Method for determining refractive index distribution of sample

Abstract

A method of determining a refractive index profile of a specimen includes: emitting a radiation beam from a radiation source, the radiation beam passing through an actual specimen comprising M actual specimen zones and then traveling toward a radiation detector comprising N sensing elements, where M and N are integers greater than 1; taking an actual image of the actual sample based on the interaction between the actual sample and the radiation beam using the radiation detector; and respectively determining M refractive index values of the M actual sample areas based on the actual image of the actual sample.

Description

[Technical field]

[0001] The invention relates to a method for determining the refractive index distribution of a sample. [Background technology]

[0002] A radiation detector is a device that measures a property of radiation. Examples of such properties may include the spatial distribution of the intensity, phase, and polarization of the radiation. The radiation measured by a radiation detector may be radiation that has been transmitted through an object. The radiation measured by a radiation detector may be electromagnetic radiation, such as infrared light, visible light, ultraviolet light, X-rays, or gamma rays. Radiation may be of other types, such as alpha and beta rays. [Summary of the invention]

[0003] The present invention discloses a method, comprising: emitting a radiation beam from a radiation source, the radiation beam passing through an actual sample and then moving toward a radiation detector, wherein the actual sample includes M actual sample areas, wherein the radiation detector includes N sensing elements, wherein M and N are integers greater than 1; using the radiation detector to capture an actual image of the actual sample based on the interaction between the actual sample and the radiation beam; and determining M refractive index values ​​of the M actual sample areas respectively based on the actual image of the actual sample.

[0004] In one aspect, the determining of M refractive index values ​​is not based on another actual image of the actual specimen.

[0005] In one aspect, the actual image is a two-dimensional image of the radiation intensity distribution, does not contain spectral data, and is not a reconstructed three-dimensional image.

[0006] In one aspect, determining the M refractive index values ​​based on the actual image includes: generating a simulated image of the simulated sample as if it were captured by the radiation detector based on the interaction between the simulated sample and the radiation beam; determining that the difference between the actual image and the simulated image is within a pre-specified tolerance range; and determining the M refractive index values ​​based on the refractive index distribution of the simulated sample.

[0007] In one aspect, every point of the actual sample is located within the simulated sample.

[0008] In one aspect, the M simulated sample areas of the simulated sample overlap with the M actual sample areas of the actual sample respectively, and each of the M refractive index values ​​is equal to the refractive index value of the corresponding simulated sample area of ​​the M simulated sample areas.

[0009] In one aspect, the actual image includes N picture elements, and the simulated image includes N picture elements.

[0010] In one aspect, the difference between the actual image and the simulated image is related to a function of (Ai-Si), where i=1, ..., N. Ai is the value of pixel (i) among the N pixels of the actual image. Si is the value of pixel (i) among the N pixels of the simulated image. The pixel (i) of the actual image and the pixel (i) of the simulated image both correspond to the sensor element (i) among the N sensor elements of the radiation detector.

[0011] In one aspect, determining the M refractive index values ​​based on the actual image includes: using an artificial neural network and taking the actual image as an input of the artificial neural network to generate the M refractive index values.

[0012] In one aspect, the radiation beam is an X-ray beam.

[0013] In one aspect, the photon energy of the X-ray beam is less than 10 KeV.

[0014] In one aspect, the radiation beam is a cone beam.

[0015] In one aspect, the radiation beam illuminates the entirety of the actual specimen.

[0016] In one aspect, the actual sample is frozen tissue.

[0017] In one aspect, a ratio of a distance between the radiation source and the actual sample to a distance between the actual sample and the radiation detector is in the range of 0.1 to 1.

[0018] In one aspect, the actual specimen has a shape of a slice having a uniform thickness measured along a direction perpendicular to the slice and parallel to a radiation receiving surface of the radiation detector.

[0019] In one aspect, the method further comprises removing a portion of the actual sample from the actual sample based on the M refractive index values.

Brief Description of the Drawings

[0020] Figure 1 A radiation detector according to an embodiment is schematically shown.

[0021] Figure 2 A simplified cross-sectional view of a radiation detector according to an embodiment is schematically shown.

[0022] Figure 3 A detailed cross-sectional view of a radiation detector according to an embodiment is schematically shown.

[0023] Figure 4A detailed cross-sectional view of a radiation detector according to an alternative embodiment is schematically shown.

[0024] Figure 5 A perspective view schematically illustrates an imaging system according to an embodiment.

[0025] Figure 6 A flow chart outlining the operation of an imaging system according to an embodiment is shown. [Specific implementation method]

[0026] Radiation Detectors

[0027] Figure 1 A radiation detector 100 is schematically shown as an example. The radiation detector 100 may include an array of pixels 150 (also referred to as sensing elements 150). The array may be a rectangular array (e.g. Figure 1 as shown), a honeycomb array, a hexagonal array, or any other suitable array. Figure 1 The array of pixels 150 in the example of FIG. 4 has 4 rows and 7 columns; however, in general, the array of pixels 150 may have any number of rows and any number of columns.

[0028] Each pixel 150 can be configured to detect radiation from a radiation source (not shown) incident thereon, and can be configured to measure the characteristics of the radiation (e.g., the energy, wavelength, and frequency of the particles). Radiation may include radiation particles such as photons (X-rays, gamma rays, etc.) and subatomic particles (alpha particles, beta particles, etc.). Each pixel 150 can be configured to count the number of radiation particles incident thereon over a period of time and whose energy falls within a plurality of energy ranges. All pixels 150 can be configured to count the number of radiation particles incident thereon over the same period of time and whose energy falls within a plurality of energy ranges. When the incident radiation particles have similar energies, the pixel 150 can be configured only to count the number of radiation particles incident thereon over a period of time, without measuring the energy of a single radiation particle.

[0029] Each pixel 150 may have its own analog-to-digital converter configured to digitize an analog signal representing the energy of an incident radiation particle into a digital signal, or to digitize an analog signal representing the total energy of multiple incident radiation particles into a digital signal. The pixels 150 may be configured to operate in parallel. For example, when one pixel 150 measures an incident radiation particle, another pixel 150 may be waiting for the radiation particle to arrive. The pixels 150 may not necessarily be individually addressable.

[0030] The radiation detector 100 described herein may have applications such as X-ray telescopes, X-ray mammography, industrial X-ray defect detection, X-ray microscopy or microradiography, X-ray casting inspection, X-ray nondestructive testing, X-ray weld inspection, X-ray digital subtraction angiography, etc. It may be appropriate to use the radiation detector 100 in place of a photographic plate, photographic film, a photo-stimulated phosphor plate (PSP plate), an X-ray image intensifier, a scintillator, or other semiconductor X-ray detector.

[0031] Figure 2 Schematically shows a Figure 1 2-2. Specifically, the radiation detector 100 may include a radiation absorbing layer 110 and an electronic circuit layer 120 (which may include one or more ASICs or application specific integrated circuits) for processing and analyzing electrical signals generated in the radiation absorbing layer 110 by incident radiation. The radiation detector 100 may or may not include a scintillator (not shown). The radiation absorbing layer 110 may include a semiconductor material such as silicon, germanium, GaAs, CdTe, CdZnTe, or a combination thereof. The semiconductor material may have a high mass attenuation coefficient for the radiation of interest.

[0032] As an example, Figure 3 Schematically shows Figure 1 Detailed cross-sectional view of the radiation detector 100 along line 2-2. Specifically, the radiation absorbing layer 110 may include one or more diodes (e.g., pin or pn) formed by one or more discrete regions 114 of the first doping region 111, the second doping region 113. The second doping region 113 may be separated from the first doping region 111 by an optional intrinsic region 112. The discrete regions 114 may be separated from each other by the first doping region 111 or the intrinsic region 112. The first doping region 111 and the second doping region 113 may have opposite types of doping (e.g., the first doping region 111 is p-type and the second doping region 113 is n-type, or the first doping region 111 is n-type and the second doping region 113 is p-type). Figure 3 In the example of , each discrete region 114 of the second doped region 113 forms a diode with the first doped region 111 and the optional intrinsic region 112. That is, in Figure 3 In the example of FIG. 1 , the radiation absorbing layer 110 has a plurality of diodes (more specifically, 7 diodes corresponding to Figure 1 The array has 7 pixels in a row of 150, for simplicity, Figure 3 Only two pixels 150 are marked in FIG. 1 . A plurality of diodes may have the electrode 119A as a common electrode. The first doped region 111 may also have a plurality of discrete portions.

[0033] The electronic circuit layer 120 may include an electronic system 121 suitable for processing or interpreting signals generated by radiation incident on the radiation absorption layer 110. The electronic system 121 may include analog circuits such as filter networks, amplifiers, integrators, and comparators, or digital circuits such as microprocessors and memories. The electronic system 121 may include one or more analog-to-digital converters. The electronic system 121 may include components shared by multiple pixels 150 or components dedicated to a single pixel 150. For example, the electronic system 121 may include an amplifier dedicated to each pixel 150 and a microprocessor shared between all pixels 150. The electronic system 121 may be electrically connected to the pixel 150 through the connection 131. The space between the connection 131 may be filled with a filling material 130, which may increase the mechanical stability of the connection between the electronic circuit layer 120 and the radiation absorption layer 110. Other bonding techniques may connect the electronic system 121 to the pixel 150 without using the connection 131.

[0034] When radiation from a radiation source (not shown) strikes the radiation absorption layer 110 including a diode, the radiation particles may be absorbed and generate one or more carriers (e.g., electrons, holes) through a variety of mechanisms. The carriers may drift to one of the electrodes of the diode under an electric field. The electric field may be an external electric field. The electrical contact 119B may include a plurality of discrete portions that are electrically in contact with a plurality of discrete regions 114, respectively. The term "electrical contact" may be used interchangeably with the term "electrode". In one embodiment, the carriers may drift in a plurality of directions, and the carriers generated by a single radiation particle are not substantially shared by two different discrete regions 114 (here "substantially not shared by..." means that less than 2%, less than 0.5%, less than 0.1%, or less than 0.01% of these carriers flow to a discrete region 114 that is different from the discrete region 114 to which the remaining carriers flow). The carriers generated by radiation particles incident on the periphery of one of the discrete regions 114 are not substantially shared by another of the discrete regions 114. A pixel 150 associated with a certain discrete region 114 may be an area around the discrete region 114 in which substantially all (more than 98%, more than 99.5%, more than 99.9%, or more than 99.99%) of the carriers generated by radiation particles incident therein flow toward the discrete region 114. That is, less than 2%, less than 1%, less than 0.1%, or less than 0.01% of the carriers flow out of the pixel 150.

[0035] Figure 4 Schematically shows a Figure 1Detailed cross-sectional view of radiation detector 100 along line 2-2. More specifically, radiation absorbing layer 110 may include resistors of semiconductor materials such as silicon, germanium, GaAs, CdTe, CdZnTe, or combinations thereof, but not diodes. The semiconductor material may have a high mass attenuation coefficient for the radiation of interest. In one embodiment, Figure 4 The electronic circuit layer 120 is similar in structure and function to Figure 3 The electronic circuit layer 120 is provided.

[0036] When radiation strikes the radiation absorbing layer 110, which includes a resistor but does not include a diode, it can be absorbed and generate one or more carriers through a variety of mechanisms. The radiation particle can generate 10 to 100,000 carriers. The carriers can drift to the electrical contacts 119A and 119B under an electric field. The electric field can be an external electric field. The electrical contact 119B may include multiple discrete portions. In one embodiment, the carriers can drift in multiple directions, and the carriers generated by a single radiation particle are substantially not shared by two different discrete portions of the electrical contact 119B (here "substantially not shared by..." means that less than 2%, less than 0.5%, less than 0.1% or less than 0.01% of these carriers flow to a discrete portion that is different from the discrete portion to which the rest of these carriers flow). The carriers generated by the radiation particles incident on one of the discrete portions of the electrical contact 119B are substantially not shared by another discrete portion of the discrete portions of the electrical contact 119B. A pixel 150 associated with a discrete portion of electrical contact 119B may be a region around the discrete portion in which substantially all (more than 98%, more than 99.5%, more than 99.9%, or more than 99.99%) of the charge carriers generated by radiation particles incident therein flow toward the discrete portion of electrical contact 119B. That is, less than 2%, less than 0.5%, less than 0.1%, or less than 0.01% of these charge carriers flow out of the pixel associated with the discrete portion of electrical contact 119B.

[0037] Imaging System

[0038] Figure 5 A perspective view of an imaging system 500 according to an embodiment is schematically shown. In one embodiment, the imaging system 500 may include a radiation source 510, a controller 530, and Figures 1 to 4 The radiation detector 100 in FIG.

[0039] In one embodiment, although radiation source 510 is shown as a point, radiation source 510 may have any size and shape (ie, radiation source 510 is not necessarily a point source).

[0040] In one embodiment, the actual sample 520a may be located between the radiation source 510 and the radiation detector 100 (as shown). In one embodiment, the actual sample 520a may have a slice shape (as shown), the slice may have a uniform thickness measured along a direction perpendicular to the slice, and may be parallel to the radiation receiving surface of the radiation detector 100.

[0041] In one embodiment, the actual sample 520a may be frozen tissue removed from a patient. In one embodiment, the ratio of the distance between the radiation source 510 and the actual sample 520a to the distance between the actual sample 520a and the radiation detector 100 may be in the range of 0.1 to 1. Note that these two distances may be measured in a direction perpendicular to the radiation receiving surface of the radiation detector 100.

[0042] For example, the actual sample 520a may include 6 actual sample areas (eg, actual sample area 520a (3, 1)). Figure 5 For example, 6 actual sample areas can be arranged into 2 rows and 3 columns (as shown in the figure).

[0043] Operation of the imaging system

[0044] In one embodiment, referring to Figure 5 , the imaging system 500 may operate as follows to determine the refractive index profile of the actual sample 520a.

[0045] In one embodiment, the radiation source 510 may send a radiation beam 512 to the actual sample 520a. In one embodiment, the radiation beam 512 may be an X-ray beam with a photon energy less than 10 KeV. In one embodiment, the radiation beam 512 may be a cone beam (as shown). In one embodiment, the radiation beam 512 may irradiate the entire actual sample 520a.

[0046] In one embodiment, the radiation detector 100 can capture an actual image of the actual sample 520a based on the interaction between the radiation beam 512 and the actual sample 520a. The interaction between the radiation beam 512 and the actual sample 520a can include, for example, a scenario in which a radiation beam 512.1 as part of the radiation beam 512 hits an area 520a.1 of the actual sample 520a, is refracted by the area 520a.1, and becomes a radiation beam 512.1' that hits the area 100.1 of the radiation detector 100.

[0047] For example, since the radiation detector 100 has 4×7 sensing elements 150 (eg Figure 1 As shown), the actual image of the actual sample 520a may have 4×7 pixels (ie, a total of 28 pixels).

[0048] In one embodiment, the controller 530 may respectively determine six refractive index values ​​of six actual sample areas of the actual sample 520 a based on the actual image of the actual sample 520 a .

[0049] Flowchart outlining the operation of the imaging system

[0050] Figure 6 shows a summary according to an embodiment Figure 5 Flowchart 600 of the operation of the imaging system 500.

[0051] In step 610, the operation may include sending a radiation beam from a radiation source, the radiation beam passing through a real sample and then traveling toward a radiation detector, wherein the real sample includes M real sample areas, wherein the radiation detector includes N sensing elements, wherein M and N are integers greater than 1. For example, in the above embodiment, with reference to Figure 5 , a radiation beam 512 is sent from a radiation source 510 , passes through an actual sample 520 a , and then travels toward a radiation detector 100 , wherein the actual sample 520 a has 6 actual sample areas and the radiation detector 100 has 28 sensing elements 150 .

[0052] In step 620, the operation may include using a radiation detector to capture an actual image of the actual sample based on the interaction between the actual sample and the radiation beam. Figure 5 The radiation detector 100 captures an actual image of the actual sample 520 a based on the interaction between the actual sample 520 a and the radiation beam 512 .

[0053] In step 630, the operation may include determining M refractive index values ​​of M actual sample areas based on the actual image of the actual sample. Figure 5 The controller 530 determines six refractive index values ​​of six actual sample areas of the actual sample 520a based on the actual image of the actual sample 520a.

[0054] Determining the Refractive Index Using a Simulated Specimen

[0055] In one embodiment, reference Figure 5 , the controller 530 can determine the six refractive index values ​​of the six actual sample areas of the actual sample 520a as shown below.

[0056] First, in one embodiment, the controller 530 may simulate the specimen 520 s and generate a simulated image of the simulated specimen 520 s as if captured by the radiation detector 100 based on the interaction between the simulated specimen 520 s and the radiation beam 512 .

[0057] For example, the simulated sample 520 may include 20 simulated sample areas, and the simulated sample areas may be arranged in 4 rows and 5 columns (as shown in the figure).

[0058] In one embodiment, each point of the actual sample 520a may be located within the simulated sample 520s (as shown).

[0059] In one embodiment, the six actual sample areas of the actual sample 520a may overlap with the six simulated sample areas of the simulated sample 520s (as shown in the figure). For example, the actual sample area 520a (3, 1) overlaps with the simulated sample area 520s (4, 2).

[0060] For example, since the radiation detector 100 has 4×7 sensing elements 150 , the simulated image of the simulated sample 520 may have 4×7 pixels (ie, a total of 28 pixels).

[0061] Next, in one embodiment, the controller 530 may determine the difference between the actual image of the actual sample 520a and the simulated image of the simulated sample 520. In one embodiment, the difference may be a function of (A1-S1), (A2-S2), ..., (A28-S28), or, in short, a function of (Ai-Si), i=1, ..., 28, where Ai is the value of pixel (i) among the 28 pixels of the actual image, Si is the value of pixel (i) among the 28 pixels of the simulated image, and both the pixel (i) of the actual image and the pixel (i) of the simulated image correspond to the sensor element (i) among the 28 sensor elements 150 of the radiation detector 100. For example, the above function may be

[0062] Next, in one embodiment, if the controller 530 determines that the difference between the actual image and the simulated image is within a pre-specified tolerance range, the controller 530 may determine six refractive index values ​​of six actual sample areas of the actual sample 520 a based on the refractive index distribution of the simulated sample 520 .

[0063] Specifically, in one embodiment, the six refractive index values ​​of the six simulated sample areas corresponding to the six actual sample areas can be used as the six refractive index values ​​of the six actual sample areas of the actual sample 520a, respectively. For example, the refractive index value of the simulated sample area 520s (4, 2) can be used as the refractive index value of the actual sample area 520a (3, 1).

[0064] Other embodiments

[0065] Using a single actual image

[0066] In the above embodiments, reference Figure 5, the six refractive index values ​​of the six actual sample areas of the actual sample 520a are determined using the actual image of the actual sample 520a. In one embodiment, other actual images of the actual sample 520a (except the actual image of the actual sample 520a described above) may not be used to determine the six refractive index values ​​of the six actual sample areas of the actual sample 520a. In other words, the determination of the six refractive index values ​​of the six actual sample areas of the actual sample 520a is not based on another actual image of the actual sample 520a.

[0067] There is only intensity data in the actual image

[0068] In one embodiment, reference Figure 5 The above-mentioned actual image of the actual sample 520a (used to determine the 6 refractive index values ​​of the 6 actual sample areas of the actual sample 520a) can be a two-dimensional image of the radiation intensity distribution (for example, 4×7 pixels), may not contain spectral data, and may not be a reconstructed three-dimensional image.

[0069] Remove part of the actual sample

[0070] In one embodiment, reference Figure 5 After determining the six refractive index values ​​of the six actual sample areas of the actual sample 520a, a portion (not shown) of the actual sample 520a may be identified based on the six refractive index values ​​of the six actual sample areas of the actual sample 520a, and then the portion may be removed from the actual sample 520a (e.g., for further inspection and analysis). For example, the portion to be identified and then removed may include an actual sample area having a refractive index value exceeding a pre-specified value.

[0071] Alternative Embodiments

[0072] Determination of refractive index using artificial neural networks

[0073] In the above embodiments, reference Figure 5 , the six refractive index values ​​of the six actual sample areas of the actual sample 520a are determined using the simulated sample 520. In an alternative embodiment, an artificial neural network (not shown) as shown below can be used to determine the six refractive index values ​​of the six actual sample areas of the actual sample 520a.

[0074] First, in one embodiment, an artificial neural network can be created and then trained. In one embodiment, a data set for training the artificial neural network can be simulated. Specifically, the training data set can include multiple data pairs.

[0075] Each data pair of the training data set may include a first element and a second element. The first element of each data pair may be a simulated sample (similar to Figure 5The second element may be a simulated image of the first element as if captured by the radiation detector 100 based on the interaction between the radiation beam 512 and the first element.

[0076] During the training of the artificial neural network, for each data pair used for training, the pixel value of the second element of each data pair is used as the input of the artificial neural network, and the refractive index distribution of the first element of each data pair is used as the output of the artificial neural network.

[0077] After training, the trained artificial neural network can be used to determine the refractive index distribution of the actual sample 520a. Specifically, the input of the trained artificial neural network is the 28 pixel values ​​of the actual image of the actual sample 520a, and the output of the trained artificial neural network will include 6 refractive index values ​​of 6 actual sample areas of the actual sample 520a.

[0078] Although various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for illustrative purposes only and are not intended to be limiting, with the true scope and spirit being indicated by the appended claims.

Claims

1. A method comprising: A radiation beam is emitted from a radiation source, the radiation beam passes through an actual sample and then travels toward a radiation detector, wherein the actual sample includes M actual sample areas, wherein the radiation detector includes N sensing elements, wherein M and N are integers greater than 1; using a radiation detector, taking an actual image of the actual sample based on an interaction between the actual sample and the radiation beam; and Based on the actual image of the actual sample, M refractive index values ​​of the M actual sample areas are respectively determined.

2. The method according to claim 1, characterized in that The determining of the M refractive index values ​​is not based on another actual image of the actual sample.

3. The method according to claim 1, characterized in that The actual image is a two-dimensional image of radiation intensity distribution, does not contain spectral data, and is not a reconstructed three-dimensional image.

4. The method according to claim 1, characterized in that The determining the M refractive index values ​​based on the actual image comprises: generating a simulated image of the simulated sample as if captured by the radiation detector based on an interaction between the simulated sample and the radiation beam; determining that a difference between the actual image and the simulated image is within a pre-specified tolerance range; and Based on the refractive index distribution of the simulated sample, the M refractive index values ​​are determined.

5. The method according to claim 4, characterized in that Each point of the actual sample is located within the simulated sample.

6. The method according to claim 5, characterized in that The M simulated sample areas of the simulated sample overlap with the M actual sample areas of the actual sample respectively. Each of the M refractive index values ​​is equal to the refractive index value of a corresponding simulated sample area among the M simulated sample areas.

7. The method according to claim 4, characterized in that The actual image includes N picture elements, and the simulated image includes N picture elements.

8. The method according to claim 7, characterized in that The difference between the actual image and the simulated image is related to a function of (Ai-Si), wherein i=1, ..., N, Ai is the value of pixel (i) among the N pixels of the actual image, Si is the value of pixel (i) among the N pixels of the simulated image, The picture element (i) of the actual image and the picture element (i) of the simulated image both correspond to the sensor element (i) among the N sensor elements of the radiation detector.

9. The method according to claim 1, characterized in that: Determining the M refractive index values ​​based on the actual image includes: using an artificial neural network and taking the actual image as an input of the artificial neural network to generate the M refractive index values.

10. The method according to claim 1, characterized in that The radiation beam is an X-ray beam.

11. The method according to claim 10, characterized in that The photon energy of the X-ray beam is less than 10 KeV.

12. The method according to claim 1, characterized in that The radiation beam is a cone beam.

13. The method according to claim 1, characterized in that The radiation beam illuminates the entirety of the actual sample.

14. The method according to claim 1, characterized in that The actual sample is frozen tissue.

15. The method according to claim 1, characterized in that A ratio of a distance between the radiation source and the actual sample to a distance between the actual sample and the radiation detector is in a range of 0.1 to 1.

16. The method according to claim 1, characterized in that The actual sample has a shape of a slice having a uniform thickness measured along a direction perpendicular to the slice and parallel to a radiation receiving surface of the radiation detector.

17. The method according to claim 1, characterized in that Also includes: Based on the M refractive index values, a portion of the actual sample is removed from the actual sample.

Images