used for correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
and the image reconstruction unit is used for reconstructing an image by using the corrected sensitivity spectrum data.
Optionally, the first sensitivity spectrum data acquiring unit includes:
a first sensitivity spectrum data calculating subunit configured to calculate a sum of squares of absolute values of the first coil data as a first intermediate value; and taking the quotient of the first coil data and the first intermediate value as first sensitivity spectrum data.
Optionally, the second sensitivity spectrum data acquiring unit includes:
and the second sensitivity spectrum data calculation subunit is used for taking the quotient of the second coil data and the third coil data as second sensitivity spectrum data.
Optionally, the sensitivity spectrum correction data acquiring unit includes:
a sensitivity spectrum correction data calculation subunit configured to calculate a sum of squares of absolute values of the second sensitivity spectrum data as a second intermediate value; and carrying out square opening processing on the second intermediate value to obtain sensitivity spectrum correction data.
Optionally, the sensitivity spectrum data correcting unit includes:
and the sensitivity spectrum data calculating subunit is used for performing point multiplication processing on the first sensitivity spectrum data and the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data.
Optionally, the image reconstruction apparatus further includes:
and the sensitivity spectrum correction data preprocessing unit is used for preprocessing the sensitivity spectrum correction data, and the preprocessing comprises polynomial fitting, low-pass filtering and/or threshold processing.
In a third aspect, the present invention provides an image reconstruction apparatus, comprising: a memory and a processor, wherein the processor is capable of,
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the following steps according to instructions in the program code:
acquiring first coil data of a preset first view field acquired by the array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data;
acquiring second coil data of a preset second field of view acquired by the array coil and third coil data of the preset second field of view acquired by the general coil, and calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
calculating sensitivity spectrum correction data according to the second sensitivity spectrum data;
correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
and reconstructing an image by using the corrected sensitivity spectrum data.
The image reconstruction method obtains first coil data collected by an array coil, and first sensitivity spectrum data are obtained through calculation according to the first coil data. In order to obtain a reconstructed image with better display effect, the image reconstruction method provided by the application further acquires second coil data of a preset second visual field acquired by the array coil and third coil data of a preset second visual field acquired by the general coil, calculating to obtain second sensitivity spectrum data according to the second coil data and the third coil data, combining the second sensitivity spectrum data with the first sensitivity spectrum data to obtain sensitivity spectrum data, since the second sensitivity spectrum data is calculated based on the data acquired by the array coil and the general coil, the data acquired by the general coil can improve the uniformity of the data acquired by the array coil, therefore, the uniformity of the reconstructed image can be improved by combining the second sensitivity spectrum data, and therefore, the reconstructed image which is good in uniformity and free of artifacts can be obtained by utilizing the sensitivity spectrum data to reconstruct the image.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a schematic illustration of a scan result from an image scan using the SENSE technique;
FIG. 2 is a schematic representation of image reconstruction of a SENSE technique scan using a parallel imaging technique;
FIG. 3 is a schematic diagram of image data received by the receivers of each coil channel for an image scan using the SENSE technique;
FIG. 4 is a schematic diagram of a process for image reconstruction using parallel imaging techniques;
fig. 5 is a flowchart of an image reconstruction method according to an embodiment of the present application;
fig. 6 is a flowchart of an image reconstruction method in a specific application scenario according to an embodiment of the present application;
fig. 7 is a schematic diagram of a reconstructed image obtained by using the image reconstruction method provided in the embodiment of the present application;
fig. 8 is a structural diagram of an image reconstruction apparatus according to an embodiment of the present application;
fig. 9 is a schematic diagram of a hardware structure of an image reconstruction device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Because the magnetic resonance apparatus has a characteristic of long scanning time, when the magnetic resonance apparatus is used for scanning, problems of low imaging speed, low imaging quality and the like occur, and therefore, in order to solve the problem caused by the long scanning time of the magnetic resonance apparatus, the SENSE technology is generally adopted in the industry to reduce the scanning time of the magnetic resonance apparatus.
The SENSE technique exploits the spatially distributed nature of the coil channel receivers to reduce the scan time of the magnetic resonance apparatus. Specifically, when scanning is performed, the imaging speed of the magnetic resonance apparatus is increased by reducing the number of phase encoding steps, but reducing the number of phase encoding steps results in the scanned image being a folded image. Therefore, the folded image needs to be de-folded according to the spatial distribution characteristics of the coil channel receivers, so as to reconstruct a complete image without folding.
For ease of understanding, the SENSE technique will now be described with reference to the accompanying drawings:
as shown in fig. 1, for one magnetic resonance image, the magnetic resonance image may be folded by reducing the number of phase encoding steps without changing the scanning resolution. As shown in fig. 2, the folded magnetic resonance image is reconstructed by using the parallel imaging technique of the image space, so as to obtain a complete image without the folded image.
The method includes the steps that a parallel imaging technology of an image space is utilized to reconstruct a magnetic resonance image with a rolling and folding function, and the magnetic resonance image with the rolling and folding function needs to be subjected to de-rolling and folding processing according to the space distribution characteristics of receivers of each coil channel so as to reconstruct the image.
Specifically, the positions of each coil channel receiver in the space are different, which may cause the gray value of the image data received by each coil channel receiver to be different, and in the image data received by each coil channel receiver, the closer to the coil channel receiver, the brighter the gray value of the image data is, and conversely, the farther from the coil channel receiver, the darker the gray value of the image data is. Since each coil channel receiver is located at a different position in space, the gray values of the image data acquired by the different coil channel receivers are different for the same scanning object. Correspondingly, for the image data with the rolling, a complete image without the rolling can be solved according to the difference of the gray values of the image data with the rolling received by each coil channel receiver.
As shown in fig. 3, the left side of fig. 3 is a schematic diagram of the spatial positions of the coil channel receiver and the scanned human body, the coil channel receiver 1 is located in front of the scanned human body, and the coil channel receiver 2 is located behind the scanned human body. The right side of fig. 3 is the image data received by the coil channel receiver 1 and the image data received by the coil channel receiver 2, and it can be found through observation that, because the positions of the coil channel receiver 1 and the coil channel receiver 2 are different, the gray level of the image data received by each coil channel receiver is also different, in the image data received by the coil channel receiver 1, the gray level on the left side is brighter, and the gray level on the right side is darker, in the image data received by the coil channel receiver 2, the gray level on the left side is darker, and the gray level on the right side is brighter.
As shown in fig. 4, after the number of phase encoding steps is reduced, the image may be subjected to rolling, but since the positions of each coil channel receiver in the space are different, the gray values of the rolled image data received by each coil channel receiver are not identical, and based on the difference of the gray values of the rolled image data received by each coil channel receiver, a sensitivity spectrum corresponding to each rolled image data may be correspondingly established, and the image may be subjected to de-rolling processing by using the sensitivity spectrum distributed in the space, so as to reconstruct the image.
Specifically, the method for reconstructing the image by deconvolution processing is as follows:
1) a sensitivity spectrum S is calculated.
2) And calculating the corresponding sensitivity spectrum of the rolling point, wherein the calculation formula is as follows:
Sγ,ρ＝Sγ(rρ) Formula (5)
Where γ represents the coil channel, ρ represents the lap point, rρRepresenting the roll-fold point location.
3) For each roll-to-roll position rρHaving the following formula:
a＝Sγ,ρu formula (6)
Where a is the folded image data, such as the folded image received by the coil channel receiver 1 or the coil channel receiver 2 in fig. 4; and u is reconstructed image data.
The formula for calculating the reconstructed image data u using the regularized least squares method is as follows:
wherein psi-1Is a noise matrix, R is a regularization factor, H is used to denote the conjugate transpose,
is a pair of Sγ,ρAnd performing conjugate transpose processing.
In order to obtain a magnetic resonance scanning image with a better display effect, the image reconstruction method provided by the application adopts a new sensitivity spectrum calculation method, and based on the sensitivity spectrum calculation method, the rolling and folding processing is carried out on the rolling and folding image, and the scanning image is reconstructed. The image reconstruction method is applied to a magnetic resonance system with an array coil and a main coil, with which a target object is scanned.
Specifically, first coil data of a preset first view field acquired by an array coil is acquired, and first sensitivity spectrum data is calculated according to the first coil data; acquiring second coil data of a preset second visual field acquired by the array coil and third coil data of the preset second visual field acquired by the general coil, and calculating second sensitivity spectrum data according to the second coil data and the third coil data; calculating sensitivity spectrum correction data according to the second sensitivity spectrum data; and correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain sensitivity spectrum data, and further performing image reconstruction by using the sensitivity spectrum data.
The image reconstruction method obtains first coil data collected by an array coil, and first sensitivity spectrum data are obtained through calculation according to the first coil data. In order to obtain a reconstructed image with better display effect, the image reconstruction method provided by the application further acquires second coil data of a preset second visual field acquired by the array coil and third coil data of a preset second visual field acquired by the general coil, calculating to obtain second sensitivity spectrum data according to the second coil data and the third coil data, combining the second sensitivity spectrum data with the first sensitivity spectrum data to obtain sensitivity spectrum data, since the second sensitivity spectrum data is calculated based on the data acquired by the array coil and the general coil, the data acquired by the general coil can improve the uniformity of the data acquired by the array coil, therefore, the uniformity of the reconstructed image can be improved by combining the second sensitivity spectrum data, and therefore, the reconstructed image which is good in uniformity and free of artifacts can be obtained by utilizing the sensitivity spectrum data to reconstruct the image.
Method embodiment one
Referring to fig. 5, a flowchart of an image reconstruction method provided in this embodiment is an image reconstruction method applied to a magnetic resonance apparatus having an array coil and a general coil, and when the magnetic resonance apparatus is used to scan a target object, the image reconstruction method includes:
step 501: and acquiring first coil data of a preset first view field acquired by the array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data.
In practical application, when a part to be scanned is scanned by using a magnetic resonance device, a preset first view field is firstly determined, and after first coil data of the part to be scanned in the preset first view field is acquired by using an array coil in the magnetic resonance device, the first coil data is acquired and used for calculating sensitivity spectrum data.
Acquiring first coil data of a preset first view field acquired by an array coil, and taking sensitivity spectrum data obtained by calculation based on the first coil data as first sensitivity spectrum data, specifically, calculating the square sum of absolute values of the first coil data as a first intermediate value as shown in formula (1) for calculating the first sensitivity spectrum data based on the first coil data; taking the quotient of the first coil data and the first intermediate value as first sensitivity spectrum data:
wherein SLγRepresenting first sensitivity spectrum data, CγRepresenting the first coil data.
It should be noted that the array coil includes γ coil channel receivers, and the first coil data CγRepresents the acquired coil data of gamma coil channel receivers in the array coil, and thus, CγIs a gamma matrix of coil data acquired by receivers corresponding to gamma coil channels in the array coil. Correspondingly, the first sensitivity spectrum data SL calculated by the formula (1)γRepresenting sensitivity spectrum data of gamma coil channel receivers in the array coil, SLγTo correspond toGamma matrices of receiver sensitivity spectrum data for gamma coil channels in the array coil.
In addition, other methods may be adopted, and the first sensitivity spectrum data is calculated from the first coil data, and the method of acquiring the first sensitivity spectrum data is not limited in any way.
Step 502: and acquiring second coil data of a preset second visual field acquired by the array coil and third coil data of the preset second visual field acquired by the general coil, and calculating sensitivity spectrum data based on the second coil data and the third coil data to serve as second sensitivity spectrum data.
In practical application, when a part to be scanned is scanned by using the magnetic resonance equipment, a preset second field of view is predetermined, the part to be scanned in the preset second field of view is scanned by using an array coil in the magnetic resonance equipment so as to acquire second coil data, then the array coil is switched to a general coil, and the part to be scanned in the preset second field of view is scanned by using the general coil in the magnetic resonance equipment so as to acquire third coil data. According to the embodiment of the invention, the second sensitivity spectrum data is calculated based on the collected second coil data and the third coil data.
When the second sensitivity spectrum data is calculated according to the second coil data and the third coil data, a quotient of the second coil data and the third coil data can be specifically used as the second sensitivity spectrum data, and a formula is as follows:
wherein, SGγRepresenting secondary sensitivity spectral data, C'γRepresenting the second coil data and Q representing the third coil data.
It should be noted that the array coil includes γ coil channel receivers and the second coil data C'γRepresenting gamma lines in the array coilThe gamma coil data, thus C ', acquired while the coil channel receiver is scanning the site to be scanned in the preset large field of view'γIs a gamma matrix of acquired coil data corresponding to all coil channel receivers in the array coil. And only one coil-path receiver is included in the substantial coil, so that the third coil data Q represents the coil data acquired when the coil-path receiver in the substantial coil scans the portion to be scanned in the preset large field of view, and thus the third coil data Q is a matrix corresponding to the coil data acquired by the coil-path receiver in the substantial coil.
Accordingly, the second sensitivity spectrum data SG calculated by the formula (2)γStill representing sensitivity spectrum data for gamma coil channel receivers in the array coil, and thus, SGγAre gamma matrices of receiver sensitivity spectrum data corresponding to all coil channels in the array coil.
In addition, other methods may be adopted to calculate the second sensitivity spectrum data according to the second coil data and the third coil data, and no limitation is made to the acquisition method of the second sensitivity spectrum data.
It should be noted that step 501 and step 502 are two parallel execution steps, and the execution order of step 501 and step 502 is not sequential, and step 501 may be executed first and then step 502 is executed, or step 502 may be executed first and then step 501 is executed.
Step 503: and calculating sensitivity spectrum correction data according to the second sensitivity spectrum data.
Since the first sensitivity spectrum data acquired in step 501 is sensitivity spectrum data calculated based on only the first coil data acquired by the array coil, the first sensitivity spectrum data is used to reconstruct an image, and the obtained image has poor uniformity although no artifact exists. In step 502, the second coil data obtained by scanning the array coil and the third coil data obtained by scanning the general coil are combined, and the second sensitivity spectrum data is obtained through calculation.
In order to combine the second sensitivity spectrum data acquired in step 502 with the first sensitivity spectrum data acquired in step 501, sensitivity spectrum correction data needs to be calculated according to the second sensitivity spectrum data.
Specifically, when the sensitivity spectrum correction data is calculated, the sum of squares of absolute values of the second sensitivity spectrum data may be calculated first as a second intermediate value; and carrying out square opening processing on the second intermediate value to obtain sensitivity spectrum correction data, wherein the formula is as follows:
where T denotes sensitivity spectrum correction data.
Specifically, the second sensitivity spectrum data SG of each acquisition channel gamma is calculatedγSquaring the matrix modulus, and dividing each second sensitivity spectrum data SGγAfter the square of the matrix modulus is summed and calculated, the square is opened to obtain the first sensitivity spectrum data SL for correctionγCorrects the data T by the sensitivity spectrum of (a).
It should be noted that the sensitivity spectrum correction data T calculated according to the formula (3) is a matrix for correction.
Of course, other calculation methods may also be adopted, and the sensitivity spectrum correction data is calculated according to the second sensitivity spectrum data, where the method for calculating the sensitivity spectrum correction data is not limited at all.
Step 504: and correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data.
The sensitivity spectrum correction data T obtained in step 503 is used to correct the first sensitivity spectrum data SL obtained in step 501γAnd correcting to obtain corrected sensitivity spectrum data.
Specifically, the first sensitivity spectrum data and the sensitivity spectrum correction data may be subjected to a dot product process to obtain corrected sensitivity spectrum data, which is as follows:
Sγ＝SLγt formula (4)
Wherein S isγRepresenting corrected sensitivity spectrum data, SLγRepresenting the first sensitivity spectrum data.
In the formula (4), SLγWith T being calculated by dot multiplication, i.e. multiplication of elements of corresponding positions of the matrix, due to the first sensitivity spectrum data SLγFor gamma matrices corresponding to all coil channel receivers in the array coil, and correspondingly corrected sensitivity spectrum data SγAlso gamma matrices corresponding to all the coil channel receivers in the array coil.
Since the sensitivity spectrum correction data T is based on the second sensitivity spectrum data SGγObtained by calculation, and therefore, the first sensitivity spectrum data SL is corrected using the sensitivity spectrum correction data T obtained in step 503γCorrection is carried out, i.e. the second sensitivity spectrum data SG is realizedγWith first sensitivity spectrum data SLγBy using the sensitivity spectrum data S obtained after combinationγThe image is reconstructed, the obtained reconstructed image has no artifact and good uniformity.
Of course, other calculation methods may also be adopted to correct the first sensitivity spectrum data, and no limitation is made on the correction method of the first sensitivity spectrum data.
Step 505: and reconstructing an image by using the corrected sensitivity spectrum data.
Obtaining sensitivity spectrum data SγThe sensitivity spectrum data S can then be utilizedγAnd carrying out image reconstruction.
Specifically, the sensitivity spectrum corresponding to the convolved point on the data image acquired by each acquisition channel may be calculated first, and the following formula is generally adopted:
Sy,ρ＝Sγ(rρ) Formula (5)
Where γ represents the acquisition channel, ρ represents the fold point on the acquired image, rρRepresenting the position of the wrap-around point on the image.
For the position of each rolling point, the following formula is satisfied:
a＝Sγ,ρu formula (6)
Where a represents the folded image data and u represents the image data to be reconstructed, where no folding exists in the reconstructed image data.
And (3) calculating reconstructed image data by adopting a regularized least square method, and adopting the following formula:
wherein psi-1Is a noise matrix, R is a regularization factor, H is used to denote the conjugate transpose,
is a pair of Sγ,ρAnd performing conjugate transpose processing.
It should be noted that before the step 504 is executed, that is, before the sensitivity spectrum correction data is used to correct the first sensitivity spectrum data to obtain the corrected sensitivity spectrum data, the sensitivity spectrum correction data may be preprocessed, specifically, polynomial fitting, low-pass filtering, and/or threshold processing may be performed on the sensitivity spectrum correction data to ensure that the obtained sensitivity spectrum correction data is smooth in appearance.
The image reconstruction method provided by the embodiment obtains the first coil data acquired by the array coil, and calculates the first sensitivity spectrum data according to the first coil data, because the first coil data is the data acquired only by using the array coil, if the image is reconstructed by directly using the first sensitivity spectrum data, the obtained reconstructed image has no artifact, but based on the reason that the uniformity of the data acquired by the array coil is poor, the reconstructed image has poor uniformity and a dark central area. In order to obtain a reconstructed image with a better display effect, the image reconstruction method provided in this embodiment further obtains second coil data of a preset second field of view acquired by the array coil and third coil data of a preset second field of view acquired by the general coil, calculates to obtain second sensitivity spectrum data according to the second coil data and the third coil data, and combines the second sensitivity spectrum data with the first sensitivity spectrum data to obtain sensitivity spectrum data, because the second sensitivity spectrum data is calculated based on the data acquired by the array coil and the general coil, the data acquired by the general coil can improve the uniformity of the data acquired by the array coil, so that the uniformity of the reconstructed image can be improved by combining the second sensitivity spectrum data, and therefore, the uniformity can be obtained by reconstructing the image by using the sensitivity spectrum data, and there are no reconstructed images of artifacts.
The following describes an image reconstruction method in the first embodiment of the method with reference to practical applications:
method embodiment two
Referring to fig. 6, a flowchart of an image reconstruction method provided in this embodiment is shown.
Step 601: after a part to be scanned is scanned by using magnetic resonance equipment, the array coil acquires first coil data in a preset first visual field.
In practical application, when the magnetic resonance device is used for scanning a part to be scanned, the range of the part to be scanned can be used as a preset first view field, the magnetic resonance device is used for scanning the part to be scanned in the preset first view field, and the array coil is used for acquiring first coil data in the preset first view field.
Step 602: on the premise of not changing the scanning resolution, the phase encoding steps are reduced, and after the part to be scanned is scanned again by using the magnetic resonance equipment, the array coil acquires image rolling data.
Because the scanning time of the magnetic resonance equipment is too long, the imaging quality of the magnetic resonance equipment is low, and therefore, in order to improve the imaging quality of the magnetic resonance equipment, in practical application, on the premise of not changing the scanning resolution, the scanning speed of the magnetic resonance equipment is improved by reducing the number of phase encoding steps, and the imaging quality of the magnetic resonance equipment is further improved.
Specifically, in order to improve the quality of the finally reconstructed image, it is necessary to ensure the consistency of the part to which the data acquired by the array coils in step 602 and step 601 belong as much as possible, for example, if the data acquired by the array coils in step 601 is the data of the left brain in the head of the human body, it is necessary to ensure that the data acquired by the array coils in step 602 is also the data of the left brain as much as possible, so that it is necessary to execute step 601 as soon as the execution of step 602 is completed to avoid the problem that the part to which the data belong is inconsistent due to the inevitable movement of the head of the human body caused by long time lag, for example, to avoid the data of the right brain acquired by the array coils in step 602, which is not the data of the left brain, but is the data of the right brain acquired.
Therefore, in practical applications, after step S601, the magnetic resonance apparatus reduces the number of phase encoding steps as soon as possible, scans the to-be-scanned region in the preset first field of view again, and acquires the image volume data by the array coil. Since the image data obtained by reducing the number of phase encoding steps has a wrap-around, it is necessary to perform a wrap-around removal process on the image wrap-around data, so as to obtain reconstructed image data with a better display effect.
Step 603: after the part to be scanned is scanned again by using the magnetic resonance equipment, the array coil acquires second coil data in a preset second visual field, and the general coil acquires third coil data in the second visual field.
After step 602, the magnetic resonance apparatus sets the field of view to the second field of view, and performs normal scanning on the part to be scanned again, and after the array coil acquires the second coil data in the second field of view, in order to ensure consistency of the second coil data and the third coil data and avoid the artifact problem, the magnetic resonance apparatus needs to immediately switch from the array coil to the general coil, and acquire the third coil data in the second field of view by using the general coil.
Step 604: calculating sensitivity spectrum data based on the first coil data as first sensitivity spectrum data; and calculating sensitivity spectrum data as second sensitivity spectrum data based on the second coil data and the third coil data.
Step 605: and calculating sensitivity spectrum correction data according to the second sensitivity spectrum data, and correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data.
Step 606: and reconstructing the image volume-folding data by using the corrected sensitivity spectrum data.
The first sensitivity spectrum data is sensitivity spectrum data obtained by calculating first coil data only according to array coil scanning, so that the first sensitivity spectrum data is directly utilized to carry out de-rolling processing on the image rolling and folding data, and an obtained reconstructed image has poor uniformity although no artifact exists. Therefore, in order to obtain a reconstructed image with better display effect, the first sensitivity spectrum data needs to be corrected.
Specifically, the second coil data and the third coil data are used for calculation to obtain second sensitivity spectrum data. Because the data acquired by the general coil has better uniformity, sensitivity spectrum correction data is calculated according to the second sensitivity spectrum data, the first sensitivity spectrum data is corrected by using the sensitivity spectrum correction data, and the corrected sensitivity spectrum data is used for reconstructing an image, so that a reconstructed image which has no artifact and better uniformity can be obtained.
It should be noted that the second embodiment of the method is only one specific implementation manner of the image reconstruction method in the present invention, and is not limited to the specific implementation manner of the present invention, and other implementation manners exist in practical applications, and are not described here.
It should be noted that, in the first and second embodiments of the method, the size relationship between the preset first view and the preset second view is not limited, and specifically, the preset second view may be larger than the preset first view, may be equal to the preset first view, and may also be smaller than the preset first view.
In one case, when the preset second field of view is larger than the preset first field of view, the second sensitivity spectrum data obtained by calculation based on the second coil data acquired by the array coil in the preset second field of view and the third coil data acquired by the general coil in the preset second field of view can be used for not only reconstructing the image folded data acquired by the array coil in the first field of view, but also reconstructing the image folded data of other parts (in the second field of view) acquired by the array coil, so that the reconstruction steps of the subsequent image folded data of other parts are saved, and the efficiency is improved.
For example, the left brain in the head of the human body is scanned by using the magnetic resonance apparatus, the specific visual field range of the left brain is set as a preset first visual field, the specific visual field range of the head of the human body is set as a preset second visual field, the second coil data and the third coil data in the visual field range of the head of the human body are acquired by using the array coil and the general coil respectively, the second sensitivity spectrum data is calculated and obtained based on the second coil data and the third coil data, and when other parts (such as the right brain) in the head of the human body are scanned subsequently, the second sensitivity spectrum data can be directly used for reconstructing image volume folding data of other parts without acquiring the second coil data and the third coil data in the visual field range of the head of the human body again.
In another case, when the preset second field of view is equal to the preset first field of view, the field of view does not need to be adjusted after step 602, the magnetic resonance device is directly used to scan the portion to be scanned again, the array coil is used to acquire the preset first field of view (i.e., the second field of view) to obtain second coil data, the general coil is used to acquire the preset first field of view to obtain third coil data, and the second sensitivity spectrum data is obtained by calculation.
In another case, when the preset second field of view is smaller than the preset first field of view, the second sensitivity spectrum data calculated based on the second coil data and the third coil data acquired by the array coil and the main coil in step 603 only correspond to a part of the first sensitivity spectrum data calculated in step 601, and in order to obtain the second sensitivity spectrum data which can correspond to all the first sensitivity spectrum data, the embodiment of the invention may perform compensation calculation on the second sensitivity spectrum data by using an extrapolation method based on the smooth characteristic of the sensitivity spectrum data and the characteristic of the image of the portion to be scanned, so as to obtain more accurate second sensitivity spectrum data which can correspond to all the first sensitivity spectrum data.
In summary, the image reconstruction method according to the first embodiment of the method is used for reconstructing an image in practical application, so that a reconstructed image with a good display effect can be obtained, and the reconstructed image has no artifact and good uniformity.
As shown in fig. 7, in order to obtain a display effect by reconstructing an image by using the image reconstruction method provided in this embodiment, it can be found through observation that an artifact does not exist in the image reconstructed by using the image reconstruction method provided in this embodiment, and the uniformity of the image is good.
Device embodiment
Referring to fig. 8, a block diagram of an image reconstruction apparatus provided in this embodiment is applied to a magnetic resonance device having an array coil and a general coil, and scanning a target object with the magnetic resonance device, and the apparatus includes:
a first sensitivity spectrum data obtaining unit 801, configured to obtain first coil data of a preset first field of view acquired by the array coil, and calculate sensitivity spectrum data based on the first coil data, as first sensitivity spectrum data;
a second sensitivity spectrum data acquiring unit 802 configured to acquire second coil data of a preset second field of view acquired by the array coil and third coil data of the preset second field of view acquired by the general coil, and calculate sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
a sensitivity spectrum correction data obtaining unit 803, configured to calculate sensitivity spectrum correction data according to the second sensitivity spectrum data;
a sensitivity spectrum data correcting unit 804, configured to correct the first sensitivity spectrum data by using the sensitivity spectrum correction data, so as to obtain corrected sensitivity spectrum data;
an image reconstruction unit 805, configured to perform image reconstruction using the corrected sensitivity spectrum data.
Optionally, the first sensitivity spectrum data acquiring unit includes:
a first sensitivity spectrum data calculating subunit configured to calculate a sum of squares of absolute values of the first coil data as a first intermediate value; taking the quotient of the first coil data and the first intermediate value as first sensitivity spectrum data;
sensitivity spectrum data can be calculated as first sensitivity spectrum data by using formula (1);
wherein SLγRepresenting said first sensitivity spectrum data, CγRepresenting the first coil data.
Optionally, the second sensitivity spectrum data acquiring unit includes:
a second sensitivity spectrum data calculation subunit configured to use a quotient of the second coil data and the third coil data as second sensitivity spectrum data;
sensitivity spectrum data can be calculated as second sensitivity spectrum data by using formula (2);
wherein, SGγRepresenting the secondary sensitivity spectrum data, C'γRepresents the second coil data, and Q represents the third coil data.
Optionally, the sensitivity spectrum correction data acquiring unit includes:
a sensitivity spectrum correction data calculation subunit configured to calculate a sum of squares of absolute values of the second sensitivity spectrum data as a second intermediate value; performing square opening processing on the second intermediate value to obtain sensitivity spectrum correction data;
sensitivity spectrum correction data can be calculated by using formula (3);
wherein T represents the sensitivity spectrum correction data.
Optionally, the sensitivity spectrum data correcting unit includes:
the sensitivity spectrum data calculation subunit is used for performing point multiplication processing on the first sensitivity spectrum data and the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
the corrected sensitivity spectrum data can be calculated by using the formula (4);
Sγ＝SLγt formula (4)
Wherein S isγRepresenting corrected sensitivity spectrum data, SLγRepresenting the first sensitivity spectrum data.
Optionally, the image reconstruction apparatus further includes:
and the sensitivity spectrum correction data preprocessing unit is used for preprocessing the sensitivity spectrum correction data, and the preprocessing comprises polynomial fitting, low-pass filtering and/or threshold processing.
The apparatus shown in fig. 8 of this embodiment is an apparatus corresponding to the method described in the method embodiment, and the specific implementation method is similar to that described in the method embodiment, and details are not repeated here.
Correspondingly, an embodiment of the present invention further provides an image reconstruction apparatus, as shown in fig. 9, which may include:
a processor 901, a memory 902, an input device 903, and an output device 904. The number of the processors 801 may be one or more, and one processor is taken as an example in fig. 9. In some embodiments of the present invention, the processor 901, the memory 902, the input device 903 and the output device 904 may be connected through a bus or other means, wherein the connection through the bus is exemplified in fig. 9.
The memory 902 may be used for storing software programs and modules, and the processor 901 executes various functional applications and data processing of the light field uniformity detection device by running the software programs and modules stored in the memory 902. The memory 902 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like. Further, the memory 902 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. The input device 903 may be used to receive input numeric or character information and generate signal inputs related to user settings and functional control of the light field uniformity detection apparatus.
Specifically, in this embodiment, the processor 901 loads an executable file corresponding to one or more processes of an application program into the memory 902 according to the following instructions, and the processor 901 runs the application program stored in the memory 902, thereby implementing various functions:
acquiring first coil data of a preset first FOV acquired by the array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data;
acquiring second coil data acquired by the array coil to a preset second FOV and third coil data acquired by the general coil to the preset second FOV, and calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
calculating sensitivity spectrum correction data according to the second sensitivity spectrum data;
correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
and reconstructing an image by using the corrected sensitivity spectrum data.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing describes an image reconstruction method, an image reconstruction device, and an image reconstruction apparatus provided in an embodiment of the present application in detail, and a specific example is applied in the present application to explain the principle and the embodiment of the present application, and the description of the foregoing embodiments is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (5)
1. An image reconstruction method for use in a magnetic resonance apparatus having an array coil and a general coil, with which a target object is scanned, the method comprising:
acquiring first coil data of a preset first view field acquired by the array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data;
acquiring second coil data of a preset second field of view acquired by the array coil and third coil data of the preset second field of view acquired by the general coil, and calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
calculating sensitivity spectrum correction data according to the second sensitivity spectrum data;
correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
carrying out image reconstruction by using the corrected sensitivity spectrum data;
the calculating sensitivity spectrum data based on the first coil data as first sensitivity spectrum data includes:
calculating a sum of squares of absolute values of the first coil data as a first intermediate value;
taking the quotient of the first coil data and the first intermediate value as first sensitivity spectrum data;
the calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data includes:
taking the quotient of the second coil data and the third coil data as second sensitivity spectrum data;
calculating sensitivity spectrum correction data according to the second sensitivity spectrum data, wherein the calculation comprises the following steps:
calculating a sum of squares of absolute values of the second sensitivity spectrum data as a second intermediate value;
performing square opening processing on the second intermediate value to obtain sensitivity spectrum correction data;
the correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data includes:
and performing dot multiplication on the first sensitivity spectrum data and the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data.
2. The image reconstruction method according to claim 1, wherein before the correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain the corrected sensitivity spectrum data, the method further comprises:
and preprocessing the sensitivity spectrum correction data, wherein the preprocessing comprises polynomial fitting, low-pass filtering and/or threshold processing.
3. An apparatus for image reconstruction, the apparatus being applied to a magnetic resonance device having an array coil and a general coil, with which a target object is scanned, the apparatus comprising:
the first sensitivity spectrum data acquisition unit is used for acquiring first coil data of a preset first visual field acquired by the array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data;
a second sensitivity spectrum data acquisition unit configured to acquire second coil data of a preset second field of view acquired by the array coil and third coil data of the preset second field of view acquired by the general coil, and calculate sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
the sensitivity spectrum correction data acquisition unit is used for calculating sensitivity spectrum correction data according to the second sensitivity spectrum data;
the sensitivity spectrum data correction unit is used for correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
the image reconstruction unit is used for reconstructing an image by using the corrected sensitivity spectrum data;
the first sensitivity spectrum data acquisition unit includes:
a first sensitivity spectrum data calculating subunit configured to calculate a sum of squares of absolute values of the first coil data as a first intermediate value; taking the quotient of the first coil data and the first intermediate value as first sensitivity spectrum data;
the second sensitivity spectrum data acquisition unit includes:
a second sensitivity spectrum data calculation subunit configured to use a quotient of the second coil data and the third coil data as second sensitivity spectrum data;
the sensitivity spectrum correction data acquisition unit includes:
a sensitivity spectrum correction data calculation subunit configured to calculate a sum of squares of absolute values of the second sensitivity spectrum data as a second intermediate value; performing square opening processing on the second intermediate value to obtain sensitivity spectrum correction data;
the sensitivity spectrum data correction unit includes:
and the sensitivity spectrum data calculating subunit is used for performing point multiplication processing on the first sensitivity spectrum data and the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data.
4. The image reconstruction apparatus according to claim 3, wherein the image reconstruction device further comprises:
and the sensitivity spectrum correction data preprocessing unit is used for preprocessing the sensitivity spectrum correction data, and the preprocessing comprises polynomial fitting, low-pass filtering and/or threshold processing.
5. An image reconstruction apparatus, characterized in that the apparatus comprises: a memory and a processor, wherein the processor is capable of,
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the following steps according to instructions in the program code:
acquiring first coil data of a preset first view field acquired by an array coil, and calculating sensitivity spectrum data based on the first coil data to serve as first sensitivity spectrum data;
acquiring second coil data of a preset second field of view acquired by the array coil and third coil data of the preset second field of view acquired by a general coil, and calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data;
calculating sensitivity spectrum correction data according to the second sensitivity spectrum data;
correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data;
carrying out image reconstruction by using the corrected sensitivity spectrum data;
the calculating sensitivity spectrum data based on the first coil data as first sensitivity spectrum data includes:
calculating a sum of squares of absolute values of the first coil data as a first intermediate value;
taking the quotient of the first coil data and the first intermediate value as first sensitivity spectrum data;
the calculating sensitivity spectrum data based on the second coil data and the third coil data as second sensitivity spectrum data includes:
taking the quotient of the second coil data and the third coil data as second sensitivity spectrum data;
calculating sensitivity spectrum correction data according to the second sensitivity spectrum data, wherein the calculation comprises the following steps:
calculating a sum of squares of absolute values of the second sensitivity spectrum data as a second intermediate value;
performing square opening processing on the second intermediate value to obtain sensitivity spectrum correction data;
the correcting the first sensitivity spectrum data by using the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data includes:
and performing dot multiplication on the first sensitivity spectrum data and the sensitivity spectrum correction data to obtain corrected sensitivity spectrum data.
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