WO2020133527A1 - Procédé, dispositif et appareil pour une séparation eau-graisse utilisant une image de résonance magnétique, et support d'enregistrement - Google Patents

Procédé, dispositif et appareil pour une séparation eau-graisse utilisant une image de résonance magnétique, et support d'enregistrement Download PDF

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WO2020133527A1
WO2020133527A1 PCT/CN2018/125855 CN2018125855W WO2020133527A1 WO 2020133527 A1 WO2020133527 A1 WO 2020133527A1 CN 2018125855 W CN2018125855 W CN 2018125855W WO 2020133527 A1 WO2020133527 A1 WO 2020133527A1
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solution
pixel
processed
phase factor
water
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PCT/CN2018/125855
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Chinese (zh)
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郑海荣
邹超
刘新
彭浩
程传力
贺强
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深圳先进技术研究院
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging

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  • the present disclosure relates to the technical field of image processing, for example, to a method, device, device and storage medium for separating water and fat based on magnetic resonance images.
  • the highlighted fat signal will affect the diagnosis of the lesion, so it is often necessary to use fat compression technology.
  • the methods in the related art have various problems: the methods of fat saturation and water excitation will fail at the place where the field displacement is large; the method of inversion recovery will greatly reduce the signal-to-noise ratio of the image.
  • fat signals are also an important diagnostic basis for heart and lung disease detection. Therefore, accurate fat quantification and separation of water and fat are crucial.
  • the most commonly used in water-fat separation is the chemical shift-coded imaging method.
  • the multi-echo-based chemical shift coding imaging method uses the difference in the resonance frequency of the hydrogen atoms in the water lipid due to the chemical environment, and collects signals at different echo times to make the difference between the water lipid phase; by least squares In the way of fitting, the signal intensity of water and fat is calculated to complete the separation of water and fat.
  • this method requires accurate estimation of the displacement of the main magnetic field B 0 .
  • the water-fat separation method in the related art is prone to the phenomenon of water-fat separation when dealing with the object space discontinuity or the area with low signal-to-noise ratio. Therefore, there is an urgent need for a fast and stable field image estimation method, especially for the case of low image signal-to-noise ratio, on the basis of which the correct estimation of water and fat components is completed.
  • Embodiments of the present disclosure provide a method, device, equipment, and storage medium for separating water and fat based on magnetic resonance images, which can quickly and stably estimate a field map, and complete correct estimation of water and fat components based on this.
  • the disclosed embodiments of the present disclosure provide a water-fat separation method based on magnetic resonance images, including:
  • phase factor candidate solutions include the global optimal solution and the inverse solution corresponding to the global optimal solution
  • the water-fat conversion area is determined, and the target phase factor solution for each pixel to be processed in the water-fat conversion area is calculated;
  • the water map and fat map in the magnetic resonance image are extracted.
  • An embodiment of the present disclosure also provides a water-fat separation device based on a magnetic resonance image, which may include:
  • the solution set division module is set to acquire each pixel to be processed in the magnetic resonance image, calculate the phase factor candidate solution for each pixel to be processed, and divide the multiple phase factor solutions in the phase factor candidate solution to the first A solution set and a second solution set, where the candidate solution of the phase factor includes a global optimal solution and a partial and inverse solution corresponding to the global optimal solution;
  • the water-fat conversion area determination module is set to determine the water-fat conversion area based on the phase factor solution corresponding to each pixel to be processed in the first solution set and the second solution set, and calculate each pixel to be processed in the water-fat conversion area The target phase factor solution;
  • the target phase factor solution determination module is set to determine the target phase factor solution of each pixel to be processed among the remaining pixels to be processed based on the target phase factor solution of each pixel to be processed in the water-fat conversion area and the water-fat conversion area ;
  • the water-fat image separation module is configured to de-extract the water map and fat map in the magnetic resonance image according to the target phase factor of each pixel to be processed in the magnetic resonance image. .
  • An embodiment of the present disclosure also provides a device, which may include:
  • One or more processors are One or more processors;
  • Memory set to store one or more programs
  • the one or more processors When one or more programs are executed by one or more processors, the one or more processors implement the water-fat separation method based on the magnetic resonance image provided by any embodiment of the present disclosure.
  • An embodiment of the present disclosure also provides a computer-readable storage medium that stores a computer program, which when executed by a processor implements the water-fat separation method based on the magnetic resonance image provided by any embodiment of the present disclosure.
  • the calculated phase factor candidate solution for each pixel to be processed in the magnetic resonance image is calculated, and the Multiple phase factor solutions are divided into the first solution set and the second solution set respectively to simplify the calculation; then, based on the phase factor solutions corresponding to each pixel to be processed in the first solution set and the second solution set, the magnetic Resonate the water-fat conversion area in the image, and calculate the target phase factor solution for each pixel to be processed in the water-fat conversion area; further, the water-fat conversion area is used as the known area, according to the known area and the water-fat conversion area
  • the target phase factor solution of each pixel to be processed in each of the remaining pixels to be processed determines the target phase factor solution of each pixel to be processed among the remaining pixels to be processed, and the target phase factor solution of the unknown area is solved according to the known area; finally, according to the magnetic resonance
  • the target phase factor of each pixel to be processed in the image is used to extract the water map and
  • FIG. 1 is a flow chart of a method for separating water and fat based on magnetic resonance images in an embodiment
  • FIG. 2 is a flowchart of another method for separating water and fat based on magnetic resonance images in an embodiment
  • 2A is a schematic diagram of neighboring pixels of pixels to be processed in a water-fat separation method for magnetic resonance images according to an embodiment
  • FIG. 3 is a flowchart of another method for separating water and fat based on magnetic resonance images in an embodiment
  • FIG. 3A is a schematic diagram of an edge pixel pair of a known area and a sub-area to be solved of a water-fat separation method of a magnetic resonance image in an embodiment
  • FIG. 4 is a flowchart of another method for separating water and fat based on magnetic resonance images in an embodiment
  • 4A is a schematic diagram of a result of performing water-fat separation on an abdomen image of a human body in a water-fat separation method based on the magnetic resonance image provided in this embodiment;
  • FIG. 5 is a structural diagram of a water-fat separation device based on a magnetic resonance image in an embodiment
  • FIG. 6 is a schematic structural diagram of a device in an embodiment.
  • the basic principle of water-fat separation may be based on the ambiguity of water-fat signals in chemical shift coding imaging, for example, for a certain
  • the signal collected by each pixel can be expressed as:
  • the water-fat chemical shift signal model can be expressed as follows:
  • S(TE n ) is the complex signal collected at the echo time TE n
  • ⁇ w is the intensity of the water signal
  • ⁇ f is the intensity of the fat signal
  • f F is the chemical shift frequency
  • ⁇ is the main magnetic field shift ie Field displacement.
  • the multi-peak model and Factors of the decay process in order to obtain the ratio of fat signals more accurately, the multi-peak model and Factors of the decay process.
  • the field displacement obtained from the model (2) can be used as the initial value of the iteration, and the multi-peak and The signal model (3) replaces the model (2) to solve the nonlinear least squares fit:
  • ⁇ p is the relative amplitude of the p-th fat peak with chemical shift f F, p , Pending Attenuation value.
  • n 1, 2, ..., N, versus Water and fat value.
  • phase factor solution p B can be introduced instead of the field displacement ⁇ .
  • the phase factor solution p B can be expressed by the following formula:
  • the minimum fitting error R(p B ) of the phase factor solution p B can be expressed by the following formula:
  • a + (p B ) is the generalized inverse of the matrix A(p B ). That is, according to the formula (4) obtained minimum fitting error R (p B) can be determined with a minimum fitting error determined R (p B) corresponding to the phase factor solution p B.
  • the field displacement ⁇ can be determined according to the phase factor solution p B , and then the water-fat signal is separated on the basis of the known field displacement ⁇ . It can be seen from this that it is very important to find the optimal solution of the phase factor solution p B.
  • the optimization method of formula (6) may have at least one local minimum (for example, there may be two local minimums), that is, there is at least one minimum fitting error R(p B ). Therefore, the above local The minimum value is selected to make the phase factor solution p B which can make the whole field displacement map the smoothest.
  • FIG. 1 is a flowchart of a method for separating water and fat based on a magnetic resonance image in an embodiment.
  • This embodiment can be applied to the case of water-fat separation based on a magnetic resonance image, for example, the case of water-fat separation for a magnetic resonance image with a low signal-to-noise ratio.
  • the method may be performed by a water-fat separation device based on a magnetic resonance image provided by an embodiment of the present disclosure, and the device may be implemented by software and/or hardware. Referring to FIG. 1, the method of this embodiment includes the following steps.
  • phase factor candidate solution includes a global optimal solution and a divided and inverse solution corresponding to the global optimal solution.
  • the pixels to be processed may be all pixels in the magnetic resonance image, or may be pixels selected from all the pixels in the magnetic resonance image that satisfy the preset condition.
  • the pixels satisfying the preset conditions may be those pixels that cannot determine whether it is a water component or a fat component based directly on the pixel based on the preset determination method.
  • the brightness value of each pixel in the magnetic resonance image may be acquired, and the pixel to be processed of the magnetic resonance image may be determined according to the brightness value.
  • determining the pixels to be processed of the magnetic resonance image according to the brightness value may be determining the target removed pixels of the magnetic resonance image according to the brightness value, and removing all of the magnetic resonance image Among the pixel points, the remaining pixel points except for the target removal pixel point are used as pixels to be processed. Since the process of water and fat separation often requires processing of each pixel, the advantage of the above technical solution is that it can reduce the amount of calculations and improve the efficiency of water and fat separation while ensuring the accuracy of water and fat separation.
  • the phase factor candidate solution can be understood as a set of phase factor solutions, including possible phase factor solutions for each pixel to be processed. It can be understood that the candidate phase factor solution includes the true phase factor solution of each pixel to be processed, that is, the target phase factor solution, and the field displacement ⁇ of the magnetic resonance image can be accurately determined according to the target phase factor solution.
  • phase factor candidate solutions when multiple phase factor solutions in the phase factor candidate solutions are divided into the first solution set and the second solution set, respectively, the multiple phase factor solutions of the same pixel to be processed need to be divided into different solutions concentrated. That is, if the global optimal solution of the current pixel to be processed is divided into the first solution set, then the inverse solution of the current pixel to be processed will be divided into the second solution set.
  • the phase factor candidate solutions include the global optimal solution PG and the inverse solution corresponding to PG
  • P G may be a set of phase factor solutions p B of each pixel to be processed obtained according to formula (6); It is a set corresponding to PG , and can be considered as a mirror solution set of PG .
  • the calculation process can be:
  • W G is the water signal component corresponding to the global optimal solution P G
  • F G is the fat signal component corresponding to the global optimal solution P G.
  • each pixel to be processed in the magnetic resonance image is at P G and There are PG and P B corresponding to each.
  • the p B of the pixel to be processed may be p B belonging to water in P G , then It may be a part of the fat p B; of course, be processed in the pixel point P G p B may be a part of the fat p B, then It is also possible that p B belonging to water is possible.
  • the purpose of having two p B for the same pixel to be processed is to make full use of the ambiguity of water and fat to more accurately determine whether the pixel belongs to a water component or a fat component.
  • phase factor solutions in the phase factor candidate solutions can be divided into the first solution set and the second solution set based on a preset division method, that is, the set
  • the multiple p B in and P G are divided into the first solution set and the second solution set, respectively.
  • the preset division method may be the result of water and fat separation.
  • the pixels in the water-fat conversion area may be pixels on the edges of the water area and the fat area.
  • the edge pixel points of the water area and the fat area can be determined, and further, the water-fat conversion area can be determined.
  • each to-be-processed pixel in the magnetic resonance image may be traversed, and the pixel that meets the preset edge pixel filtering conditions may be used as the edge pixel.
  • each pixel to be processed in the water-fat conversion area has a possible phase factor solution in the first solution set and the second solution set respectively, and the phase factor corresponding to the pixel to be processed in the first solution set
  • the solution serves as the first candidate phase factor solution
  • the phase factor solution corresponding to the pixel to be processed in the second solution set is used as the second candidate phase factor solution.
  • the target phase factor solution of each pixel to be processed in the water-fat conversion area is calculated, and the pixel to be processed may be selected from the first candidate phase factor solution and the second candidate phase factor solution The target phase factor solution for the point.
  • the water-fat conversion area can be used as a known area, and multiple sub-areas can be used as an unknown area, so as to determine each to-be-processed in the unknown area according to the target phase factor solution of each to-be-processed pixel in the known area Pixel target phase factor solution.
  • the target phase factor solution of each pixel to be processed in the known area can be used as a priori condition to gradually determine the target phase factor solution of each pixel to be processed in the unknown area.
  • the inner field diagram of the unknown area can be determined based on the neighborhood pixel voting. The above steps are beneficial to improve the noise resistance and efficiency of water-fat separation.
  • the pixels to be processed except the water-fat conversion area may be spatially divided into at least two consecutive sub-areas, and then each The target phase factor solution of each pixel to be processed is the target phase factor solution of each pixel to be processed in each subregion.
  • a plurality of sub-regions may be sequentially processed based on a preset sub-region selection method, and the processed sub-regions are merged with known regions to update the known regions. Iteratively loops until multiple unknown regions are processed as known regions, and the target phase factor solutions of all pixels to be processed are obtained.
  • the field displacement of the magnetic resonance image is determined.
  • the intensity of the water and fat signal of each pixel to be processed can be calculated by the following formula:
  • ⁇ w is the intensity of the water signal
  • ⁇ f is the intensity of the fat signal
  • a + (p B ) is the generalized inverse of the matrix A(p B )
  • S is the multi-echo magnetic resonance signal, if the current pixel to be processed ⁇ w > ⁇ f , the current pixel to be processed is a water signal; if the ⁇ w of the current pixel to be processed is less than or equal to ⁇ f , the current pixel to be processed is a fat signal.
  • the technical solution of this embodiment first simplifies the calculation amount by dividing the calculated phase factor candidate solutions of each pixel to be processed in the magnetic resonance image into the first solution set and the second solution set respectively; then, based on The phase factor solution corresponding to each pixel to be processed in the first solution set and the second solution set determines the water-fat conversion area in the magnetic resonance image, and calculates the target phase factor for each pixel to be processed in the water-fat conversion area Solution; further, using the water-fat conversion area as a known area, the target phase factor solution of each pixel to be processed among the remaining pixels to be processed is determined according to the target phase factor solution of each pixel to be processed in the known area; Finally, according to the target phase factor of each pixel to be processed in the magnetic resonance image, the water and fat images in the magnetic resonance image are extracted.
  • the above technical scheme can quickly and stably estimate the field map, and on this basis, complete the correct estimation of the water and fat components.
  • the water-fat separation method based on the magnetic resonance image may further include: acquiring the highest amplitude corresponding to each pixel to be processed in the multi-echo data; according to the highest amplitude and at least one The preset grading threshold divides a plurality of pixels in the magnetic resonance image into at least two grading areas; the at least two grading levels are processed in order from the area with high signal-to-noise ratio to the area with low signal-to-noise ratio.
  • the water-fat signal in order to avoid the low signal-to-noise ratio region from affecting the high signal-to-noise ratio region, the water-fat signal can be separated according to the amplitude classification method.
  • the highest amplitude corresponding to each pixel to be processed in the multi-echo data is obtained, and the highest amplitude corresponding to each pixel to be processed is compared with at least one pre-set threshold value to make the magnetic
  • the multiple pixels to be processed in the resonance image are divided into at least two classification regions.
  • H1, H2, H3,...Hn+1 represents the highest amplitude of multiple pixels, where H1 is the maximum value of the highest amplitude of multiple pixels to be processed, and Hn+1 is the multiple pixels to be processed The minimum value of the highest amplitude of the point.
  • the pixel to be processed may be classified into the level Hn.
  • the image with higher amplitude has higher signal-to-noise and the image with lower amplitude has lower signal-to-noise. Therefore, the higher amplitude level has higher processing than the lower amplitude level.
  • Priority multiple graded regions in multiple steps involved in the water-fat separation method based on magnetic resonance images can be processed in order from the region with a high signal-to-noise ratio to the region with a low signal-to-noise ratio.
  • the above-mentioned amplitude grading method may be used to sequentially process from a region with a high SNR to a region with a low SNR, each amplitude level
  • the field displacement is solved in turn, and the processing result of the higher amplitude level is used as the reference value of the lower amplitude level, which effectively avoids the impact of the low SNR area on the high SNR area.
  • the “dividing multiple phase factor solutions among the phase factor candidate solutions into the first solution set and the second solution set, respectively” may include: according to the calculated water-lipid separation result, the global optimal solution And the multiple phase factor solutions in the inverse solution are divided into the first solution set and the second solution set, respectively.
  • explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.
  • the method of this embodiment may include the following steps.
  • phase factor candidate solution includes a global optimal solution and a sub-inverse solution corresponding to the global optimal solution .
  • S220 Divide the global optimal solution and the multiple phase factor solutions in the split-inverse solution into the first solution set and the second solution set according to the calculated water-lipid separation results, respectively.
  • phase factor solutions in the global optimal solution and the sub-inverse solution are traversed, and the intensity of the water and fat signal of each phase factor solution is calculated by formula (7).
  • multiple phase factor solutions may be divided into a first solution set and a second solution set according to the magnitude relationship between the strength of the water signal and the strength of the fat signal, respectively.
  • the first solution set P w may be a set of global optimal solutions of a plurality of pixels to be processed and a set of phase factor solutions in which the strength of the water signal in the split-inverse solution is greater than the strength of the fat signal, which is considered to be a water signal ;
  • the second solution set P f may be a set of global optimal solutions for multiple pixels to be processed and a set of phase factor solutions in which the intensity of the fat signal is greater than the intensity of the water signal in the split-inverse solution. Possible result of lipid separation. The division of the first solution set and the second solution set helps to simplify the calculation of subsequent steps and realize the rapid determination of the field displacement.
  • the first solution set P w may be a global optimal solution and a set of phase factor solutions in which the intensity of the fat signal is greater than the intensity of the water signal in the inverse solution, which is considered to be a fat signal;
  • the second solution set P f It may be a set of global optimal solutions and phase factor solutions in which the strength of the water signal in the split-inverse solution is greater than the strength of the fat signal. It is considered to belong to the water signal, and a possible result of water-fat separation has been obtained initially.
  • S240 Determine the target phase factor solution of each pixel to be processed among the remaining pixels to be processed based on the water-fat conversion area and the target phase factor solution of each pixel to be processed in the water-fat conversion area.
  • the global optimal solution and all phase factor solutions in the sub-inverse solution are divided into the first solution set and the second solution set respectively according to the calculated water-fat separation result, which realizes the preliminary water-fat signal It separates and simplifies the calculation of the solution process of the target phase factor.
  • determining the water-fat conversion area based on the phase factor solution corresponding to each pixel to be processed in the first solution set and the second solution set may include: Processing the phase factor solution corresponding to the pixel, calculating the maximum vector change of each pixel to be processed and the multiple neighboring pixels of each pixel to be processed in the first solution set and the second solution set, according to the first The maximum vector change corresponding to the solution set and the second solution set determines the water-fat conversion region.
  • the neighboring pixel may be a pixel adjacent to the current pixel in multiple directions. It can be understood that the number of neighboring pixels of each pixel to be processed can be set according to actual needs, and is not specifically limited here.
  • the neighboring pixels matching the current pixel r to be processed may be the pixels q included in the region 10, or may be the pixels q included in the outer extension region 20 of the region 10, and of course It may be the pixel point q contained in the outer extension of the area 20, and so on.
  • eight pixel points q in the area 10 may be selected as neighboring pixel points of the current pixel point to be processed r.
  • a plurality of neighborhood pixels for each pixel to be processed and each pixel to be processed are calculated
  • the vector change of the point in the first solution set and the second solution set may be based on the phase factor solution of each pixel to be processed in the first solution set to calculate the multiple neighborhoods of the current pixel to be processed and the current pixel to be processed
  • the maximum vector change of the pixel point is to obtain the maximum vector change corresponding to the current pixel to be processed.
  • the phase factor solution of each pixel to be processed in the second solution set calculate the maximum vector change of the current pixel to be processed and the neighboring pixels of the pixel to be processed to obtain the current pixel to be processed corresponding Maximum vector change.
  • whether the pixel to be processed belongs to the water-fat conversion region can be determined according to the maximum vector change corresponding to the first solution set and the second solution set.
  • a plurality of neighborhood pixels for each pixel to be processed and each pixel to be processed are calculated
  • the maximum vector change of the point in the first solution set may include: for each pixel to be processed, calculating each pixel to be processed and multiple neighboring pixels of each pixel to be processed based on the following formula in the first
  • the maximum vector change in the solution set :
  • D w (r) represents the maximum vector change of the pixel to be processed r and the neighboring pixels of the pixel to be processed r in the first solution set; i represents the pixel in the neighborhood; abs(.) represents Find the absolute value; angle(.) means to find the phase angle; conj(.) means to find the complex conjugate; P w (r i ) means the neighboring pixel i of the pixel r to be processed in the first solution set Phase factor solution.
  • the maximum vector change in the second solution set of each pixel to be processed and a plurality of neighboring pixels can also be calculated based on the following formula:
  • D f (r) represents the maximum vector change in the second solution set graph of the pixel r to be processed and the neighboring pixels r to be processed
  • P f (r i ) represents the pixel r to be processed The phase factor solution of the neighboring pixel point i in the second solution set.
  • the maximum vector change in the first solution set and the maximum vector change in the second solution set can be obtained for each pixel to be processed and multiple neighboring pixel points according to the above formula.
  • determining the water-fat conversion region according to the maximum vector change corresponding to the first solution set and the second solution set may include: if the maximum vector change of the current pixel to be processed in the first solution set and the second solution set When at least one of the maximum vector changes in the concentration is greater than the preset conversion threshold, the current pixel to be processed belongs to the water-fat conversion area, where the preset conversion threshold can be determined according to the phase shift between the water-fat signals within the sampling interval .
  • the current pixel to be processed belongs to the water-fat conversion region. Then, traversing each pixel to be processed in the magnetic resonance image can determine which pixels to be processed belong to the water-fat conversion region.
  • calculating the target phase factor solution for each pixel to be processed in the water-fat conversion region may include: determining the maximum vector change among multiple neighboring pixels in each pixel to be processed in the water-fat conversion region The largest target neighborhood pixel; when the phase shift between the water and fat signals during the sampling interval is not equal to an integer multiple of 180 degrees, according to each pixel to be processed in the water and fat conversion area and the The combination of the phase factor solutions of the target neighboring pixels corresponding to the processing pixels determines the target phase factor solutions of each pixel to be processed.
  • the phase factor solution of the pixel to be processed in the water-fat conversion area in the first solution set or the phase factor solution in the second solution set can be solved as the target phase factor solution.
  • the phase factor solution of two pixels can have four possible combinations of solutions, for example, [P w (r), P w (q)], [P w (r), P f (q)] , [P f (r), P w (q)], [P f (r), P f (q)].
  • [P w (r), P w (q)] means to use the phase factor solution of the current pixel to be processed in the first solution set P w and the phase factor solution of the target neighboring pixel;
  • [P w (r) , P f (q)] means using the phase factor solution of the current pixel to be processed in the first solution set P w and the phase factor solution of the target neighborhood pixel in the second solution set P f ; and so on.
  • phase offset between the water signal and the fat signal is not equal to an integer multiple of 180 degrees, that is, ⁇ k ⁇
  • the magnetic resonance image of the solution combination with the smallest difference is the smoothest, and the phase factor solution of the current pixel to be processed corresponding to the solution combination with the smallest phase difference is taken as the target phase factor solution of the current pixel to be processed.
  • phase factor solution of the current pixel to be processed in the first solution set is used as the target phase factor of the current pixel to be processed Solution, that is, the phase factor solution P w (r) of the current pixel to be processed in the first solution set P w is selected as the target phase factor solution of the current pixel to be processed r to select the optimal corresponding to the current pixel to be processed Phase factor solution.
  • the target phase factor solution of each pixel to be processed among the remaining pixels to be processed is determined, It may include: dividing the remaining pixels to be processed except the water-fat conversion region into a first number of spatially consecutive sub-regions to be solved according to the first solution set and the second solution set, wherein each sub-solution All the pixels to be processed in the region come from the same solution set; the target phase of each pixel to be processed in each sub-region to be solved is determined according to the target phase factor solution of each pixel to be processed in the water-fat conversion region Factor solution.
  • the explanation of the same or corresponding terms as those in the above embodiments will not be repeated here.
  • the method of this embodiment may include the following steps.
  • phase factor candidate solution includes a global optimal solution and a partial inverse solution corresponding to the global optimal solution.
  • the first number of values may be determined according to actual needs.
  • the spatially continuous sub-regions to be solved may be sub-regions to be solved that have edges connected or adjacent edge pixels in the first number of spaces.
  • the remaining pixels to be processed can be divided into the first number of spatially consecutive sub-regions to be solved, and the target phase factor solutions of all the pixels to be processed in each sub-region to be solved come from In the same solution set, that is, the target phase factor solution of all pixels to be processed in each sub-region to be solved comes from the first solution set, or the target of all pixels to be processed in each sub-region to be solved
  • the phase factor solutions all come from the second solution set. In other words, all the pixels to be processed in each sub-region to be solved have only two possible choices, and all the pixels to be processed can only select the phase factor in the same solution set. solution.
  • one of the first solution set and the second solution set can be selected by the neighborhood pixel voting method as the pixel to be processed of the sub-region Target phase factor solution.
  • the magnetic resonance image includes at least two sub-regions to be solved. In an embodiment, it may be determined which sub-region to be solved according to the gradation level of a plurality of pixels to be processed in the plurality of sub-regions to be solved Multiple pixels to be processed are given priority.
  • S350 Determine the target phase factor solution of each pixel to be processed among the remaining pixels to be processed based on the water-fat conversion region and the target phase factor solution of each pixel to be processed in the water-fat conversion region.
  • the remaining pixels to be processed except the water-fat conversion region are divided into a first number of spatially continuous sub-regions to be solved according to the first solution set and the second solution set.
  • Solve the sub-region to achieve a quick and convenient solution to determine the target phase factor solution of a part of the pixels to be processed each time; determine each sub-region to be solved according to the target phase factor solution of each pixel to be processed in the water-lipid conversion region
  • the target phase factor solution of each pixel to be processed in the image using the target phase factor solution of the known region as a priori condition of the unknown region, can accurately calculate the target behavior factor solution of the pixel to be processed of the unknown region, that is, the sub-region to be solved .
  • determining the target phase factor solution for each pixel to be processed in each sub-region to be solved according to the target phase factor solution for each pixel to be processed in the water-fat conversion region may include: obtaining all current A plurality of edge pixel pairs that are spatially adjacent to the known region and the current sub-region to be solved, where the current known region includes a water-lipid conversion region; based on the plurality of edge pixel pairs, the corresponding to the first solution set and the second solution set are calculated respectively The first cost function and the second cost function of; determine the target phase factor solution of each pixel to be processed in each sub-region to be solved according to the first cost function and the second cost function.
  • adjacent edge pixel pairs can be regarded as a pixel pair composed of pixels of the known region and the subregion to be solved spatially next to each other.
  • the current known region 30 Including the pixels to be processed 301 and 302, and the current sub-region 40 to be solved includes pixels to be processed 401 and 402, then the pixels to be processed 301 and the pixels to be processed 401 can form adjacent edge pixel pairs; the pixels to be processed 302 and Pixels to be processed 402 may form adjacent edge pixel pairs
  • the first cost function corresponding to the first solution set and the second cost function corresponding to the second solution set can be calculated according to multiple edge pixel pairs of all currently known regions and the current sub-region to be solved . According to the above cost function, it can be determined whether the target phase factor solutions of the multiple pixels to be processed in the multiple sub-regions to be solved are the phase factor solutions in the first solution set or the phase factor solutions in the second solution set.
  • one of the remaining sub-areas to be solved can be selected as the current sub-area to be solved based on preset filter conditions; then the current sub-area to be solved is The known areas are merged to become a known area; the operation of selecting one of the remaining sub-areas to be solved as the current sub-area to be solved based on preset filter conditions is repeatedly performed until all the sub-areas to be solved are updated to the known area.
  • the preset filtering condition may be the priorities of multiple sub-regions to be determined according to the highest amplitudes of multiple pixel points in multiple sub-regions to be solved; or the sub-regions to be solved and the known The area constitutes the number of adjacent edge pixel pairs and so on.
  • calculating the first cost function and the second cost function corresponding to the first solution set and the second solution set based on the plurality of edge pixel pairs respectively includes: calculating the first cost function and the second cost function based on each edge pixel pair and the following formula The first cost function C w and the second cost function C f corresponding to the first solution set and the second solution set:
  • the current sub-region to be solved is determined by all neighboring pixel pairs (s j , k j ) in space All the pixels to be processed in the first cost function corresponding to the phase factor solution of the first solution set and the second cost function corresponding to the phase factor solution of the second solution set.
  • determining the target phase factor solution for each pixel to be processed in each sub-region to be solved according to the first cost function and the second cost function may include: collecting the first solution set or the second solution set, The phase factor solution in the solution set corresponding to the smaller cost function in the first cost function and the second cost function is used as the target phase factor solution for each pixel to be processed in the current sub-region to be solved.
  • the smaller the cost function the smaller the loss and the more convergent the magnetic resonance image. Therefore, the smaller cost function of the first cost function and the second cost function serves as a reference for solving the target phase factor solution.
  • the current subregion to be solved All pixels to be processed in the process select the phase factor solution in the first solution set P w as the target phase factor solution; if C f ⁇ C w , the phase factor solution in the second solution set P f is selected as the target phase factor solution.
  • the water-fat separation method based on the magnetic resonance image may further include: if the current sub-region to be solved is not adjacent to any currently known region, and there are multiple layers of magnetic data in the current data set For the resonance image, a plurality of edge pixel pairs that are spatially adjacent to all the currently known regions and the current sub-regions in the adjacent magnetic resonance image layer are obtained along the direction in which the image layers are arranged.
  • the current result can be determined according to the calculation result of formula (7) Whether the pixels to be processed in the sub-region to be solved belong to the water component or the fat component; if there are multiple magnetic resonance images in the current data set, all the current magnetic resonance image layers can be obtained along the direction of the image layer arrangement Knowing the region and all edge pixel pairs spatially adjacent to the current sub-region to be solved, and then using the above method of solving the first cost function and the second cost function to determine whether the pixels to be processed in the current sub-region to be solved belong to water The ingredients are still fat.
  • the advantage of the above step setting is that it can combine the phase factor solutions of multiple pixels of the adjacent layer magnetic resonance image to effectively deal with the solution of the target phase factor solution when the pixels are discontinuous in the plane space.
  • the method may further include: if the signal-to-noise ratio of the magnetic resonance image is lower than a preset threshold, resolving the target phase factor of a plurality of pixels to be processed in a known area by local growth Determine the target phase factor solution for each pixel to be processed in the water-fat conversion area.
  • the method of this embodiment may include the following steps.
  • phase factor candidate solution includes a global optimal solution and a divided and inverse solution corresponding to the global optimal solution.
  • the target phase factor solution of each pixel to be processed obtained according to the above steps may determine the field displacement.
  • the signal-to-noise ratio of the magnetic resonance image is lower than the preset threshold, there may be errors in the field displacement of the pixels to be processed in the water-fat conversion region under the low signal-to-noise ratio.
  • the above-mentioned to-be-solved sub-region can be used as a known region, and multiple pixels to be processed in the known region can be locally grown
  • the target phase factor solution of the point re-determines the target phase factor solution of each pixel to be processed in the water-fat conversion region.
  • redetermining the target phase factor solution of each pixel to be processed in the water-fat conversion region by locally increasing the target phase factor solution of multiple pixels to be processed in the known area may include: Calculate the difference between the selected phase factor solution in the first solution set and the second solution set of the current pixel to be processed in the water-fat conversion area and the target phase factor solution of multiple neighboring pixels; it will be different from the calculated two
  • the phase factor solution to be selected corresponding to the smaller difference in the difference is used as the target phase factor solution of the current pixel to be processed.
  • the water-fat conversion area includes at least two pixels to be processed, so one of the pixels to be processed may be selected as the current pixel to be processed based on a preset condition.
  • the selection can be based on the number of pixels in the neighborhood of a plurality of pixels to be processed in the water-fat conversion area, and the pixels to be processed in the neighborhood that have the most pixels in the known area Point, as the current pixel to be processed.
  • the target phase factor of these neighboring pixels belonging to the known area may be used
  • the solution calculates the difference between the current pixel to be processed in the first solution set and the second solution set.
  • the difference between the phase factor solution to be selected in the first solution set and the second solution set of the current pixel to be processed in the water-fat conversion region and the target phase factor solution of multiple neighboring pixel points can be calculated separately. It includes: calculating the difference D X between the X-th solution to be selected and the target phase factors of multiple neighboring pixels in the water-fat conversion area based on the following formula:
  • K is the neighboring pixels of all known target phase factors
  • X is the number of solutions to be selected
  • m k is the maximum amplitude of the kth neighboring pixel in all echo signals
  • p B, k represents The target phase factor solution of the k-th neighbor pixel
  • angle(.) means to obtain the phase angle
  • conj(.) means to obtain the complex conjugate.
  • D X can be regarded as D w or D f .
  • D 1 ⁇ D 2 the phase factor solution of the current pixel to be processed in the water-fat conversion area in the first solution set is taken as the target phase factor solution; when D 1 ⁇ D 2 , the water-fat conversion area is used The phase factor solution of the current pixel to be processed in the second solution set is used as the target phase factor solution.
  • the local phase increase method is used to re-determine the water-fat conversion area according to the target phase factor solution of multiple pixels to be processed in the known area
  • the solution of the target phase factor of each pixel to be processed can effectively avoid the problem that the field displacement of the pixel to be processed in the water-fat conversion region solved under a low signal-to-noise ratio may have errors.
  • the acquisition system was a Siemens 3T magnetic resonance system
  • the sequence was a multi-echo GRE sequence
  • the acquired image is processed based on the above water-fat separation method, and the result of water-fat separation is shown in FIG. 4A.
  • the signal-to-noise ratio SNR of the liver region in the figure is 22.16, 4.89 and 2.6, respectively.
  • the four columns of images are the first echo amplitude map, phase factor map, fat map and water map separation results under multiple signal-to-noise ratios. . It can be seen from the above that the above water-fat separation method can still achieve stable and accurate separation of water-fat signals under the condition of low signal-to-noise ratio.
  • each amplitude grading can be divided into two categories: belong to the water-fat conversion region and not belong to the water-fat conversion region.
  • all the pixels to be processed in the water-fat conversion area are first extracted, all the different phase factor solutions are considered and the smoothest phase factor solution is selected as the target phase factor of the pixels to be processed in the water-fat conversion area Solution:
  • After processing each amplitude-graded pixel iterate to the next amplitude-grading process.
  • the target phase factor solution of the region with high amplitude classification is used as a priori condition for the region with low amplitude classification. Processing unknown areas with the results of known areas can effectively avoid images with low signal-to-noise ratio.
  • the above-mentioned separation method based on magnetic resonance images can be applied not only to water-fat separation imaging, but also to other chemical shift-coded imaging, as long as the corresponding parameters in the model need to be adaptively modified.
  • FIG. 5 is a structural block diagram of a water-fat separation device based on a magnetic resonance image provided by an embodiment, and the device is used to perform the water-fat separation method based on a magnetic resonance image provided by any of the above embodiments.
  • This device and the magnetic resonance image-based water and fat separation method of the above embodiment belong to the same concept.
  • the apparatus may include: a de-aggregation module 510, a water-fat conversion region determination module 520, a target phase factor solution determination module 530, and a water-fat image separation module 540.
  • the solution set division module 510 is configured to acquire each pixel to be processed in the magnetic resonance image, calculate the candidate phase factor solution for each pixel to be processed, and divide multiple phases in the candidate phase factor solution
  • the factor solutions are divided into the first solution set and the second solution set, respectively, where the phase factor candidate solutions include the global optimal solution and the sub-inverse solution corresponding to the global optimal solution;
  • the water-fat conversion area determination module 520 is set to The phase factor solution corresponding to each pixel to be processed in the first solution set and the second solution set determines the water-fat conversion area, and calculates the target phase factor solution for each pixel to be processed in the water-fat conversion area;
  • the target phase factor solution is determined Module 530, set to determine the target phase factor solution of each pixel to be processed among the remaining pixels to be processed based on the water-fat conversion area and the target phase factor solution of each pixel to be processed in the water-fat conversion area;
  • the separation module 540 is configured to de-extract the water map and fat map in
  • the phase factor candidate solution of each pixel to be processed in the magnetic resonance image calculated separately, and the phase factor candidate solution
  • the multiple phase factor solutions in are divided into the first solution set and the second solution set respectively to simplify the calculation; then, based on the phase factor solutions corresponding to each pixel to be processed in the first solution set and the second solution set, determine The water-fat conversion area in the magnetic resonance image is obtained, and the target phase factor solution of each pixel to be processed in the water-fat conversion area is calculated; further, the water-fat conversion area is used as a known area, and the known area and water-fat are used as the known area
  • the target phase factor solution of each pixel to be processed in the conversion area determines the target phase factor solution of each pixel to be processed among the remaining pixels to be processed, and the target phase factor solution of the unknown area is solved according to the known area; finally, according to The target phase factor of each pixel to be processed in the magnetic resonance image extracts the water map and fat
  • the disaggregation module 510 may include:
  • the solution set division submodule is configured to divide the global optimal solution and the multiple phase factor solutions in the split-inverse solution into the first solution set and the second solution set according to the calculated water-lipid separation results, respectively.
  • the water-fat conversion area determination module 520 may include:
  • the sub-module of the water-fat conversion area determination module is set to calculate each to-be-processed pixel point and multiple neighboring pixel points in the first based on the phase factor solution corresponding to each to-be-processed pixel point in the first and second solution sets
  • the maximum vector change in the solution set and the second solution set determines the water-fat conversion region according to the maximum vector change corresponding to the first solution set and the second solution set.
  • the water-fat conversion area determination module sub-module may include:
  • the maximum vector change calculation unit is set to calculate, for each pixel to be processed, the maximum vector change in the first solution set for each pixel to be processed and multiple neighboring pixels based on the following formula:
  • D w (r) represents the maximum vector change of the pixel to be processed r and the neighboring pixels of the pixel to be processed r in the first solution set; i represents the pixel in the neighborhood; abs(.) represents Find the absolute value; angle(.) means to find the phase angle; conj(.) means to find the complex conjugate; P w (r i ) means the neighboring pixel i of the pixel r to be processed in the first solution set Phase factor solution.
  • the water-fat conversion area determination module sub-module may include:
  • the water-fat conversion area determining unit is set to set the current pixel to be processed if at least one of the maximum vector change of the current pixel to be processed in the first solution set and the maximum vector change in the second solution set is greater than a preset conversion threshold
  • the point belongs to the water-fat conversion area, where the preset conversion threshold is determined according to the phase shift between the water-fat signals within the sampling interval.
  • the water-fat conversion area determination module 520 may further include: a target neighborhood pixel point determination sub-module and a target phase factor solution determination sub-module.
  • the target neighborhood pixel determination submodule is set to determine the target neighborhood pixel with the largest vector change among the multiple neighborhood pixels of each pixel to be processed in the water-fat conversion area; the target phase factor solution determiner Module, when the phase shift between the water and fat signals within the sampling interval is not equal to an integer multiple of 180 degrees, according to each pixel to be processed in the water and fat conversion area and the target corresponding to each pixel to be processed The combination of phase factor solutions of the neighboring pixels determines the target phase factor solution of each pixel to be processed.
  • the target phase factor solution determination module 530 may include: a sub-region determination sub-module to be solved and a target phase factor solution determination sub-module in the sub-region to be solved.
  • the sub-region determination sub-module to be solved is set to divide the remaining pixels to be processed except the water-fat conversion region into the first number of spatially consecutive sub-solves to be solved according to the first solution set and the second solution set Area, where all the pixels to be processed in each sub-area to be solved come from the same solution set; the target phase factor solution determination sub-module in the sub-area to be solved is set according to each The target phase factor solution of the processing pixel determines the target phase factor solution of each pixel to be processed in each sub-region to be solved.
  • the target phase factor solution determination sub-module in the sub-region to be solved may include: an edge pixel pair acquisition unit, a cost function calculation unit, and a target phase factor solution determination unit in the sub-region to be solved.
  • the edge pixel pair acquisition unit is set to acquire multiple edge pixel pairs spatially adjacent to all the current known regions and the current sub-region to be solved, wherein the current known region includes a water-fat conversion region; a cost function calculation unit, Set to calculate the first cost function and the second cost function corresponding to the first solution set and the second solution set based on multiple edge pixel pairs, respectively; the target phase factor solution determination unit in the sub-region to be solved is set to The cost function and the second cost function determine the target phase factor solution of each pixel to be processed in each sub-region to be solved.
  • the cost function calculation unit is set to:
  • the first cost function C w and the second cost function C f corresponding to the first solution set and the second solution set are calculated based on multiple edge pixel pairs and the following formulas, respectively:
  • the target phase factor solution determination unit in the sub-region to be solved is set to:
  • the target phase factor solution determination subunit in the sub-region to be solved is set to set the phase factor in the solution set corresponding to the first cost function and the second cost function in the first solution set or the second solution set corresponding to the smaller cost function in the first cost function and the second cost function
  • the solution serves as the target phase factor solution for each pixel to be processed in the current sub-region to be solved.
  • the target phase factor solution determination sub-module in the sub-region to be solved may also be set as:
  • the current sub-region to be solved is not adjacent to any currently known region, and there are multiple layers of magnetic resonance images in the current data set, all the currently known regions in the adjacent magnetic resonance image layer are obtained along the direction of the image layer arrangement And the spatially adjacent edge pixel pairs of the subregion to be solved.
  • the device may further include:
  • the low signal-to-noise ratio processing module is set to re-determine the water-fat conversion according to the target phase factor solution of multiple pixels to be processed in the known area by local growth if the signal-to-noise ratio of the magnetic resonance image is lower than a preset threshold The target phase factor solution for each pixel to be processed in the area.
  • the low signal-to-noise ratio processing module may include:
  • the difference calculation submodule is configured to calculate the difference between the phase factor solution to be selected in the first solution set and the second solution set of the current pixel to be processed in the water-fat conversion area and the target phase factor solution of multiple neighboring pixels;
  • the low signal-to-noise ratio processing sub-module is configured to use the selected phase factor solution corresponding to the smaller difference between the two calculated differences as the target phase factor solution of the current pixel to be processed.
  • the difference calculation submodule is set as:
  • K is the neighboring pixels of all known target phase factors
  • X is the number of solutions to be selected
  • m k is the maximum amplitude of the kth neighboring pixel in all echo signals
  • p B, k represents The target phase factor solution of the k-th neighbor pixel
  • angle(.) means to obtain the phase angle
  • conj(.) means to obtain the complex conjugate.
  • the device may further include:
  • the highest amplitude acquisition module is set to acquire the highest amplitude corresponding to each pixel to be processed in the multi-echo data
  • a hierarchical area dividing module configured to divide a plurality of pixels in the magnetic resonance image into at least two hierarchical areas according to the highest amplitude and at least one preset hierarchical threshold;
  • the sequential processing module is configured to process at least two grading levels in order from the area with a high signal-to-noise ratio to the area with a low signal-to-noise ratio.
  • the device for separating water and fat based on magnetic resonance images provided in this embodiment can execute the method for separating water and fat based on magnetic resonance images provided in any embodiment of the present invention, and has a function module and beneficial effects corresponding to the execution method.
  • At least one unit and at least one module included are only divided according to functional logic, but it is not limited to the above division, as long as the corresponding function can be achieved ;
  • the name of each functional unit is only to facilitate the distinction between each other, and is not used to limit the scope of protection of the present disclosure.
  • FIG. 6 is a schematic structural diagram of a device provided by an embodiment.
  • the device includes a memory 610, a processor 620, an input device 630, and an output device 640.
  • the number of processors 620 in the device may be one or more, and one processor 620 is taken as an example in FIG. 6; the memory 610, processor 620, input device 630, and output device 640 in the device may be connected through a bus or other means In FIG. 6, the connection through the bus 650 is taken as an example.
  • the memory 610 can be configured to store software programs, computer executable programs, and modules, such as program instructions/modules corresponding to the water-fat separation method based on magnetic resonance images in the above embodiments (for example, based on The de-aggregation and division module 510, the water-fat conversion area determination module 520, the target phase factor solution determination module 530, and the water-fat image separation module 540 in the water-fat separation device of the magnetic resonance image.
  • the processor 620 executes at least one functional application of the device and data processing by running software programs, instructions, and modules stored in the memory 610, that is, implementing the above-mentioned magnetic resonance image-based water-fat separation method.
  • the memory 610 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system and application programs required for at least one function; the storage data area may store data created according to the use of the device, and the like.
  • the memory 610 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.
  • the memory 610 may include memories remotely provided with respect to the processor 620, and these remote memories may be connected to the device through a network. Examples of the aforementioned network include, but are not limited to, the Internet, intranet, local area network, mobile communication network, and combinations thereof.
  • the input device 630 may be configured to receive input numeric or character information, and generate key signal input related to user settings and function control of the device.
  • the output device 640 may include a display device such as a display screen.
  • This embodiment provides a storage medium containing computer-executable instructions.
  • the computer-executable instructions are executed by a computer processor, the computer-executable instructions are used to execute a method for separating water and fat based on a magnetic resonance image.
  • the method includes:
  • each pixel to be processed in the magnetic resonance image calculate the phase factor candidate solution for each pixel to be processed, and divide the multiple phase factor solutions in the phase factor candidate solution into the first solution set and the second solution respectively Concentration, where the candidate solution of the phase factor includes the global optimal solution and the inverse solution corresponding to the global optimal solution;
  • the water-fat conversion area is determined, and the target phase factor solution for each pixel to be processed in the water-fat conversion area is calculated;
  • the water map and fat map in the magnetic resonance image are extracted.
  • This embodiment provides a storage medium containing computer-executable instructions.
  • the computer-executable instructions are not limited to the method operations described above, and may also be used in the water-fat separation method based on magnetic resonance images provided in any of the above embodiments. Related operations.
  • the present disclosure can be implemented by software and general hardware, or by hardware.
  • the technical solution of the present disclosure can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (Read-Only Memory, ROM), Random access memory (RAM), flash memory (FLASH), hard disk or optical disc, etc., including multiple instructions to enable a computer device (which may be a personal computer, server, or network device, etc.) to perform any of the above implementations Example method.
  • a computer-readable storage medium such as a computer floppy disk, read-only memory (Read-Only Memory, ROM), Random access memory (RAM), flash memory (FLASH), hard disk or optical disc, etc.
  • a computer device which may be a personal computer, server, or network device, etc.

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Abstract

L'invention concerne un procédé, un dispositif et un appareil pour une séparation eau-graisse utilisant une image de résonance magnétique, et un support d'enregistrement. Le procédé de séparation eau-graisse comprend les étapes consistant à : acquérir une pluralité de pixels à traiter (r, 301, 302, 401, 402) dans une image de résonance magnétique, calculer des solutions candidates de facteur de phase de celles-ci, et diviser une pluralité de solutions de facteur de phase dans les solutions candidates de facteur de phase en un premier ensemble de solutions et un second ensemble de solutions respectivement (s110) ; déterminer une région de conversion eau-graisse sur la base des solutions de facteur de phase dans le premier ensemble de solutions et le second ensemble de solutions, et calculer une solution de facteur de phase cible pour chaque pixel à traiter (r, 301, 302, 401, 402) dans la région de conversion eau-graisse (s120) ; déterminer, sur la base de la région de conversion eau-graisse et des solutions de facteur de phase cible dans la région de conversion eau-graisse, une solution de facteur de phase cible pour chaque pixel à traiter (r, 301, 302, 401, 402) dans les pixels restants à traiter (r, 301, 302, 401, 402) (s130) ; et extraire une carte d'eau et une carte de graisse dans l'image de résonance magnétique en fonction de la solution de facteur de phase cible pour chaque pixel à traiter (r, 301, 302, 401, 402) dans l'image de résonance magnétique (s140).
PCT/CN2018/125855 2018-12-29 2018-12-29 Procédé, dispositif et appareil pour une séparation eau-graisse utilisant une image de résonance magnétique, et support d'enregistrement WO2020133527A1 (fr)

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WO2013130587A1 (fr) * 2012-02-28 2013-09-06 The Board Of Regents Of The University Of Texas System Procédé et appareil de correction de phase prolongée en imagerie par résonance magnétique asservie en phase
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