Chemical shift encoding imaging method based on conversion region and local field map iteration

Abstract

The application discloses a chemical shift encoding imaging method based on a conversion region and local field map iteration, and the method comprises the following steps: acquiring an initial image, determining an initial field map solution of a conversion region based on the initial image, taking the initial field map solution as initial information, performing local field map iteration along at least two set directions, obtaining a target field map solution based on the local field map iteration results corresponding to each set direction, determining a first chemical component signal and a second chemical component signal based on the target field map solution, and performing chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal. Through multi-dimensional local field map iteration, the incorrect field map information is independently transmitted along different dimensions, the incorrect information transmitted along different directions is excluded, the correct information consistent in each dimension is reserved, the separated chemical component signal is more accurate in the case that the initial information is inaccurate, and the chemical shift encoding imaging effect is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, and in particular to a chemical shift encoding imaging method based on conversion region and local field map iteration. BACKGROUND

[0002] The chemical shift encoding imaging method is an imaging method based on detecting the chemical shift frequency difference of an object to distinguish the signals of different components. Different chemical environments of an imaging object cause its magnetic resonance signals to have different chemical shift frequencies. For example, the water-fat separation method based on the chemical shift frequency difference of hydrogen protons in water and fat to distinguish water and fat signals is the most common chemical shift encoding imaging method.

[0003] In the process of implementing the present application, it is found that at least the following technical problems exist in the prior art: The existing chemical shift component separation method has obtained accurate chemical shift component separation results in some application scenarios, however, the current method largely depends on the determined initial information, such as seed points. The requirement of seed points for the chemical component content of a pixel point is relatively harsh, and the seed points are difficult to find in some scanning scenarios and under scanning parameters, which causes instability of the algorithm, resulting in poor stability and low accuracy of chemical shift component separation, and further resulting in poor chemical shift encoding imaging effect. SUMMARY

[0004] The present application provides a chemical shift encoding imaging method based on conversion region and local field map iteration, to solve the technical problem that in the case of uncertain initial information, the field map information is difficult to accurately obtain, resulting in poor stability and low accuracy of chemical shift component separation, and to ensure the stability and accuracy of chemical shift component separation in the case of uncertain initial information, and to improve the chemical shift encoding imaging effect.

[0005] According to an aspect of the present application, a chemical shift encoding imaging method based on conversion region and local field map iteration is provided, comprising:

[0006] Obtaining an initial image, and determining an initial field map solution of a conversion region based on the initial image;

[0007] Taking the initial field map solution as initial information, performing local field map iteration along at least two set directions, and obtaining a target field map solution based on the local field map iteration results corresponding to each set direction;

[0008] Determining a first chemical component signal and a second chemical component signal based on the target field map solution, and performing chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal.

[0009] Optionally, further, the determining of the initial field map solution of the conversion region based on the initial image comprises:

[0010] determine foreground pixel points based on pixel values of pixel points in the initial image, and determine field map candidate solutions of each foreground pixel point;

[0011] determine a conversion region and an initial field map solution of the conversion region based on the field map candidate solutions of each foreground pixel point.

[0012] Optionally, further, the determining foreground pixel points based on pixel values of pixel points in the initial image comprises:

[0013] pixel points with pixel values greater than a set amplitude are taken as the foreground pixel points, and the set amplitude is determined based on pixel values of each pixel point.

[0014] Optionally, further, the taking the initial field map solution as initial information, performing local field map iteration along at least two set directions, and obtaining a target field map solution based on local field map iteration results corresponding to each set direction comprises:

[0015] taking the initial field map solution as initial information, performing local field map iteration along a set direction respectively, and obtaining a corresponding local field map iteration result;

[0016] for each pixel point, determining target field map information of the pixel point according to field map information of the pixel point in each local field map iteration result;

[0017] determining a merged field map solution based on target field map information of each pixel point, and determining the target field map solution based on the merged field map solution.

[0018] Optionally, further, the taking the initial field map solution as initial information, performing local field map iteration along a set direction respectively, and obtaining a corresponding local field map iteration result comprises:

[0019] for each set direction, performing Hamming window filtering on the initial field map solution along the set direction to obtain a filtered field map, and determining an iterative field map solution of the field map according to the filtered field map, wherein a window function size of the Hamming window filtering is determined according to a resolution of the initial image in the set direction;

[0020] taking the iterative field map solution as new initial information, repeating the above steps until an iteration stopping condition is reached, and determining the local field map iteration result of the set direction.

[0021] Optionally, further, the determining target field map information of the pixel point according to field map information of the pixel point in each local field map iteration result comprises:

[0022] when the pixel point corresponds to consistent field map information in each of the local field map iteration results, taking the field map information in the local field map iteration results as target field map information of the pixel point;

[0023] when the pixel point corresponds to inconsistent field map information in each of the local field map iteration results, setting zero as the target field map information of the pixel point.

[0024] Optionally, further, the determining the target field map solution based on the merged field map solution comprises:

[0025] performing local field map iteration on the merged field map solution to obtain the target field map solution.

[0026] According to another aspect of the present application, there is provided a chemical shift encoding imaging apparatus based on conversion region and local field map iteration, comprising:

[0027] an initial field map solution determination module configured to acquire an initial image, and determine an initial field map solution of a conversion region based on the initial image;

[0028] a target field map solution determination module configured to take the initial field map solution as initial information, perform local field map iteration along at least two set directions, and obtain a target field map solution based on local field map iteration results corresponding to each set direction;

[0029] a chemical shift encoding imaging module configured to determine first and second chemical component signals based on the target field map solution, and perform chemical shift encoding imaging based on the first and / or second chemical component signals.

[0030] According to another aspect of the present application, there is provided an electronic device, comprising:

[0031] at least one processor; and

[0032] a memory communicatively connected to the at least one processor; wherein,

[0033] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the chemical shift encoding imaging method based on conversion region and local field map iteration according to any one of the embodiments of the present application.

[0034] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to perform the chemical shift encoding imaging method based on conversion region and local field map iteration according to any one of the embodiments of the present application.

[0035] The technical scheme of the embodiment of the present application comprises the following steps: obtaining an initial image, determining an initial field map of a conversion region based on the initial image, taking the initial field map as initial information, performing local field map iteration along at least two set directions, obtaining a target field map based on the local field map iteration results corresponding to each set direction, determining a first chemical component signal and a second chemical component signal based on the target field map, and performing chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal. Through multi-dimensional local field map iteration, the incorrect field map information is independently transmitted along different dimensions, and then the multi-dimensional local field map iteration results are combined to exclude the incorrect information transmitted along different directions and retain the correct information consistent in each dimension, thereby solving the technical problem that the field map information is difficult to accurately obtain in the case of uncertain initial information, resulting in poor stability and low accuracy of the separated chemical component signals, and achieving more accurate chemical component signals separated in the case of uncertain initial information and improved chemical shift encoding imaging effect.

[0036] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0038] Figure 1 is a flowchart of a chemical shift encoding imaging method based on conversion region and local field map iteration provided by the first embodiment of the present application;

[0039] Figure 2 is a flowchart of a chemical shift encoding imaging method based on conversion region and local field map iteration provided by the second embodiment of the present application;

[0040] Figure 3 is a chemical shift encoding imaging result diagram based on conversion region and local field map iteration provided by the second embodiment of the present application;

[0041] Figure 4 is a structure diagram of a chemical shift encoding imaging device based on conversion region and local field map iteration provided by the third embodiment of the present application;

[0042] Figure 5 is a structure diagram of an electronic device provided by the fourth embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the present application.

[0044] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to include only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0045] Embodiment one

[0046] Figure 1 is a flowchart of a chemical shift encoding imaging method based on conversion region and local field map iteration provided by the embodiment one of the present application. The embodiment can be applicable to the case of performing chemical shift encoding imaging on separated chemical shift components, especially applicable to the case of performing chemical shift encoding imaging under the condition of uncertain initial information. The method can be performed by a chemical shift encoding imaging device based on conversion region and local field map iteration. The chemical shift encoding imaging device based on conversion region and local field map iteration can be realized in the form of hardware and / or software, and can be configured in an electronic device. As shown in the figure, the method comprises: Figure 1

[0047] S110, acquiring an initial image, determining an initial field map solution of a conversion region based on the initial image.

[0048] ​In the embodiment, the chemical shift encoding imaging is performed based on an initial image. Optionally, the initial image can be an image reconstructed based on magnetic resonance signals acquired by a magnetic resonance imaging method. It should be noted that the embodiment can realize the chemical shift encoding imaging in the case that the initial information is uncertain, and therefore, the acquisition method of the initial image and the parameters (such as the magnetic field strength, the acquisition bandwidth, etc.) of the acquisition device are not limited. Even if the initial information in the initial image reconstructed based on the acquired signals is uncertain, the water-fat signals can be stably separated.

[0049] Optionally, the field map of the conversion region in the initial image can be calculated by a conversion region extraction method or a seed point discrimination method.

[0050] In an embodiment of the present application, the initial field map of the conversion region based on the initial image comprises: determining foreground pixel points based on the pixel values of the pixel points in the initial image, and determining the field map candidate solution of each foreground pixel point; determining the conversion region and the initial field map of the conversion region based on the field map candidate solution of each foreground pixel point.

[0051] Optionally, all the pixel points in the initial image can be preprocessed to screen out the foreground pixel points, and the remaining regions are regarded as the image background, which does not need to be processed. Then, the field map candidate solution of the foreground pixel points is determined, and the initial field map of the conversion region is further determined.

[0052] Optionally, the determination of the field map candidate solution of each foreground pixel point comprises: determining the fitting error of the foreground pixel point for each foreground pixel point; and taking the phase vector of the local minimum value of the fitting error as the field map candidate solution. Taking the water-fat signal separation for chemical shift encoding imaging as an example, for each foreground pixel point, the fitting error of the foreground pixel point can be determined according to wherein err(p) is the fitting error, S is the acquired water-fat signal, p is the phase vector, and A is the parameter matrix of the multi-point Dixon signal model. The local minimum value of the fitting error err(p) can be searched in the mode of traversing (-π, π] according to the above formula, and the phase vector of the fitting error corresponding to the local minimum value is taken as the field map candidate solution of the foreground pixel point.

[0053] In some embodiments, the determining the foreground pixel points based on the pixel values of the pixels in the initial image comprises: determining the foreground pixel points as the pixels with pixel values greater than a set amplitude, the set amplitude being determined based on the pixel values of the pixels. The amplitude can be determined according to the pixel values of all the pixels in the initial image, and the pixels with pixel values greater than the amplitude are selected as the foreground pixel points. Optionally, the characteristic value of the pixel values of all the pixels can be used as the amplitude, such as the mean value, variance, or other characteristic values of all the pixels. The maximum pixel value can also be determined, and a portion of the maximum pixel value can be used as the amplitude, such as 5% of the maximum pixel value. The specific amplitude setting method can be set according to actual conditions, which is not limited herein.

[0054] S120, using the initial field solution as initial information, performing local field map iteration along at least two set directions, and obtaining a target field solution based on the local field map iteration results corresponding to each set direction.

[0055] Overall, after the initial field solution of the conversion region is solved, the initial field solution is used as initial information, and local field map iteration is performed along at least two directions, so that the incorrect initial information is transmitted along three different directions at this time, and the correct information remains consistent in three cases. The correct initial information is screened out through iteration in different directions, and the target field solution is obtained based on the correct initial information.

[0056] In an embodiment of the present application, the initial field solution is used as initial information, local field map iteration is performed along at least two set directions, and a target field solution is obtained based on the local field map iteration results corresponding to each set direction, which comprises: using the initial field solution as initial information, performing local field map iteration along a set direction to obtain a corresponding local field map iteration result; for each pixel point, determining the target field information of the pixel point according to the field information of the pixel point in each local field map iteration result; determining a merged field solution based on the target field information of each pixel point, and determining the target field solution based on the merged field solution.

[0057] Optionally, local field map iteration can be performed for each set direction using the initial field solution as initial information to obtain a local field map iteration result corresponding to each set direction. Then, the target field information corresponding to each pixel point is determined according to the field information of the pixel point in each local field map iteration result. Then, the target field information of each pixel point is integrated to obtain a merged field solution. Finally, the target field solution is determined based on the merged field solution. The set direction can be set according to actual needs, and three mutually perpendicular directions can be set as the set direction.

[0058] In one implementation, the initial field map solution is taken as initial information, and local field map iteration is performed along a set direction to obtain a corresponding local field map iteration result, including: for each set direction, Hamming window filtering is performed on the initial field map solution along the set direction to obtain a filtered field map, and an iteration field map solution of the field map is determined according to the filtered field map, wherein a window function size of the Hamming window filtering is determined according to a resolution of the initial image in the set direction; the iteration field map solution is taken as new initial information, and the above steps are repeatedly executed until an iteration stop condition is reached, and a local field map iteration result of the set direction is determined.

[0059] Taking a single set direction as an example, assuming that the set direction is a corresponding direction of an xy plane, and the solution of the conversion region is taken as initial information, a local field map iteration is used to determine the field map solution of the pixel points of the remaining region. The solution of the conversion region along the xy plane is filtered by a Hamming window, and the window function size can be determined by L=k / r

[0060] According to the resolution of image acquisition, wherein k=30mm, and r is the resolution of image acquisition in a certain dimension (unit: mm). Exemplarily, the resolution of the xy plane acquisition is 3*3mm 2 , and the window function size used is 10*10. The initial information is filtered by the above window function to obtain a filtered field map P filter , and a candidate solution of the field map is selected as an iteration field map solution according to the filtering result:

[0061]

[0062] Then, the current iteration field map solution is taken as initial information, and the above process is executed again until all the remaining pixel points in the entire image are determined, and P s,1 is obtained as the local field map iteration result of the set direction.

[0063] For any set direction, the local field map iteration result of the set direction can be obtained by the above method.

[0064] In this embodiment, the target field map information of the pixel point is determined according to the field map information of the pixel point in each local field map iteration result, including: when the field map information of the pixel point in each local field map iteration result is consistent, the field map information in the local field map iteration result is taken as the target field map information of the pixel point; and when the field map information of the pixel point in each local field map iteration result is inconsistent, zero is set as the target field map information of the pixel point.

[0065] It can be understood that when the initial information is correct, the field map information obtained by iteration in different directions is the same. Based on this, for each pixel point, assuming that the field map information corresponding to the pixel point in each local field map iteration result is consistent, it is indicated that the initial information corresponding to the pixel point is accurate, and the consistent field map information is taken as the target field map information of the pixel point; assuming that the field map information corresponding to the pixel point in each local field map iteration result is inconsistent, it is indicated that the initial information corresponding to the pixel point is inaccurate, and 0 is set as the target field map information of the pixel point, so as to avoid the influence of false information on the field map solution.

[0066] On the basis of the above scheme, the target field map solution is determined based on the merged field map solution, including: performing local field map iteration on the merged field map solution to obtain the target field map solution. Through the above scheme, the merged field map solution with accurate initial information can be obtained, and then the local field map iteration can be directly performed based on the merged field map solution to obtain the accurate target field map solution. The specific iteration mode can refer to the local iteration mode in the prior art, or can refer to the local iteration mode provided in the above embodiment, which is not limited here.

[0067] In the above scheme, the target field map solution is determined based on the merged field map solution, including: performing local field map iteration on the merged field map solution to obtain the target field map solution. Through the above scheme, the merged field map solution with accurate initial information can be obtained, and then the local field map iteration can be directly performed based on the merged field map solution to obtain the accurate target field map solution. The specific iteration mode can refer to the local iteration mode in the prior art, or can refer to the local iteration mode provided in the above embodiment, which is not limited here.

[0068] In the above scheme, the target field map solution is determined based on the merged field map solution, including: performing local field map iteration on the merged field map solution to obtain the target field map solution. Through the above scheme, the merged field map solution with accurate initial information can be obtained, and then the local field map iteration can be directly performed based on the merged field map solution to obtain the accurate target field map solution. The specific iteration mode can refer to the local iteration mode in the prior art, or can refer to the local iteration mode provided in the above embodiment, which is not limited here.

[0069] In the above scheme, the target field map solution is determined based on the merged field map solution, including: performing local field map iteration on the merged field map solution to obtain the target field map solution. Through the above scheme, the merged field map solution with accurate initial information can be obtained, and then the local field map iteration can be directly performed based on the merged field map solution to obtain the accurate target field map solution. The specific iteration mode can refer to the local iteration mode in the prior art, or can refer to the local iteration mode provided in the above embodiment, which is not limited here. In the above scheme, the target field map solution is determined based on the merged field map solution, including: performing local field map iteration on the merged field map solution to obtain the target field map solution. Through the above scheme, the merged field map solution with accurate initial information can be obtained, and then the local field map iteration can be directly performed based on the merged field map solution to obtain the accurate target field map solution. The specific iteration mode can refer to the local iteration mode in the prior art, or can refer to the local iteration mode provided in the above embodiment, which is not limited here.

[0070] The technical scheme of the embodiment comprises the following steps: acquiring an initial image, determining an initial field map of a conversion region based on the initial image; taking the initial field map as initial information, performing local field map iteration along at least two set directions, obtaining a target field map based on the local field map iteration results corresponding to each set direction; determining a first chemical component signal and a second chemical component signal based on the target field map, and performing chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal. Through multi-dimensional local field map iteration, the incorrect field map information is independently transmitted along different dimensions, and then the multi-dimensional local field map iteration results are combined to exclude the incorrect information transmitted along different directions and retain the correct information consistent in each dimension, so that the technical problem that the field map information is difficult to accurately acquire in the case of uncertain initial information and the separated chemical component signal is poor in stability and low in accuracy is solved, and the separated chemical component signal is more accurate in the case of uncertain initial information, and the chemical shift encoding imaging effect is improved.

[0071] Embodiment two

[0072] The embodiment provides a preferred embodiment on the basis of the above-mentioned embodiment.

[0073] The embodiment takes water-fat separation chemical shift encoding imaging as an example, proposes a method for accurately obtaining field map information in the case of uncertain initial information, and solves the problem of insufficient water-fat separation stability in this scenario. Overall, first, the field map of the conversion region is calculated by using the conversion region extraction method or the seed point identification method, and the definition and solving method have been given in the foregoing paper. After the solution of the conversion region is solved, the local field map iteration is used along the xy, xz and yz planes. At this time, the incorrect initial information will be transmitted along the three different directions, while the correct information will remain consistent in the three cases. The field maps in the three cases are combined, the consistent field map is retained as the initial information, and finally one more local field map iteration is performed to obtain the final field map. In the case where the field map is known, the signals of water and fat are calculated.

[0074] Before water-fat separation is performed, the calculation method of the parameters in water-fat separation is first determined.

[0075] For the pixel points containing water and fat at the same time, the multi-point Dixon signal model can be expressed as follows:

[0076]

[0077] Where Sn is the acquired water-fat signal, W and F are the signals of water and fat respectively, P is the number of peaks in the fat multi-peak model, α p is the relative content of each fat peak. f F,p f is the shift of each fat peak relative to the water resonance frequency, ψ is the inhomogeneity of the main magnetic field, TE is the echo time, n is the number of echoes (at least 2). n f is the shift of each fat peak relative to the water resonance frequency, ψ is the inhomogeneity of the main magnetic field, TE is the echo time, n is the number of echoes (at least 2).

[0078] The above equation can be rewritten in matrix form, let

[0079]

[0080]

[0081]

[0082] Then equation (1) is:

[0083] S = A (ψ) ρ (5)

[0084] In the above equation, the unknown quantities are W, F and the field ψ. By variable projection method, after the field is obtained, the water and fat signals can be calculated by least square solution:

[0085] ρ = A + (ψ) S (6)

[0086] Since the term in the equation itself has periodicity, it can be replaced by a phase vector:

[0087] p = e i2πψΔTE (7)

[0088] The equivalent replacement, p is a unit vector with direction. For each given field value, the corresponding fitting error can be calculated using the following formula:

[0089]

[0090] By traversing (-π, π] to seek the local minimum of err(p), the possible candidate solution of the field map is obtained.

[0091] For a special case in this signal model, two-point water-fat separation, the situation will be slightly different. However, the key to the problem in both multi-point water-fat separation and two-point water-fat separation is how to determine the correct solution of the field map, so the method used in the multi-point water-fat separation model and the two-point water-fat separation model can be universal.

[0092] ​After the magnetic resonance signal is collected, the possible field map is obtained in a traversal manner. For the two-point application, the analytical solution can be calculated using the two-point analytical method in the prior art. After the candidate solution of the field map is calculated, the solution of the conversion region is obtained using the conversion region extraction method. In the application scenario of the embodiment, the readout bandwidth is insufficient, resulting in incomplete conversion region calculation, and the field map solution of part of the conversion region may be incorrect, and it is difficult to obtain an accurate water-fat separation result using the original water-fat conversion region method. For the same reason, it is difficult to obtain stable results using the local field map iterative method based on the seed point.

[0093] Figure 2 is a flowchart of a chemical shift encoding imaging method based on conversion region and local field map iteration provided by an embodiment of the present application. The embodiment of the present application proposes a method based on conversion region extraction and local field map iteration, and realizes stable water-fat signal separation. Referring to Figure 2 , the specific steps include:

[0094] 1) First, pre-process all pixel points in the image, and retain the pixel points (for example, the amplitude is greater than 5% of the maximum signal amplitude) meeting a certain condition, and the remaining regions are regarded as the image background and are not processed. For each retained pixel point, the fitting error is calculated in the manner shown in formula (8), and the phase vector corresponding to the local minimum value of the fitting error is the candidate solution of the field map;

[0095] 2) Classify the candidate solutions of all pixel points in the image, and calculate the conversion region and the solution of the conversion region. Due to the bandwidth problem, the conversion region detection in the readout direction is incomplete, and even part of the region may be incorrect, resulting in the inability to perform water-fat region partitioning and subsequent water-fat separation based on the conversion region.

[0096] 3) Using the solution of the conversion region as initial information, the field map solution of the remaining region pixel points is determined using the local field map iteration. The solution of the conversion region is Hamming window filtered along the xy plane, and the window function size is adjusted according to the resolution of image acquisition:

[0097] L=k / r

[0098] Wherein, k=30mm, and r is the resolution (unit: mm) of image acquisition along a certain dimension. When the resolution of the xy plane acquisition is 3*3mm 2 , the window function size used is 10*10.

[0099] 4) The initial information is filtered using the above window function to obtain the filtered field map P filter , and the candidate solution of the field map is selected according to the filtering result:

[0100]

[0101] Then the current field map is taken as initial information to perform the process again until all the reserved pixel points in the whole image are determined to obtain P s,1 .

[0102] 5) In the same way, the local field map iteration is performed along the yz plane and the xz plane to obtain P s,2 and P s,3 respectively.

[0103] 6) The phase merging is performed on P s,1 , P s,2 and P s,3 . For any pixel point, if the solutions in P s,1 , P s,2 and P s,3 are consistent, the field map information of the pixel point is reserved; if not, the field map information of the point is set to zero to obtain the merged field map P s .

[0104] 7) The local field map iteration is performed again on the merged field map P s to obtain the final field map solution P final .

[0105] 8) The final water and fat signals are calculated according to the final field map result:

[0106]

[0107] W and F are the final separated water and fat signals.

[0108] Figure 2 In the figure, (a) is the amplitude of the original image, (b1) and (b2) are two candidate solutions of the field map, (c) is the solution of the conversion region, (d1)-(d3) are the field map solutions obtained by using the local field map iteration along the xz, yz and xy planes respectively, (e) is the merged solution, (f) is the solution obtained by using the local field map iteration with (e) as initial information, (g) and (h) are the separated water and fat signals respectively.

[0109] It should be noted that, in order to verify the feasibility of the embodiment of the present application, sample data has been collected for imaging. Specifically, the collection sequence is T2_fse, B0=3T, and the imaging parameters are as follows: repetition time TR=2000ms, collection bandwidth 220Hz / pixel, resolution 0.5*0.5mm 2 , layer thickness 4mm, number of layers 20, flip angle 130°, TE=[0, 0.839]ms. Figure 3 is a chemical shift encoding imaging result schematic diagram based on a conversion region and a local field map iteration provided by the second embodiment of the present application. Figure 3The processing result of the sample data is shown in the middle, Figure 3 The left side in the middle is a water signal image, and the right side is a fat signal image, which are obtained by Figure 3 It can be seen that the method provided in the embodiment can stably separate water and fat signals, and there is no obvious separation error tissue.

[0110] On the basis of the above-mentioned embodiment, the signal model in formula (1) can be changed, so that the method executed based on the changed signal model can be used for other chemical shift component corresponding chemical shift encoding imaging method.

[0111] The technical scheme of the embodiment, according to the resolution of the collected image in each image dimension, the size of the window is adjusted adaptively, the echo acquisition time selection range is flexible, and the acquisition efficiency can be faster; through multiple dimension local field map iteration, the error field map information is transmitted along different dimensions, independent of each other, so that the algorithm has good stability for the error of the initial information.

[0112] Embodiment three

[0113] Figure 4 It is a structure schematic diagram of a chemical shift encoding imaging device based on conversion region and local field map iteration provided by the third embodiment of the application. As Figure 4 shown, the device comprises an initial field map determination module 410, a target field map determination module 420 and a chemical shift encoding imaging module 430, wherein:

[0114] The initial field map determination module 410 is used to acquire an initial image, and determine an initial field map of a conversion region based on the initial image;

[0115] The target field map determination module 420 is used to perform local field map iteration along at least two set directions with the initial field map as initial information, and obtain a target field map based on the local field map iteration results corresponding to each set direction;

[0116] The chemical shift encoding imaging module 430 is used to determine a first chemical component signal and a second chemical component signal based on the target field map, and perform chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal.

[0117] The technical scheme of the embodiment comprises the following steps: obtaining an initial image, determining an initial field diagram of a conversion region based on the initial image, taking the initial field diagram as initial information, performing local field diagram iteration along at least two set directions, obtaining a target field diagram based on the local field diagram iteration results corresponding to each set direction, determining a first chemical component signal and a second chemical component signal based on the target field diagram, and performing chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal. Through multi-dimensional local field diagram iteration, the incorrect field diagram information is independently transmitted along different dimensions, and then the multi-dimensional local field diagram iteration results are combined to exclude the incorrect information transmitted along different directions and retain the correct information consistent in each dimension, so that the technical problem that the field diagram information is difficult to accurately obtain in the case of uncertain initial information and the separated chemical component signal is poor in stability and low in accuracy is solved, and the separated chemical component signal is more accurate in the case of uncertain initial information, and the chemical shift encoding imaging effect is improved.

[0118] Based on the above-mentioned embodiment, optionally, the initial field diagram determination module 410 is specifically configured to:

[0119] determine foreground pixel points based on the pixel values of the pixel points in the initial image, and determine field diagram candidate solutions of the foreground pixel points;

[0120] determine the conversion region and the initial field diagram of the conversion region based on the field diagram candidate solutions of the foreground pixel points.

[0121] Based on the above-mentioned embodiment, optionally, the initial field diagram determination module 410 is specifically configured to:

[0122] determine the foreground pixel points as the pixel points with pixel values greater than a set amplitude value, and determine the set amplitude value based on the pixel values of the pixel points.

[0123] Based on the above-mentioned embodiment, optionally, the target field diagram determination module 420 is specifically configured to:

[0124] take the initial field diagram as initial information, perform local field diagram iteration along the set directions respectively, and obtain corresponding local field diagram iteration results;

[0125] for each pixel point, determine target field diagram information of the pixel point according to the field diagram information of the pixel point in the local field diagram iteration results;

[0126] determine a combined field diagram based on the target field diagram information of the pixel points, and determine the target field diagram based on the combined field diagram.

[0127] Based on the above-mentioned embodiment, optionally, the target field diagram determination module 420 is specifically configured to:

[0128] for each set direction, a hamming window filtering is performed on the initial field map along the set direction to obtain a filtered field map, and an iterative field map solution of the field map is determined according to the filtered field map, wherein a window function size of the hamming window filtering is determined according to a resolution of the initial image in the set direction;

[0129] The iterative field map solution is taken as new initial information, and the above steps are repeatedly performed until an iteration stopping condition is reached, and a local field map iteration result of the set direction is determined.

[0130] On the basis of the above embodiment, optionally, the target field map solution determination module 420 is specifically configured to:

[0131] When the field map information corresponding to the pixel point in each of the local field map iteration results is consistent, the field map information in the local field map iteration result is taken as the target field map information of the pixel point;

[0132] When the field map information corresponding to the pixel point in each of the local field map iteration results is inconsistent, zero is set as the target field map information of the pixel point.

[0133] On the basis of the above embodiment, optionally, the target field map solution determination module 420 is specifically configured to:

[0134] The merged field map solution is subjected to local field map iteration to obtain the target field map solution.

[0135] The chemical shift encoding imaging device based on the conversion region and the local field map iteration provided in the embodiments of the present application can execute the chemical shift encoding imaging method based on the conversion region and the local field map iteration provided in any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0136] Embodiment four

[0137] Figure 5 is a structural schematic diagram of an electronic device provided in Embodiment Four of the present application. The electronic device 10 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the present application described and / or claimed in this document.

[0138] As Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., communicatively connected to the at least one processor 11, where the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded into the random access memory (RAM) 13 from the storage unit 18. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0139] Various components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc., an output unit 17, such as various types of displays, a speaker, etc., a storage unit 18, such as a magnetic disk, an optical disk, etc., and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0140] The processor 11 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the iterative chemical shift encoding imaging method based on the conversion region and local field map.

[0141] In some embodiments, the iterative chemical shift encoding imaging method based on the conversion region and local field map can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the iterative chemical shift encoding imaging method based on the conversion region and local field map described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the iterative chemical shift encoding imaging method based on the conversion region and local field map by any other appropriate means, such as by means of firmware.

[0142] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system on a chip systems (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0143] Computer programs implementing the method of chemical shift encoding imaging based on conversion region and local field map iteration of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program running on the processor implements the functions / operations specified in the flow diagrams and / or block diagrams. The computer program can execute entirely on a machine, partly on a machine, partly on a machine as a stand-alone software package, partly on a machine and partly on a remote machine or entirely on a remote machine or server.

[0144] Embodiment five

[0145] Embodiment five of the present application also provides a computer readable storage medium, which stores computer instructions for causing a processor to execute a method of chemical shift encoding imaging based on conversion region and local field map iteration, the method comprising:

[0146] obtaining an initial image, determining an initial field map solution of a conversion region based on the initial image;

[0147] performing local field map iteration along at least two set directions with the initial field map solution as initial information, and obtaining a target field map solution based on the local field map iteration results corresponding to each set direction;

[0148] determining a first chemical component signal and a second chemical component signal based on the target field map solution, and performing chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal.

[0149] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0150] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0151] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0152] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0153] It should be understood that the various forms of flow shown above can be reordered, added to, or have steps deleted. For example, the steps described in the present application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0154] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A chemical shift encoding imaging method based on transformation region and local field map iteration, characterized in that, include: Acquire an initial image, and determine an initial field diagram of the conversion region based on the initial image; Using the initial field diagram as initial information, local field diagram iteration is performed along at least two set directions, and the target field diagram is obtained based on the local field diagram iteration results corresponding to each set direction. Based on the target field diagram, a first chemical component signal and a second chemical component signal are determined, and chemical shift encoding imaging is performed based on the first chemical component signal and / or the second chemical component signal. The step of using the initial field diagram as initial information, performing local field diagram iterations along at least two predetermined directions, and obtaining the target field diagram based on the local field diagram iteration results corresponding to each predetermined direction includes: Using the initial field diagram as initial information, local field diagram iterations are performed along the set directions to obtain the corresponding local field diagram iteration results; For each pixel, the target field map information of the pixel is determined based on the field map information in the iteration results of each local field map corresponding to the pixel; The merged field diagram is determined based on the target field diagram information of each pixel, and the target field diagram is determined based on the merged field diagram.

2. The method according to claim 1, characterized in that, The determination of the initial field diagram of the transformation region based on the initial image includes: Foreground pixels are determined based on the pixel values ​​of the pixels in the initial image, and field map candidate solutions are determined for each of the foreground pixels; The transformation region and the initial field map solution of the transformation region are determined based on the field map candidate solutions of each of the foreground pixels.

3. The method according to claim 2, characterized in that, Determining the foreground pixels based on the pixel values ​​of the pixels in the initial image includes: Pixels with pixel values ​​greater than a set amplitude are designated as foreground pixels, and the set amplitude is determined based on the pixel values ​​of each pixel.

4. The method according to claim 1, characterized in that, The step of using the initial field diagram as initial information and performing local field diagram iterations along predetermined directions to obtain corresponding local field diagram iteration results includes: For each set direction, a Hamming window filter is applied to the initial field diagram along the set direction to obtain a filtered field diagram. An iterative field diagram of the field diagram is determined based on the filtered field diagram. The size of the window function of the Hamming window filter is determined according to the resolution of the initial image in the set direction. Using the iterative field diagram as new initial information, repeat the above steps until the iteration stopping condition is met, and determine the local field diagram iteration result in the set direction.

5. The method according to claim 1, characterized in that, Determining the target field map information of a pixel based on the field map information in the iteration results of each local field map corresponding to the pixel includes: When the field map information in each of the local field map iteration results is consistent, the field map information in the local field map iteration results is taken as the target field map information of the pixel. When the field map information corresponding to each local field map iteration result is inconsistent, zero is set to the target field map information of the pixel.

6. The method according to claim 1, characterized in that, Determining the target field diagram based on the merged field diagram includes: The target field diagram is obtained by performing local field diagram iteration on the merged field diagram.

7. A chemical shift-encoded imaging device based on transformation region and local field map iteration, characterized in that, include: The initial field diagram determination module is used to acquire an initial image and determine the initial field diagram of the conversion region based on the initial image. The target field diagram determination module is used to perform local field diagram iteration along at least two set directions using the initial field diagram as initial information, and to obtain the target field diagram based on the local field diagram iteration results corresponding to each set direction. A chemical shift encoding imaging module is used to determine a first chemical component signal and a second chemical component signal based on the target field diagram, and to perform chemical shift encoding imaging based on the first chemical component signal and / or the second chemical component signal. The target field diagram determination module is specifically used for: Using the initial field diagram as initial information, local field diagram iterations are performed along the set directions to obtain the corresponding local field diagram iteration results; For each pixel, the target field map information of the pixel is determined based on the field map information in the iteration results of each local field map corresponding to the pixel; The merged field diagram is determined based on the target field diagram information of each pixel, and the target field diagram is determined based on the merged field diagram.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, which enables the at least one processor to perform the chemical shift-coded imaging method based on the iterative transformation region and local field map as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the chemical shift-coded imaging method based on the iteration of the conversion region and local field map as described in any one of claims 1-6.

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