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專利授權區

專利授權區
專利名稱(中)	利用掃描式同調光繞射的三維顯影方法及系統
專利名稱(英)	THREE-DIMENSIONAL IMAGING METHOD AND SYSTEM USING SCANNING-TYPE COHERENT DIFFRACTION
專利家族	中華民國：I782822 大陸：CN116266378A(公開號) 美國：US11968351
專利權人	國立清華大學 100%
發明人	陳健群
技術領域	光電光學

專利摘要(英)
Therefore, developing a 3D imaging method that is relatively convenient and time-saving, and/or that can minimize the damage of light irradiation for the purpose of 3D image reconstruction to a sample object has become a goal in the related technical field. An object of the disclosure is to provide a 3D imaging method that uses scanning-type coherent diffraction and that can alleviate at least one of the drawbacks of the prior art. According to the disclosure, the 3D imaging method includes steps of: (A) by a light source that is moved relative to a sample object to N number of scanning positions one by one in a scanning manner, emitting, at each of the scanning positions, a coherent light beam toward the sample object while having a same orientation to form a light spot on the sample object, so as to define N number of light spot regions on the sample object that respectively correspond to the N number of the scanning positions, wherein N is a positive integer, and any adjacent two of the light spot regions partly overlap each other; (B) by a 2D photodetector, detecting, for the coherent light beam emitted by the light source at each of the scanning positions, diffraction of the coherent light beam that passes through the corresponding one of the light spot regions, so as to obtain N number of 2D diffraction data distributions that respectively correspond to the scanning positions; (C) by a processor, using a mathematical coordinate transformation to map all data points of each of the 2D diffraction data distributions onto a 3D spherical coordinate system to generate a pair of spherical shells that are symmetric with respect to an origin of the 3D spherical coordinate system, and presenting all data points on one of the spherical shells in a 3D Cartesian coordinate system of a reciprocal space, so as to obtain N number of 3D intensity distributions in the reciprocal space, each of the 3D intensity distributions corresponding to one of the scanning positions to which the 2D diffraction data distribution corresponds, and being represented as I_(j,q)^M, where j is an integer ranging from 1 to N; (D) by the processor, performing, for each value of j from 1 to N, an iteration based on a sample function O_(j,r) that is related to a 3D structure of the sample object, a light source function P_(j,r) that is related to a structure of the light spot regions, and the 3D intensity distributions that respectively correspond to the scanning positions, so as to obtain a sample reconstruction function candidate and a light source reconstruction function candidate that correspond to the iteration, wherein the iteration includes operations of (i) performing Fourier transform on a wave function ψ_(j,r) to obtain a distribution data φ_(j,q) for the reciprocal space, where the wave function ψ_(j,r) is defined as a product of the sample function O_(j,r) and the light source function P_(j,r); (ii) updating the distribution data φ_(j,q) in terms of amplitude based on one of the 3D intensity distributions I_(j,q)^M that corresponds to the jth one of the scanning positions, so as to obtain an updated distribution data 〖φ’〗_(j,q); (iii) performing inverse Fourier transform on the updated distribution data 〖φ’〗_(j,q) to obtain an updated wave function 〖ψ’〗_(j,r) for a real space; (iv) obtaining an updated sample function 〖O’〗_(j,r) and an updated light source function 〖P’〗_(j,r) based on the sample function O_(j,r), the light source function P_(j,r) and the updated wave function 〖ψ’〗_(j,r); (v) when j≠N, repeating operations (i) to (iv) for a next value of j with the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of operations (i) to (iv); and (vi) when j=N, making the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) obtained in operation (iv) for j=N respectively serve as the sample reconstruction function candidate and the light source reconstruction function candidate for the iteration; (E) by the processor, determining whether the sample reconstruction function candidate satisfies a predetermined convergence condition; (F) by the processor, upon determining in step (E) that the sample reconstruction function candidate does not satisfy the predetermined convergence condition, repeating steps (D) and (E) with the sample reconstruction function candidate and the light source reconstruction function candidate respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of step (D) when j=1; and (G) by the processor, after determining in step (E) that the sample reconstruction function candidate satisfies the predetermined convergence condition, making the sample reconstruction function candidate serve as a sample reconstruction function, executing a predetermined 3D graphics program to generate, based on the sample reconstruction function, a 3D envelope curved surface that corresponds to a specific value included in the sample reconstruction function, and that serves as a 3D reconstruction image of the sample object, and displaying the 3D reconstruction image on a display module. Another object of the disclosure is to provide a 3D imaging system that uses scanning-type coherent diffraction and that can alleviate at least one of the drawbacks of the prior art. According to the disclosure, the 3D imaging system is provided to reconstruct a 3D image for a sample object, and includes a light source, a light source driver module, a 2D photodetector, a processor and a display module. The light source is movable on a movement plane that faces a surface of the sample object in a spacing direction, and is operable to emit a coherent light beam toward the surface of the sample object while having a specific orientation. The light source driver module is configured to drive movement of the light source to N number of scanning positions on the movement plane one by one in a scanning manner, so that the light source, at each of the scanning positions, emits the coherent light beam toward the sample object while having the specific orientation to form a light spot on the sample object, thereby defining N number of light spot regions on the sample object that respectively correspond to the N number of the scanning positions, where N is a positive integer, and any adjacent two of the light spot regions partly overlap each other. The 2D photodetector is disposed to detect, for the coherent light beam emitted by the light source at each of the scanning positions, diffraction of the coherent light beam that passes through the corresponding one of the light spot regions, so as to obtain N number of 2D diffraction data distributions that respectively correspond to the scanning positions, wherein the movement plane, the sample object and the 2D photodetector are arranged along the spacing direction. The processor is electrically connected to the 2D photodetector for receiving the 2D diffraction data distributions, and includes a coordinate transformation module, an iteration module, a convergence determination module and a reconstruction module. The coordinate transformation module is configured to use a mathematical coordinate transformation to map all data points of each of the 2D diffraction data distributions onto a 3D spherical coordinate system to generate a pair of spherical shells that are symmetric with respect to an origin of the 3D spherical coordinate system, and is configured to present all data points on one of the spherical shells in a 3D Cartesian coordinate system of a reciprocal space, so as to obtain N number of 3D intensity distributions in the reciprocal space. Each of the 3D intensity distributions corresponds to one of the scanning positions to which the 2D diffraction data distribution corresponds, and is represented as I_(j,q)^M, where j is an integer from 1 to N. The iteration module is configured to perform, for each value of j from 1 to N, an iteration based on a sample function O_(j,r) that is related to a 3D structure of the sample object, a light source function P_(j,r) related to a structure of the light spot regions, and the 3D intensity distributions that respectively correspond to the scanning positions, so as to obtain a sample reconstruction function candidate and a light source reconstruction function candidate that correspond to the iteration. The iteration includes operations of: (i) performing Fourier transform on a wave function ψ_(j,r) to obtain a distribution data φ_(j,q) for the reciprocal space, where the wave function ψ_(j,r) is defined as a product of the sample function O_(j,r) and the light source function P_(j,r); (ii) updating the distribution data φ_(j,q) in terms of amplitude based on one of the 3D intensity distributions I_(j,q)^M that corresponds to the jth one of the scanning positions, so as to obtain an updated distribution data 〖φ’〗_(j,q); (iii) performing inverse Fourier transform on the updated distribution data 〖φ’〗_(j,q) to obtain an updated wave function 〖ψ’〗_(j,r) for a real space; (iv) obtaining an updated sample function 〖O’〗_(j,r) and an updated light source function 〖P’〗_(j,r) based on the sample function O_(j,r), the light source function P_(j,r) and the updated wave function 〖ψ’〗_(j,r); (v) when j≠N, repeating operations (i) to (iv) for a next value of j with the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of operations (i) to (iv); and (vi) when j=N, making the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) obtained in operation (iv) for j=N respectively serve as the sample reconstruction function candidate and the light source reconstruction function candidate of the iteration. The convergence determination module configured to determine whether the sample reconstruction function candidate satisfies a predetermined convergence condition, to, upon determining that the sample reconstruction function candidate does not satisfy the predetermined convergence condition, cause the iteration module to repeat the iteration with the sample reconstruction function candidate and the light source reconstruction function candidate respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of the iteration, and to, after determining that the sample reconstruction function candidate satisfies the predetermined convergence condition, make the sample reconstruction function candidate serve as a sample reconstruction function that is a phase-retrieval sample function. The reconstruction module is configured to execute a predetermined 3D graphics program to generate, based on the sample reconstruction function, a 3D envelope curved surface that corresponds to a specific value included in the sample reconstruction function, and that serves as a 3D reconstruction image of the sample object. The display module is electrically connected to the processor, and is operable by the processor to display the 3D reconstruction image.

專利摘要(英)

Therefore, developing a 3D imaging method that is relatively convenient and time-saving, and/or that can minimize the damage of light irradiation for the purpose of 3D image reconstruction to a sample object has become a goal in the related technical field. An object of the disclosure is to provide a 3D imaging method that uses scanning-type coherent diffraction and that can alleviate at least one of the drawbacks of the prior art. According to the disclosure, the 3D imaging method includes steps of: (A) by a light source that is moved relative to a sample object to N number of scanning positions one by one in a scanning manner, emitting, at each of the scanning positions, a coherent light beam toward the sample object while having a same orientation to form a light spot on the sample object, so as to define N number of light spot regions on the sample object that respectively correspond to the N number of the scanning positions, wherein N is a positive integer, and any adjacent two of the light spot regions partly overlap each other; (B) by a 2D photodetector, detecting, for the coherent light beam emitted by the light source at each of the scanning positions, diffraction of the coherent light beam that passes through the corresponding one of the light spot regions, so as to obtain N number of 2D diffraction data distributions that respectively correspond to the scanning positions; (C) by a processor, using a mathematical coordinate transformation to map all data points of each of the 2D diffraction data distributions onto a 3D spherical coordinate system to generate a pair of spherical shells that are symmetric with respect to an origin of the 3D spherical coordinate system, and presenting all data points on one of the spherical shells in a 3D Cartesian coordinate system of a reciprocal space, so as to obtain N number of 3D intensity distributions in the reciprocal space, each of the 3D intensity distributions corresponding to one of the scanning positions to which the 2D diffraction data distribution corresponds, and being represented as I_(j,q)^M, where j is an integer ranging from 1 to N; (D) by the processor, performing, for each value of j from 1 to N, an iteration based on a sample function O_(j,r) that is related to a 3D structure of the sample object, a light source function P_(j,r) that is related to a structure of the light spot regions, and the 3D intensity distributions that respectively correspond to the scanning positions, so as to obtain a sample reconstruction function candidate and a light source reconstruction function candidate that correspond to the iteration, wherein the iteration includes operations of (i) performing Fourier transform on a wave function ψ_(j,r) to obtain a distribution data φ_(j,q) for the reciprocal space, where the wave function ψ_(j,r) is defined as a product of the sample function O_(j,r) and the light source function P_(j,r); (ii) updating the distribution data φ_(j,q) in terms of amplitude based on one of the 3D intensity distributions I_(j,q)^M that corresponds to the jth one of the scanning positions, so as to obtain an updated distribution data 〖φ’〗_(j,q); (iii) performing inverse Fourier transform on the updated distribution data 〖φ’〗_(j,q) to obtain an updated wave function 〖ψ’〗_(j,r) for a real space; (iv) obtaining an updated sample function 〖O’〗_(j,r) and an updated light source function 〖P’〗_(j,r) based on the sample function O_(j,r), the light source function P_(j,r) and the updated wave function 〖ψ’〗_(j,r); (v) when j≠N, repeating operations (i) to (iv) for a next value of j with the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of operations (i) to (iv); and (vi) when j=N, making the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) obtained in operation (iv) for j=N respectively serve as the sample reconstruction function candidate and the light source reconstruction function candidate for the iteration; (E) by the processor, determining whether the sample reconstruction function candidate satisfies a predetermined convergence condition; (F) by the processor, upon determining in step (E) that the sample reconstruction function candidate does not satisfy the predetermined convergence condition, repeating steps (D) and (E) with the sample reconstruction function candidate and the light source reconstruction function candidate respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of step (D) when j=1; and (G) by the processor, after determining in step (E) that the sample reconstruction function candidate satisfies the predetermined convergence condition, making the sample reconstruction function candidate serve as a sample reconstruction function, executing a predetermined 3D graphics program to generate, based on the sample reconstruction function, a 3D envelope curved surface that corresponds to a specific value included in the sample reconstruction function, and that serves as a 3D reconstruction image of the sample object, and displaying the 3D reconstruction image on a display module. Another object of the disclosure is to provide a 3D imaging system that uses scanning-type coherent diffraction and that can alleviate at least one of the drawbacks of the prior art. According to the disclosure, the 3D imaging system is provided to reconstruct a 3D image for a sample object, and includes a light source, a light source driver module, a 2D photodetector, a processor and a display module. The light source is movable on a movement plane that faces a surface of the sample object in a spacing direction, and is operable to emit a coherent light beam toward the surface of the sample object while having a specific orientation. The light source driver module is configured to drive movement of the light source to N number of scanning positions on the movement plane one by one in a scanning manner, so that the light source, at each of the scanning positions, emits the coherent light beam toward the sample object while having the specific orientation to form a light spot on the sample object, thereby defining N number of light spot regions on the sample object that respectively correspond to the N number of the scanning positions, where N is a positive integer, and any adjacent two of the light spot regions partly overlap each other. The 2D photodetector is disposed to detect, for the coherent light beam emitted by the light source at each of the scanning positions, diffraction of the coherent light beam that passes through the corresponding one of the light spot regions, so as to obtain N number of 2D diffraction data distributions that respectively correspond to the scanning positions, wherein the movement plane, the sample object and the 2D photodetector are arranged along the spacing direction. The processor is electrically connected to the 2D photodetector for receiving the 2D diffraction data distributions, and includes a coordinate transformation module, an iteration module, a convergence determination module and a reconstruction module. The coordinate transformation module is configured to use a mathematical coordinate transformation to map all data points of each of the 2D diffraction data distributions onto a 3D spherical coordinate system to generate a pair of spherical shells that are symmetric with respect to an origin of the 3D spherical coordinate system, and is configured to present all data points on one of the spherical shells in a 3D Cartesian coordinate system of a reciprocal space, so as to obtain N number of 3D intensity distributions in the reciprocal space. Each of the 3D intensity distributions corresponds to one of the scanning positions to which the 2D diffraction data distribution corresponds, and is represented as I_(j,q)^M, where j is an integer from 1 to N. The iteration module is configured to perform, for each value of j from 1 to N, an iteration based on a sample function O_(j,r) that is related to a 3D structure of the sample object, a light source function P_(j,r) related to a structure of the light spot regions, and the 3D intensity distributions that respectively correspond to the scanning positions, so as to obtain a sample reconstruction function candidate and a light source reconstruction function candidate that correspond to the iteration. The iteration includes operations of: (i) performing Fourier transform on a wave function ψ_(j,r) to obtain a distribution data φ_(j,q) for the reciprocal space, where the wave function ψ_(j,r) is defined as a product of the sample function O_(j,r) and the light source function P_(j,r); (ii) updating the distribution data φ_(j,q) in terms of amplitude based on one of the 3D intensity distributions I_(j,q)^M that corresponds to the jth one of the scanning positions, so as to obtain an updated distribution data 〖φ’〗_(j,q); (iii) performing inverse Fourier transform on the updated distribution data 〖φ’〗_(j,q) to obtain an updated wave function 〖ψ’〗_(j,r) for a real space; (iv) obtaining an updated sample function 〖O’〗_(j,r) and an updated light source function 〖P’〗_(j,r) based on the sample function O_(j,r), the light source function P_(j,r) and the updated wave function 〖ψ’〗_(j,r); (v) when j≠N, repeating operations (i) to (iv) for a next value of j with the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of operations (i) to (iv); and (vi) when j=N, making the updated sample function 〖O’〗_(j,r) and the updated light source function 〖P’〗_(j,r) obtained in operation (iv) for j=N respectively serve as the sample reconstruction function candidate and the light source reconstruction function candidate of the iteration. The convergence determination module configured to determine whether the sample reconstruction function candidate satisfies a predetermined convergence condition, to, upon determining that the sample reconstruction function candidate does not satisfy the predetermined convergence condition, cause the iteration module to repeat the iteration with the sample reconstruction function candidate and the light source reconstruction function candidate respectively serving as the sample function O_(j,r) and the light source function P_(j,r) for operation (i) in the repetition of the iteration, and to, after determining that the sample reconstruction function candidate satisfies the predetermined convergence condition, make the sample reconstruction function candidate serve as a sample reconstruction function that is a phase-retrieval sample function. The reconstruction module is configured to execute a predetermined 3D graphics program to generate, based on the sample reconstruction function, a 3D envelope curved surface that corresponds to a specific value included in the sample reconstruction function, and that serves as a 3D reconstruction image of the sample object. The display module is electrically connected to the processor, and is operable by the processor to display the 3D reconstruction image.

聯絡資訊
承辦人姓名	楊美茹
承辦人電話	03-5715131 #62305
承辦人Email	mjyang2@mx.nthu.edu.tw