Method and system for sample scanning x-ray multi-lamella imaging

Abstract

The present application relates to a kind of sample scanning type X-ray multilayer imaging method and system.Sample scanning type X-ray multilayer imaging method includes the following steps:S1, adjusting the position, angle of sample mask and detector mask in X-ray edge illumination imaging device, so that the center position of each detector unit corresponding to field illumination curve in the field of view appears difference along the sample scanning movement direction;S2, obtains the field illumination curve of each detection unit in the field of view;S3, move sample, detector acquires the image of sample at each position;S4, by the value of detection unit when sample passes through and the multilayer image of field illumination curve of corresponding detection unit is extracted, wherein, sample scanning type moves, passes through multiple detection units in the field of view, the value of detection unit that passes through changes due to the absorption, refraction and scattering signal value of sample, by the change of a point on the illumination curve of multiple detector units that pass through caused by sample, realize sample scanning type X-ray multilayer imaging.

Description

Technical Field

[0001] This invention relates to the field of X-ray imaging, and more specifically, to a method and system for sample scanning X-ray multi-contrast imaging. Background Technology

[0002] Multicontrast imaging, as an important development direction in X-ray imaging technology, images the attenuation, refraction, and scattering of X-rays by a sample, providing details that traditional techniques cannot offer. Multicontrast imaging technology has evolved from its initial research stage, which relied on synchrotron radiation sources, to its current stage, utilizing optical elements to reduce the requirements for the X-ray source. In multicontrast imaging methods, edge illumination transforms phase and scattering information, which are difficult to observe directly, into changes in light intensity on the detector through sample and detector masks, thus achieving multicontrast imaging.

[0003] Currently, there are two main methods to achieve sample scanning edge illumination multi-contrast imaging. One method involves fabricating an asymmetric mask to actively generate misalignment in the field of view, thus achieving multi-contrast imaging. The other method uses a moving mask, fitting the values ​​of the detector units along the sample's path as it moves into an illumination curve to achieve multi-contrast imaging. Both methods have certain requirements for the mask and are not suitable for large-scale applications. The asymmetric mask method suffers from the drawback that the sample movement step size is fixed after the asymmetric mask is fabricated, making it difficult to adjust according to actual conditions. The moving mask method requires the formation of multiple stripes in the field of view to enhance the imaging effect, but there are regions where the slits between the masks are completely misaligned between these stripes. These regions contribute very little to the phase and scattered signal areas, reducing the utilization efficiency of the imaging units. Furthermore, both methods transform the illumination curve formed by mask movement into illumination curves formed at different positions in the field of view. Therefore, the τ and σ values ​​related to area, broadening, and DC component in the background illumination curves of each detector unit in the field of view are required. 2 The three parameters, τ, σ, and b, should be as similar as possible, which places high demands on the uniformity of the mask. When the performance of the mask is not uniform at different locations, the τ and σ of each detection unit will vary. 2 When the three parameters b differ significantly, the above method will introduce noise.

[0004] Therefore, there is an urgent need to develop an edge illumination multi-contrast imaging method that is suitable for large-scale applications, has low requirements for masks, and is easy to operate. Summary of the Invention

[0005] The technical problem to be solved by the present invention is how to realize an edge illumination multi-contrast imaging method that is suitable for large-scale applications, has low requirements for masks, and is easy to operate.

[0006] To solve the above-mentioned technical problems, according to one aspect of the present invention, a method for sample scanning X-ray multi-contrast imaging is provided, wherein the method is applied to an X-ray edge illumination imaging device including a radiation source, a sample mask, a sample stage, a detector mask, and a detector, wherein the radiation source, sample mask, sample stage, detector mask, and detector are arranged in the XOZ plane and sequentially along the Z-axis; the radiation source is used to emit X-rays, and the sample stage is used to place the sample to be imaged; the X-ray optical axis is along the Z-axis, and the X-rays pass through the sample mask, the sample stage, and the detector mask, and the X-rays passing through the detector mask are detected by the detector unit; the method includes the following steps: Step S1, adjusting the sample in the X-ray edge illumination imaging device... The positions and angles of the mask and detector mask cause differences in the center positions of the field illumination curves corresponding to each detector unit along the sample scanning direction in the field of view; Step S2: Obtain the field illumination curves of each detector unit in the field of view; Step S3: Move the sample, and the detector acquires images of the sample at various positions; Step S4: Extract multi-contrast images from the values ​​of the detector units as the sample passes and the corresponding field illumination curves of the detector units. The sample moves in a scanning manner along the X-axis direction, passing through multiple detector units in the field of view. The values ​​of the detector units it passes through change due to the absorption, refraction, and scattering signals of the sample. By observing the change at a point on the illumination curves of the multiple detector units passed through by the sample, sample scanning X-ray multi-contrast imaging is achieved.

[0007] According to an embodiment of the present invention, in step S4, the multi-contrast of the sample can be incorporated into the open field illumination curve through a multi-point multi-illumination curve optimization method. The difference between the actual value and the assumed result is used as the optimization direction to extract the multi-contrast image. The assumed value of the multi-contrast result of the sample is introduced into the background illumination curve of each detection unit through the influence of the sample's absorption, refraction, and scattering on X-rays to obtain the assumed sample illumination curve and the corresponding assumed sample value. The difference between the obtained assumed sample value and the value of each detection unit when the actual sample passes through is used as the optimization direction to extract the multi-contrast image of the sample. When the value change of the detection unit is only related to one point in the sample grid, the extraction algorithm is as follows:

[0008]

[0009] Where m and n represent the regions of the sample to be reconstructed, y j w represents the actual value taken by the sample when it passes through the detection unit. j The weighting factor for each detection unit is used; the sample multicontrast value that satisfies the above formula is calculated by an iterative extraction method.

[0010] According to an embodiment of the present invention, in step S4, the multi-contrast of the sample can be incorporated into the open field illumination curve using a multi-point multi-illumination curve optimization method. The difference between the actual value and the assumed result is used as the optimization direction to extract the multi-contrast image. The assumed value of the sample's multi-contrast result is introduced into the background illumination curve of each detection unit through the influence of the sample's absorption, refraction, and scattering on X-rays to obtain the assumed sample illumination curve and the corresponding assumed sample value. The difference between the obtained assumed sample value and the value of each detection unit when the actual sample passes through is used as the optimization direction to extract the sample's multi-contrast image.

[0011] When the value change of a detection unit is related to multiple points in the sample grid, a factor P representing the weight of the influence of each sample grid point on the value change of the detection unit needs to be added, as shown in the following formula:

[0012]

[0013] Where m and n represent the regions of the sample to be reconstructed, y j w represents the actual value taken by the sample when it passes through the detection unit. j The weighting factor is for each detection unit; the subscript u is the sequence number of the sample position during the scanning imaging process. Each element in P is a weighting factor calculated based on the area or volume of the overlapping part of the ray beam corresponding to the detection unit j and the coordinates (m, n) of each sample point in the sample space when the sample moves to position u.

[0014] According to an embodiment of the present invention, in step S1, the mask can be moved in a stepping manner to obtain the field illumination curve of each detection unit; based on this, in step S3, the sample is scanned and moved, and the detector is used to capture the corresponding images when the sample is at different positions. The center position x0 of the field illumination curve of the multiple detection units through which the sample passes is different, so that the changes in the values ​​of each detector cover the influence of the sample on different positions on the illumination curve. That is, the influence of the sample on different positions of the illumination curve is distributed among different detection units, thereby satisfying the conditions for realizing scanning imaging. Thus, multi-contrast images are extracted in an iterative manner, realizing the iterative extraction method.

[0015] According to an embodiment of the present invention, it is assumed that the X-ray morphology changes induced by the sample at each imaging position are the same, that is, the absorption, phase, and scattering contrast are all the same; after the sample space is gridded, if the value change of each detection unit is only related to a point in the sample grid, the value of each detection unit can be represented in the following form:

[0016]

[0017] Where m and n are the sequence numbers of the sample region to be reconstructed, and j represents the sequence number of the detection unit that the sample region to be reconstructed has passed through.

[0018] If the value changes of each detection unit are related to multiple sample grid points, the value of each detection unit can be represented in the following form:

[0019]

[0020] Where m and n are the sequence numbers of the sample region to be reconstructed, j represents the sequence number of the detection unit that the sample region to be reconstructed passes through; the subscript u is the sequence number of the sample position during the scanning imaging movement, and each element in P is a weighting factor calculated based on the area or volume of the overlapping part of the ray beam corresponding to the detection unit j and the coordinates (m, n) of each sample point in the sample space when the sample moves to position u.

[0021] According to an embodiment of the present invention, the multi-contrast information of the sample can be incorporated into the existing empty field illumination curve, and the empty field illumination curve will then be transformed into the sample illumination curve shape. Using an iterative method, the difference between the simulated value obtained according to the above formula and the value when the sample actually passes through is used as the optimization direction. When the value of each detection unit is only related to a point in the sample grid, the specific optimization expression is as follows:

[0022]

[0023] Among them, w j is the weight factor of the detection unit j, and f is a constraint term that can be added according to the actual situation of the sample. Its purpose is to optimize the value of the reconstruction result by applying prior information. During the iteration process, the initial value can be carefully designed based on the relevant information of the sample, or the initial value τ, λ, φ, σ can be set to 1, 1, 0, 0 respectively by taking assumptions. Then, iterative optimization is performed based on the values ​​of the above expression, including one or more methods such as the conjugate gradient method and ADMM calculation method, in order to extract the multi-contrast image of the sample.

[0024] When the value changes of each detection unit are related to multiple points in the sample grid, the specific optimization expression is as follows:

[0025]

[0026] Among them, w jLet u be the weighting factor of detection unit j, and let u be the index of the sample position during the scanning imaging movement. Each element in P is a weighting factor calculated based on the area or volume of the overlapping part of the ray beam corresponding to detection unit j and the coordinates (m, n) of each sample point in the sample space when the sample moves to position u. f is a constraint term that can be added according to the actual situation of the sample. Its purpose is to optimize the value of the reconstruction result by applying prior information. During the iteration process, the initial values ​​can be carefully designed based on the relevant information of the sample, or the initial values ​​τ, λ, φ, and σ can be set to 1, 1, 0, and 0 respectively by taking assumptions. Then, iterative optimization is performed based on the values ​​of the above expression, including one or more methods such as the conjugate gradient method and ADMM calculation method, to extract the multi-contrast image of the sample.

[0027] According to an embodiment of the present invention, the number of multiple detection units is ≥3, more preferably 5, but is not limited thereto and depends on actual needs.

[0028] According to an embodiment of the present invention, in step S1, it can be assumed that there are m*n detection units in the field of view, and the positions of the moving sample mask and / or detector mask satisfy the following two conditions:

[0029] Condition 1: By actively moving the position of either the sample mask and / or the detector mask along the optical axis, the illumination curve of a row of detector cells along the sample movement direction in the imaging field of view satisfies:

[0030]

[0031] Where, x mask The position of the moving imaging device during scanning imaging is given by the illumination curve acquisition method. x0 is the center position of the illumination curve of the corresponding detection unit. i in the corresponding brackets is the sequence number of the detection unit along the Y-axis direction perpendicular to the sample movement, 0 is the first detection unit along the X-axis direction of the sample movement, n is the last detection unit, and σ is the broadening of the illumination curve of the corresponding detection unit.

[0032] Condition 2: By actively moving either the sample mask and / or the detector mask along the sample movement direction, the illumination curve at the center of a row of detector cells along the sample movement direction in the imaging field of view satisfies the following:

[0033]

[0034] Where n / 2 represents the serial number of the detection unit located at the center of the field of view.

[0035] The above two conditions are not strict requirements, but are currently the optimal conditions based on simulation. According to experiments, conditions near these are acceptable, but are not specifically limited to these conditions.

[0036] According to another aspect of the present invention, a system for sample scanning X-ray multi-contrast imaging is provided, comprising: an X-ray edge illumination imaging device, the X-ray edge illumination imaging device including a radiation source, a sample mask, a sample stage, a detector mask, and a detector; and employing the sample scanning X-ray multi-contrast imaging method as described above.

[0037] According to an embodiment of the present invention, the sample mask and the detector mask can be respectively mounted on the controller, and the position and angle of the sample mask and the detector mask on the X-axis, Y-axis and Z-axis can be adjusted by the controller.

[0038] According to an embodiment of the present invention, the controller for setting the detector mask can be a micrometer-level stepper stage, used to move the detector mask within the range of 0 to 200 micrometers with an accuracy of less than 0.1 μm.

[0039] Compared with the prior art, the technical solution provided by the embodiments of the present invention can achieve at least the following beneficial effects:

[0040] The present invention proposes a novel sample scanning X-ray multi-contrast imaging method based on edge illumination. This method can obtain images with three contrasts—absorption, phase, and scattering—during the sample scanning imaging process, which can meet practical engineering needs.

[0041] The edge-illuminated sample scanning X-ray multi-contrast imaging method of the present invention only requires sample movement, which has the advantage of being easy to operate compared with the classic edge-illuminated imaging method.

[0042] This invention extracts multi-contrast images through a multi-point, multi-IC optimization method. Compared with existing scanning edge illumination imaging methods, it has lower requirements for masks and is easier to apply on a large scale.

[0043] Imaging systems based on traditional edge illumination techniques can implement the sample scanning imaging method proposed in this invention, thereby expanding the application scope of edge illumination.

[0044] This invention does not require the background illumination curves τ and σ of each detection unit in the field of view. 2 Since the three parameters (b, s, and c) are the same, based on the principle of this invention, the final imaging effect has minimal relationship with these three parameters. This invention only requires that during the sample scanning process, the x0 parameter, representing the center position, of the background illumination curve of each detection unit in the sample imaging is different. This difference can be achieved by actively moving the sample mask or detector mask along the optical axis, thus placing lower requirements on the mask. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments will be briefly described below. Obviously, the drawings described below only relate to some embodiments of the present invention and are not intended to limit the present invention.

[0046] Figure 1 This is a flowchart illustrating a sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram illustrating a sample scanning X-ray multi-contrast imaging system according to an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram illustrating a sample scanning edge illumination imaging system according to an embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram showing the distribution of the center positions of the field illumination curves corresponding to a row of detector units in the field of view obtained by the sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention;

[0050] Figure 5 This is a schematic diagram showing the value distribution of a row of detector cells in the field of view obtained by the sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention;

[0051] Figure 6 This is a schematic diagram showing the five detection units that the sample area to be reconstructed passes through as it moves;

[0052] Figure 7 This illustrates an image acquired by the detector in an empty field in a sample scanning edge illumination imaging system according to an embodiment of the present invention;

[0053] Figure 8a ~c are absorption, phase, and scattering contrast images obtained by the sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] Unless otherwise defined, the technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains. The terms “first,” “second,” and similar terms used in the specification and claims of this patent application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms “an” or “a” and similar terms do not indicate a limitation of quantity, but rather indicate the presence of at least one.

[0056] Before scanning and imaging, the sample space needs to be divided into a suitable grid. Then, based on the imaging accuracy determined by the grid, the movement method and algorithm are determined to achieve multi-contrast image extraction. In this invention, grid division is done in two ways. The first method obtains the sample magnification ratio based on the relative positions of the X-ray source, sample, and detector. The shape of the detector unit is then reduced according to the magnification ratio to serve as the basic unit for dividing the sample space into grids. The second method uses a finer approach, further reducing the size of the basic unit obtained in the first method to serve as the basic unit for dividing the sample space into grids.

[0057] In scanning imaging, a sample movement-detector imaging-re-movement-re-imaging pattern is adopted, cyclically using images of the sample at different positions, and extracting multi-contrast information based on the obtained scanning images. Sample movement occurs in two ways. In the first way, after each sample movement, the X-ray beam behind the sample mask corresponding to any detector unit in the field of view passes only one point in the sample grid along its path. Influenced by this point, its shape changes before reaching the corresponding detector unit and being recorded. In the second movement mode, after each sample movement, the X-ray beam behind the sample mask corresponding to a detector unit in the field of view passes two or more sample grid points along its path. Influenced by these points, its shape changes before reaching the corresponding detector unit and being recorded.

[0058] Figure 1 This is a flowchart illustrating a sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating a sample scanning X-ray multi-contrast imaging system according to an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating a sample scanning edge illumination imaging system according to an embodiment of the present invention.

[0059] like Figures 1 to 3As shown, a sample scanning X-ray multi-contrast imaging method is applied to an X-ray edge illumination imaging device including a radiation source 1, a sample mask 2, a sample stage 3, a detector mask 4, and a detector 5. The radiation source 1, sample mask 2, sample stage 3, detector mask 4, and detector 5 are arranged in the XOZ plane and sequentially along the Z-axis. The radiation source 1 emits X-rays, and the sample stage 3 holds the sample to be imaged. The X-ray optical axis is along the Z-axis. The X-rays pass through the sample mask 2, the sample stage 3, and the detector mask 4. The number of detector units used for scanning imaging in the field of view is set to 1790*196. The X-rays passing through the detector mask 4 are detected by the detector 5, which obtains the values ​​of the detector units.

[0060] The method for sample scanning X-ray multicontrast imaging includes the following steps:

[0061] Step S1: Adjust the position and angle of the sample mask 2 and detector mask 4 in the X-ray edge illumination imaging device so that the center position of the empty field illumination curve corresponding to each detector unit along the sample scanning movement direction in the field of view is different;

[0062] Step S2: Obtain the field illumination curves of each detection unit in the field of view;

[0063] Step S3: Move the sample, and detector 5 acquires images of the sample at various locations;

[0064] Step S4: Extract the multi-contrast image from the values ​​of the detection units when the sample passes through and the corresponding field illumination curves of the detection units.

[0065] In this process, the sample moves in a scanning manner along the X-axis, passing through multiple detector units in the field of view. The values ​​of the detector units it passes through change due to the absorption, refraction, and scattering signals of the sample. By observing the change at a point on the illumination curve of the multiple detector units 5 that the sample passes through, the sample scanning X-ray multi-contrast imaging is achieved.

[0066] The edge-illuminated sample scanning X-ray multi-contrast imaging method of the present invention only requires sample movement, which has the advantage of simple operation compared with the classic edge-illuminated imaging method. The present invention extracts multi-contrast images through a multi-point multi-IC optimization method, which has lower requirements for masks and is easier to apply on a large scale compared with existing scanning edge-illuminated imaging methods.

[0067] According to one or more embodiments of the present invention, in step S4, the multi-contrast of the sample is incorporated into the open field illumination curve using a multi-point multi-illumination curve optimization method. The difference between the actual value and the assumed result is used as the optimization direction to extract the multi-contrast image. The assumed value of the multi-contrast result of the sample is introduced into the background illumination curve of each detection unit through the influence of the sample's absorption, refraction, and scattering on X-rays to obtain the assumed sample illumination curve and the corresponding assumed sample value. The difference between the obtained assumed sample value and the value of each detection unit when the actual sample passes through is used as the optimization direction to extract the multi-contrast image of the sample. When the value change of the detection unit is only related to one point in the sample grid, the extraction algorithm is as follows:

[0068]

[0069] Where m and n represent the regions of the sample to be reconstructed, y j w represents the actual value taken by the sample when it passes through the detection unit. j The weighting factor for each detection unit is used; the sample multicontrast value that satisfies the above formula is calculated by an iterative extraction method.

[0070] According to one or more embodiments of the present invention, in step S4, the multi-contrast of the sample is incorporated into the open field illumination curve using a multi-point multi-illumination curve optimization method. The difference between the actual values ​​and the assumed results is used as the optimization direction to extract the multi-contrast image. The assumed values ​​of the sample's multi-contrast results are introduced into the background illumination curve of each detection unit through the influence of the sample's absorption, refraction, and scattering on X-rays to obtain the assumed sample illumination curve and the corresponding assumed sample values. The difference between the obtained assumed sample values ​​and the values ​​of each detection unit when the actual sample passes through is used as the optimization direction to extract the sample's multi-contrast image.

[0071] When the value change of a detection unit is related to multiple points in the sample grid, a factor P representing the weight of the influence of each sample grid point on the value change of the detection unit needs to be added, as shown in the following formula:

[0072]

[0073] Where m and n represent the regions of the sample to be reconstructed, y j w represents the actual value taken by the sample when it passes through the detection unit. j The weighting factor is for each detection unit; the subscript u is the sequence number of the sample position during the scanning imaging process. Each element in P is a weighting factor calculated based on the area or volume of the overlapping part of the ray beam corresponding to the detection unit j and the coordinates (m, n) of each sample point in the sample space when the sample moves to position u.

[0074] According to one or more embodiments of the present invention, in step S1, the mask is moved in a stepwise manner to obtain the field illumination curve of each detection unit; based on this, in step S3, the sample is scanned and moved, and the detector 5 is used to capture images corresponding to the sample at different positions.

[0075] Among them, the center position x0 of the field illumination curve of the multiple detection units through which the sample passes has different values, so that the changes in the values ​​of each detector 5 cover the influence of the sample on different positions on the illumination curve. That is, the influence of the sample on different positions on the illumination curve is distributed among different detection units, thus satisfying the conditions for achieving scanning imaging. Therefore, multi-contrast images are extracted through iteration, realizing the iterative extraction method.

[0076] According to one or more embodiments of the present invention, it is assumed that the X-ray morphology changes induced by the sample at each imaging position are the same, that is, the absorption, phase, and scattering contrast are all the same; after the sample space is gridded, if the value change of each detection unit is only related to a point in the sample grid, the value of each detection unit can be represented in the following form:

[0077]

[0078] Where m and n are the sequence numbers of the sample region to be reconstructed, and j represents the sequence number of the detection unit that the sample region to be reconstructed has passed through.

[0079] If the value changes of each detection unit are related to multiple sample grid points, the value of each detection unit can be represented in the following form:

[0080]

[0081] Where m and n are the sequence numbers of the sample region to be reconstructed, j represents the sequence number of the detection unit that the sample region to be reconstructed passes through; the subscript u is the sequence number of the sample position during the scanning imaging movement, and each element in P is a weighting factor calculated based on the area or volume of the overlapping part of the ray beam corresponding to the detection unit j and the coordinates (m, n) of each sample point in the sample space when the sample moves to position u.

[0082] The present invention proposes a novel sample scanning X-ray multi-contrast imaging method based on edge illumination. This method can obtain images with three contrasts—absorption, phase, and scattering—during the sample scanning imaging process, which can meet practical engineering needs.

[0083] According to one or more embodiments of the present invention, the multi-contrast information of the sample is incorporated into the existing empty field illumination curve, and the empty field illumination curve is transformed into the sample illumination curve shape. Using an iterative method, the difference between the simulated value obtained according to the above formula and the value when the sample actually passes through is used as the optimization direction. When the value of each detection unit is only related to a point in the sample grid, the specific optimization expression is as follows:

[0084]

[0085] Among them, w j is the weight factor of the detection unit j, and f is a constraint term that can be added according to the actual situation of the sample. Its purpose is to optimize the value of the reconstruction result by applying prior information. During the iteration process, the initial value can be carefully designed based on the relevant information of the sample, or the initial value τ, λ, φ, σ can be set to 1, 1, 0, 0 respectively by taking assumptions. Then, iterative optimization is performed based on the values ​​of the above expression, including one or more methods such as the conjugate gradient method and ADMM calculation method, in order to extract the multi-contrast image of the sample.

[0086] When the value changes of each detection unit are related to multiple points in the sample grid, the specific optimization expression is as follows:

[0087]

[0088] Among them, w j Let u be the weighting factor of detection unit j, and let u be the index of the sample position during the scanning imaging movement. Each element in P is a weighting factor calculated based on the area or volume of the overlapping part of the ray beam corresponding to detection unit j and the coordinates (m, n) of each sample point in the sample space when the sample moves to position u. f is a constraint term that can be added according to the actual situation of the sample. Its purpose is to optimize the value of the reconstruction result by applying prior information. During the iteration process, the initial values ​​can be carefully designed based on the relevant information of the sample, or the initial values ​​τ, λ, φ, and σ can be set to 1, 1, 0, and 0 respectively by taking assumptions. Then, iterative optimization is performed based on the values ​​of the above expression, including one or more methods such as the conjugate gradient method and ADMM calculation method, to extract the multi-contrast image of the sample.

[0089] According to one or more embodiments of the present invention, the number of multiple detection units is ≥3, more preferably 5, but is not limited thereto and depends on actual needs.

[0090] According to one or more embodiments of the present invention, in step S1, assuming there are m*n detection units in the field of view, the positions of the moving sample mask 2 and / or detector mask 4 satisfy the following two conditions:

[0091] Condition 1: By actively moving the position of either the sample mask 2 and / or the detector mask 4 along the optical axis, the illumination curve of a row of detector cells along the sample movement direction in the imaging field of view satisfies:

[0092]

[0093] Where, x mask The position of the moving imaging device during scanning imaging is given by x0, which is the center position of the illumination curve of the corresponding detection unit. In the corresponding brackets, i is the sequence number of the detection unit along the Y-axis direction perpendicular to the sample movement, 0 is the first detection unit along the X-axis direction of the sample movement, n is the last detection unit, and σ is the broadening of the illumination curve of the corresponding detection unit.

[0094] Condition 2: By actively moving either sample mask 2 or detector mask 4 along the sample movement direction, the illumination curve center of a row of detector cells along the sample movement direction in the imaging field of view satisfies the following:

[0095]

[0096] Where n / 2 represents the serial number of the detection unit located at the center of the field of view.

[0097] The above two conditions are not mandatory requirements. These conditions are obtained from simulations to achieve the best results. However, experiments only need to be close to these conditions to achieve good imaging results. These conditions are not mandatory and are not subject to these restrictions. They are determined based on the actual situation.

[0098] According to another aspect of the present invention, a system for sample scanning X-ray multicontrast imaging is provided, comprising:

[0099] The X-ray edge illumination imaging device includes a radiation source 1, a sample mask 2, a sample stage 3, a detector mask 4, and a detector 5.

[0100] The sample scanning X-ray multi-contrast imaging method described above is employed.

[0101] Imaging systems based on traditional edge illumination techniques can implement the sample scanning imaging method proposed in this invention, thereby expanding the application scope of edge illumination.

[0102] According to one or more embodiments of the present invention, the sample mask 2 and the detector mask 4 are respectively disposed on the controller, and the position and angle of the sample mask 2 and the detector mask 4 on the X-axis, Y-axis and Z-axis can be adjusted by the controller.

[0103] According to one or more embodiments of the present invention, the controller for setting the detector mask 4 is a micrometer-level stepper stage, which is used to enable the detector mask 4 to move with an accuracy of less than 0.1 μm in the range of 0 to 200 micrometers.

[0104] According to one or more embodiments of the present invention, the X-ray source 1 is an X-ray source 1 with a tube voltage of 40 kV and a tube current of 400 μA. The detector 5 used is a photon counting detector 5, and the size of its detection unit is 100 μm. The period of the sample mask 2 is 77.3 μm, and the slit width is 20.3 μm; the period of the detector mask 4 is 98.1 μm, and the slit width is 26.2 μm.

[0105] In this example, the sample grid is divided according to a magnification ratio of 1.2 and a detector cell size of 100μm, resulting in an extracted multi-contrast image with an accuracy of 83.33μm.

[0106] The sample moves 1.5 mm at a time, and after each movement, each point in the sample space spans 18 pixels in the field of view. After each movement, the value change of each detection unit is only related to one sample grid point. After each ray beam is affected by only one sample grid point, its shape changes and is recorded by the detector. The total number of detection units in the field of view is 1790*196. During the process of each point in the sample grid moving into and out of the field of view, the total number of detection units whose values ​​change due to the influence of the sample point is approximately 10. The changes in the values ​​of these detection units are used to extract the multicontrast information of that sample point.

[0107] According to one or more embodiments of the present invention, when the sample scanning X-ray multicontrast imaging method is used,

[0108] Step 1: Adjust the position and angle of the sample mask 2 and the detector mask 4 to meet the imaging conditions. Adjust the Z angle of the two masks so that the grid lines of the two masks are parallel to a column of detector units of the detector 5. Adjust the X and Y angles of the two masks so that the two masks are nearly parallel to the plane of the detector 5. Adjust the X position of the two masks so that the center position of the illumination curve corresponding to the column of detector units in the field of view is approximately 0.31 μm, which is close to condition two required by this invention. Adjust the Z position of the detector mask 4 so that the center positions of the illumination curves of adjacent detector units differ by approximately 0.17 μm, and the center positions of the illumination curves at both ends of the field of view are 15.88 μm and -17.26 μm, respectively. Since the mean value of the empty field illumination curve σ of the imaging system is 15 μm, the relative positions of the two detector units on the illumination curves are close to +σ and -σ, which meets condition two required by this invention. Adjust the Y position of the two masks to maximize the field of view of the imaging system.

[0109] Figure 7This image shows a sample scanning edge illumination imaging system according to an embodiment of the present invention, where the detector 5 acquires an image in an empty field.

[0110] The final field image during scanning imaging is as follows: Figure 7 As shown, the system basically meets the two conditions for optimal imaging proposed in this invention.

[0111] Step 2: The detector mask 4 moves in 4μm increments within a range of 40–160μm, with a sampling time of 30 seconds at each position, to obtain the field illumination curve of each detector unit in the field of view.

[0112] Step 3: Place the sample into the sample stage 3 between the sample mask 2 and the detector mask 4. The sample stage 3 moves 1.5 mm at a time, and an image is captured after each movement.

[0113] Step 4: Using the multi-point multi-illumination curve optimization method, the multi-contrast of the samples is incorporated into the open field illumination curve. The difference between the actual values ​​and the assumed results is used as the optimization direction to extract the multi-contrast image.

[0114] Figure 4 This is a schematic diagram showing the distribution of the center positions of the field illumination curves corresponding to a row of detector units in the field of view obtained by the sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the value distribution of a row of detector cells in the field of view obtained by the sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention, wherein... Figure 4 and Figure 5 The results are from the simulation. Figure 6 This is a schematic diagram showing the five detection units that the sample area to be reconstructed passes through as it moves.

[0115] like Figure 6 As shown, the triangle symbol points represent the values ​​of each detection unit when a sample passes through, and the diamond point represents the value of the corresponding detection unit when there is no sample. The curve containing the diamond point is the fitted empty field illumination curve; the curve containing the triangle symbol points shows the shape of the empty field illumination curve changed by the sample when it passes through the detection unit. The hypothetical value of the multi-contrast result of the sample is introduced into the background illumination curve of each detection unit through the influence of the sample on the illumination curve, resulting in the hypothetical sample illumination curve shown by the dashed line, and the corresponding hypothetical sample value. Taking the difference between the obtained hypothetical sample value and the actual value of each detection unit when the sample passes through as the optimization direction, the multi-contrast image of the sample is extracted, as shown in the following formula:

[0116]

[0117] Where m and n represent the regions to be reconstructed for the sample, is the actual value taken by the sample when passing through the detection unit, and is the weight factor for each detection unit. This example calculates the sample multicontrast values ​​that satisfy the above formula through an iterative method.

[0118] This invention does not require the background illumination curves τ and σ of each detection unit in the field of view. 2 Since the three parameters (b, s, and c) are the same, based on the principle of this invention, the final imaging effect has minimal relationship with these three parameters. This invention only requires that during the sample scanning process, the x0 parameter, representing the center position, of the background illumination curve of each detection unit in the sample imaging is different. This difference can be achieved by actively moving the sample mask or detector mask along the optical axis, thus placing lower requirements on the mask.

[0119] Figure 8a ~c are absorption, phase, and scattering contrast images obtained by the sample scanning X-ray multi-contrast imaging method according to an embodiment of the present invention.

[0120] Based on this method, a sample scanning multi-contrast imaging was performed on a chicken feet sample, such as... Figure 8a As shown in Figure ~c, the multi-contrast images of the chicken foot obtained using this method show good imaging results. This chicken foot sample is a complex biological sample containing skin, bone, and muscle, with an imaging length of approximately 18 cm. This sample was used to evaluate the imaging capability of this method for complex biological samples. In the absorption contrast image, the bone and muscle of the sample are clearly distinguishable, and the overall contour imaging of the bone is good. In the phase contrast image, the imaging effect of the sample edges is even better, the medulla inside the bone is clearly highlighted, and the imaging effect of the complex structure of the bone ends and the chicken skin is better than that of the absorption contrast image. In the scattering contrast image, the signal in specific areas inside the bone is particularly obvious, and the signal at the bone edges is also strong. The multi-contrast images of the chicken foot show that, compared with the absorption contrast image, the phase contrast image and the scattering contrast image are superior in imaging the edges of the chicken foot and the edges of the bone, and can reveal the details of the bone ends.

[0121] The above description is merely an exemplary embodiment of the present invention and is not intended to limit the scope of protection of the present invention, which is determined by the appended claims.

Claims

1. A method of sample scanning x-ray multi-lamella imaging, wherein, The method is applied to an X-ray edge illumination imaging device including a ray source, a sample mask, a sample table, a detector mask and a detector, wherein the ray source, the sample mask, the sample table, the detector mask and the detector are arranged in the XOZ plane and sequentially along the Z-axis direction; the ray source is used to release X-rays, and the sample table is used to place a sample to be imaged; the X-ray optical axis is along the Z-axis direction, the X-rays pass through the sample mask, the sample table and the detector mask, and the field of view through which the X-rays pass is provided with a plurality of detection units, and the X-rays passing through the detector mask are obtained by the detection units of the detector; The method comprises the following steps: Step S1, adjusting the positions and angles of the sample mask and the detector mask in the X-ray edge illumination imaging device, so that the center position parameters x0 of the empty field illumination curves corresponding to each detector unit in the field of view along the sample scanning movement direction are different; Step S2, obtaining the empty field illumination curves of each detection unit in the field of view; Step S3, moving the sample, and the detector collects images of the sample at each position; Step S4, extracting a multi-contrast image from the values of the detection units when the sample passes through and the empty field illumination curves of the corresponding detection units, Wherein, the sample is scanned and moved, passes through a plurality of detection units in the field of view, the values of the passed detection units change due to the absorption, refraction and scattering signal values of the sample, and the change of a point on the illumination curve of the plurality of detector units passed through by the sample is realized, so as to realize the sample scanning X-ray multi-contrast imaging, In step S1, it is assumed that the detection units in the field of view are m*n, and the positions of the sample mask and / or the detector mask are moved to satisfy the following two conditions: Condition one, by actively moving the position of any mask of the sample mask and / or the detector mask along the optical axis direction, the illumination curve of a row of detection units in the imaging field of view along the sample movement direction satisfies: wherein is the position of the imaging device moved for collecting the illumination curve at the time of scanning imaging, is the center position of the illumination curve of the corresponding detection unit, i in the corresponding bracket is the serial number of the detection unit in the Y-axis direction perpendicular to the sample movement, 0 is the first detection unit in the X-axis direction along the sample movement, and n is the last detection unit, is the spread of the illumination curve of the corresponding detection unit; Condition two, by actively moving the position of any mask of the sample mask and / or the detector mask along the sample movement direction, the center of the illumination curve of a row of detection units in the imaging field of view along the sample movement direction satisfies: wherein denotes the index of the detection unit located in the center of the field of view, In step S4, by the multi-point multi-illumination curve optimization method, the multi-contrast of the sample is integrated into the empty field illumination curve, the difference between the actual value and the assumed result is taken as the optimization direction, so as to extract the multi-contrast image; the assumed value of the multi-contrast result of the sample is introduced into the background illumination curve of each detection unit through the influence of the absorption, refraction and scattering of the sample on the X-rays, to obtain the assumed sample illumination curve and the corresponding assumed sample value; the difference between the obtained assumed sample value and the actual sample value of each detection unit when the sample passes through is taken as the optimization direction, to extract the multi-contrast image of the sample, When the value change of the detection unit is only related to one point in the sample grid, the extraction algorithm is as follows: wherein m, n represent the sample to be reconstructed region, y j is the actual value of the sample when passing through the detection unit, w j is the weight factor of each detection unit; the sample multi-contrast value satisfying the above formula is calculated by the iterative extraction method.

2. The method of sample-scanning x-ray multi-lamella imaging of claim 1, wherein, In step S4, the multi-contrast of the sample is integrated into the empty field illumination curve by the multi-point multi-illumination curve optimization method, and the difference between the actual value and the assumed result is taken as the optimization direction to extract the multi-contrast image; the assumed value of the multi-contrast result of the sample is introduced into the background illumination curve of each detection unit by the influence of the absorption, refraction and scattering of the sample on the X-ray, to obtain the assumed sample illumination curve and the corresponding assumed sample value; the difference between the obtained assumed sample value and the value of each detection unit when the sample passes through is taken as the optimization direction to extract the multi-contrast image of the sample, Wherein, when the value change of the detection unit is related to multiple points in the sample grid, a factor P representing the influence weight of each sample grid point on the value change of the detection unit needs to be added, as shown in the following formula: wherein m, n represent the sample region to be reconstructed, y j is the actual value of the sample when passing through the detection unit, w j is the weight factor of each detection unit; the subscript u is the serial number of the sample position in the scanning imaging movement process, and each element in P is the weight factor calculated according to the area or volume of the overlapping part of the ray beam corresponding to the detection unit j and each sample point coordinate (m, n) in the sample space when the sample moves to the position u.

3. The method of sample-scanning x-ray multi-lamella imaging of claim 2, wherein, In step S1, the mask is moved in a step-by-step manner to obtain the empty field illumination curve of each detection unit; on this basis, in step S3, the sample is scanned and moved, and the corresponding images when the sample is at different positions are photographed by the detector, Wherein, the center position x0 of the empty field illumination curve of the multiple detection units through which the sample passes has a difference, so that the changes in the values of each detector cover the influence of the sample on different positions on the illumination curve, that is, the influence of different positions of the sample on the illumination curve is dispersed among different detection units, thereby meeting the condition of realizing scanning imaging, and the multi-contrast image is extracted by iteration, thereby realizing the iterative extraction method.

4. The method of sample scanning x-ray multi-lamella imaging of claim 3, wherein, It is assumed that the X-ray form change caused by the sample at each imaging position is the same, that is, the absorption, phase and scattering contrast are the same; after the sample space is grid processed, Wherein, when the value of each detection unit is only related to one point in the sample grid, it is represented by the following form: Wherein, m, n are the sequence numbers of the sample to be reconstructed, and j represents the sequence number of the detection unit through which the sample to be reconstructed region passes; When the value of each detection unit is related to multiple points in the sample grid, it is represented by the following form: Wherein, m, n are the sequence numbers of the sample to be reconstructed, and j represents the sequence number of the detection unit through which the sample to be reconstructed region passes; subscript u is the sequence number of the sample position in the scanning imaging movement process, and each element in P is a weight factor calculated according to the area or volume of the overlapping part of the ray beam corresponding to the detection unit j and each sample point coordinate (m, n) in the sample space when the sample moves to position u.

5. The method of sample scanning x-ray multi-lamella imaging of claim 4, wherein, The multi-contrast information of the sample is integrated into the existing empty field illumination curve, and the empty field illumination curve is changed into the sample illumination curve form. The difference between the simulated value obtained according to the formula and the value when the sample actually passes through is taken as the optimization direction by using the iterative method, Wherein, when the value change of each detection unit is only related to one point in the sample grid, the specific optimization expression is as follows: where w j In the formula, w is a weight factor of the detection unit j, and f is a constraint term that can be added according to the actual situation of the sample, which is used to optimize the value of the reconstruction result by applying prior information; in the iteration process, the initial value can be carefully designed according to the sample related information, or the initial value τ, λ, φ, σ can be set as 1, 1, 0, 0 respectively by assuming, and then one or more of the calculation methods including the conjugate gradient method and the ADMM are used for iterative optimization of the value of the above expression to extract the multi-contrast image of the sample. When the value change of each detection unit is related to multiple points in the sample grid, the specific optimization expression is as follows: where w j is the weight factor of the detection unit j, subscript u is the serial number of the sample position in the scanning imaging movement, each element in P is the weight factor calculated according to the area or volume of the overlapping part of the ray beam corresponding to the detection unit j and each sample point coordinate (m, n) in the sample space when the sample moves to position u; f is a constraint term that can be added according to the actual situation of the sample, which is used to optimize the value of the reconstruction result by applying prior information; in the iteration process, the initial value can be carefully designed according to the sample related information, or the initial value τ, λ, φ, σ can be set as 1, 1, 0, 0 respectively by assuming, and then one or more of the calculation methods including the conjugate gradient method and the ADMM are used for iterative optimization of the value of the above expression to extract the multi-contrast image of the sample.

6. A sample scanning X-ray multi-contrast imaging system, comprising: An X-ray edge illumination imaging device, comprising a ray source, a sample mask, a sample stage, a detector mask and a detector; The sample scanning X-ray multi-contrast imaging system adopts the sample scanning X-ray multi-contrast imaging method according to any one of claims 1-5.

7. The system for sample scanning x-ray multilayer imaging of claim 6, wherein, The sample mask and the detector mask are respectively arranged on a controller, and the position and angle of the sample mask and the detector mask on the X-axis, Y-axis and Z-axis can be adjusted through the controller.

8. The system for sample scanning x-ray multi-lamella imaging of claim 7, wherein, The controller for setting the detector mask is a micrometer level stepping stage, which is used to move the detector mask in the range of 0-200 micrometers with an accuracy less than 0.1 um.

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