Electron microscope and calibration method
The electron microscope system addresses sensitivity variations in direct detection cameras by calculating correction coefficients for sensor pixels, enhancing image accuracy and reducing noise for high-resolution imaging.
Patent Information
- Application Number
- JP2023132919
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- Filing Date
- 2023-08-17
- Publication Date
- 2025-11-12
- Estimated Expiration
- 2043-08-17
AI Technical Summary
Direct detection cameras in electron microscopes suffer from varying pixel sensitivities due to manufacturing errors, leading to inaccuracies in image formation.
An electron microscope system that calculates correction coefficients by averaging output values from frame images captured under Poisson conditions to correct the sensitivities of sensor pixels, using a CMOS image sensor to enhance accuracy.
The system effectively corrects sensitivity variations among sensor pixels, improving the accuracy of image capture and reducing noise, enabling high-resolution and high-contrast imaging.
Smart Images

Figure 0007768944000001 
Figure 0007768944000002 
Figure 0007768944000003
Abstract
Description
[Technical Field]
[0001] The present invention relates to an electron microscope and a calibration method. [Background technology]
[0002] Direct detection cameras in which electrons are directly incident on the sensitive area of an image sensor are known as cameras for transmission electron microscopes. For example, Patent Document 1 discloses a direct detection camera equipped with a direct detector (image sensor) as a camera for transmission electron microscopes. In the direct detector disclosed in Patent Document 1, the semiconductor layer that detects the electron beam is thinned to suppress the interaction between the electron beam and the semiconductor layer. This makes it possible to reduce noise due to excess signals greater than the incident electrons, which are generated by the interaction between the electron beam and the semiconductor layer. [Prior art documents] [Patent documents]
[0003] [Patent Document 1] Japanese Patent Publication No. 2022-002317 Summary of the Invention [Problem to be solved by the invention]
[0004] The direct detector disclosed in Patent Document 1 includes multiple pixels for forming an image based on an electron beam. In an image sensor with such multiple pixels, the sensitivity of each pixel may differ due to manufacturing errors, etc. Therefore, an electron microscope that can correct the different sensitivity of each pixel is desired. [Means for solving the problem]
[0005] One aspect of the electron microscope according to the present invention is an electron optical system that irradiates an electron beam onto a sample and forms an image using electrons that have transmitted through the sample; a camera including an image sensor having a plurality of sensor pixels, and configured to capture a frame image based on output values output from each of the plurality of sensor pixels when electrons are incident on the image sensor; a correction coefficient calculation unit that calculates a plurality of correction coefficients for correcting the sensitivities of the plurality of sensor pixels; Including, The correction coefficient calculation unit determining a mode of output values for each of the sensor pixels from a plurality of the frame images captured under conditions in which electrons incident on the image sensor follow a Poisson process; calculating an average mode by averaging the modes obtained for each of the sensor pixels; For each of the sensor pixels Dividing the mode by the average mode, The plurality of correction coefficients are calculated.
[0006] In such an electron microscope, the sensitivities of a plurality of sensor pixels having different sensitivities can be corrected.
[0007] One aspect of the calibration method according to the present invention is to an electron optical system that irradiates an electron beam onto a sample and forms an image using electrons that have transmitted through the sample; An image sensor having a plurality of sensor pixels, wherein electrons are incident on the image sensor. a camera that captures a frame image based on output values output from each of the plurality of sensor pixels when light is incident on the image sensor, A step of obtaining a mode of output values for each of the sensor pixels from a plurality of the frame images captured under conditions in which electrons incident on the image sensor follow a Poisson process; calculating an average mode by averaging the modes calculated for each of the sensor pixels; For each of the sensor pixels Dividing the mode by the average mode calculating a plurality of correction coefficients for correcting the sensitivities of the plurality of sensor pixels; Includes:
[0008] Such a calibration method can correct the sensitivities of a plurality of sensor pixels having different sensitivities. [Brief explanation of the drawings]
[0009] [Figure 1] FIG. 1 is a diagram showing the configuration of an electron microscope according to an embodiment of the present invention. [Figure 2] FIG. 1 is a diagram showing an example of the configuration of an imaging processing device. [Figure 3] 10 is a flowchart showing an example of the flow of image generation processing by an image processing unit. [Figure 4] FIG. 10 is a diagram for explaining blackout processing. [Figure 5] FIG. 10 is a diagram for explaining sensitivity correction processing. [Figure 6] FIG. 1 is a cross-sectional view schematically showing an image sensor. [Figure 7] A graph showing the amount of signal generated and its frequency when a single incident electron strikes any sensor pixel on the image sensor. [Figure 8] FIG. 10 is a diagram for explaining a counting process. [Figure 9] 10 is a flowchart showing an example of processing by a correction coefficient calculation unit. [Figure 10] A histogram of the output values of any sensor pixel. [Figure 11] FIG. 10 is a diagram showing an example of a mode table. [Figure 12] 10 is a flowchart showing an example of a dark image update process of the camera control unit. [Figure 13] 10 is a flowchart showing a modified example of the dark image update process of the camera control unit. [Figure 14] 10 is a flowchart showing a modified example of the dark image update process of the camera control unit. DETAILED DESCRIPTION OF THE INVENTION
[0010] Preferred embodiments of the present invention will be described in detail below with reference to the drawings. Note that the embodiments described below do not unduly limit the content of the present invention as defined in the claims. Furthermore, not all of the configurations described below are necessarily essential components of the present invention.
[0011] 1. Electron Microscopy First, an electron microscope according to one embodiment of the present invention will be described with reference to the drawings. Figure 1 is a diagram showing the configuration of an electron microscope 100 according to one embodiment of the present invention.
[0012] The electron microscope 100 includes an electron optical system 10 , a sample stage 20 , a camera 30 , an electron optical system control unit 40 , and an image processing device 50 .
[0013] The electron optical system 10 irradiates a sample S with an electron beam and forms an image using electrons that have transmitted through the sample S. The electron optical system 10 includes an electron source 12, an illumination system 14, an imaging system 16, and a fluorescent screen 18 that also functions as a shutter for the electron beam.
[0014] The electron source 12 emits an electron beam. The electron source 12 is, for example, an electron gun that accelerates electrons emitted from a cathode by an anode to emit an electron beam.
[0015] The irradiation system 14 irradiates the sample S with the electron beam emitted from the electron source 12. For example, the irradiation system 14 irradiates the sample S with a parallel beam. The irradiation system 14 includes a plurality of condenser lenses 140. The condenser lenses 140 focus the electron beam emitted from the electron source 12. Although not shown, the irradiation system 14 may include lenses and apertures other than the condenser lenses 140.
[0016] The imaging system 16 is an optical system for forming an image with the electron beam transmitted through the sample S. The imaging system 16 includes an objective lens 160, an intermediate lens 162, and a projection lens 164.
[0017] The objective lens 160 is the first lens used to form a TEM image (specimen image) using an electron beam transmitted through the specimen S. An electron diffraction pattern is formed on the back focal plane of the objective lens 160. The intermediate lens 162 focuses the TEM image or electron diffraction pattern formed by the objective lens 160 by changing the focal length. This allows the TEM image or electron diffraction pattern to be enlarged and formed on the object plane of the projection lens 164. The projection lens 164 enlarges the image (TEM image or electron diffraction pattern) formed by the intermediate lens 162 and forms the image on the fluorescent screen 18 and camera 30.
[0018] Although not shown, the imaging system 16 may include lenses other than the objective lens 160, the intermediate lens 162, and the projection lens 164, an aperture, and the like.
[0019] The fluorescent screen 18 visualizes the TEM image and electron diffraction pattern. Electrons collide with the fluorescent screen 18 to excite fluorescent materials, and the emitted visible light creates brightness and darkness corresponding to the intensity of the electrons. The fluorescent screen 18 is located in front of the camera 30. The fluorescent screen 18 also functions as a shutter for the electron beam. For example, when the camera chamber in which the camera 30 is located is closed by the fluorescent screen 18, the electron beam does not enter the camera 30. When the fluorescent screen 18 is flipped up to open the camera chamber, the electron beam enters the camera 30, allowing the camera 30 to capture the TEM image and electron diffraction pattern.
[0020] The sample stage 20 holds a sample S. The sample stage 20 is capable of tilting the sample S. The sample stage 20 includes a sample holder 22 and a goniometer 24. The sample holder 22 holds the sample S. The sample holder 22 is inserted into the goniometer 24. The goniometer 24 is capable of tilting and moving the sample S.
[0021] The camera 30 includes an image sensor 32 having a plurality of sensor pixels. The camera 30 is a direct detection camera that directly detects electrons with the image sensor 32. Examples of direct detection cameras include the K2 manufactured by Gatan, the K3 manufactured by Gatan, the Falcon 4 manufactured by Thermo Fisher Science, and the Direct Examples include the DE-64 manufactured by Electron.
[0022] Here, indirect detection cameras and direct detection cameras are known as cameras for electron microscopes. Indirect detection cameras convert electrons into light using a scintillator and detect the light using an image sensor. In contrast, direct detection cameras detect electrons directly using an image sensor 32 without using a scintillator. Direct detection cameras can reduce blurring caused by light spreading during the process of converting electrons into light using a scintillator, allowing for the acquisition of high-resolution images. Furthermore, direct detection cameras can obtain high contrast with a low dose of radiation. Therefore, an electron microscope 100 equipped with a direct detection camera is suitable for cryo-electron microscopy, which observes biological samples in a frozen state.
[0023] The camera 30 captures a frame image. The frame image has a plurality of image pixels that correspond one-to-one to the plurality of sensor pixels of the image sensor 32, and the pixel value of each of the plurality of image pixels has a value corresponding to the output value of the corresponding sensor pixel. The output value of a sensor pixel corresponds to the amount of signal (amount of charge) generated by electrons incident on the sensor pixel.
[0024] Note that multiple sensor pixels of the image sensor 32 are collectively regarded as one sensor pixel. That is, the pixel value of an image pixel may be a value corresponding to the output values of a plurality of sensor pixels regarded as one sensor pixel.
[0025] The camera 30 captures the TEM image or electron diffraction pattern formed on the image sensor 32 and outputs it as a frame image. A frame is the smallest unit of photography, and a frame image is an image obtained by capturing one frame. The camera 30 is capable of capturing, for example, 400 frames per second. In other words, the camera 30 can capture 400 frame images per second. The electron microscope 100 accumulates hundreds to thousands of frame images to generate a single image (TEM image or electron diffraction pattern).
[0026] The image sensor 32 is, for example, a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor, a CCD (Charge Coupled Device) image sensor, etc. By using a CMOS image sensor as the image sensor 32, frame images can be captured at a higher frame rate than when a CCD image sensor is used. In other words, by using a CMOS image sensor as the image sensor 32, the number of frame images that can be captured per unit time can be increased.
[0027] The electron-optical system control unit 40 controls the electron-optical system 10. By controlling the electron-optical system 10 with the electron-optical system control unit 40, it is possible to form a TEM image or an electron diffraction pattern. The electron-optical system control unit 40 includes, for example, a processing circuit such as a CPU (Central Processing Unit) or an FPGA (Field Programmable Gate Array), and a storage circuit such as a semiconductor memory. The electron-optical system control unit 40 performs various control processes by causing the processing circuit such as the CPU to execute programs stored in the storage circuit.
[0028] The image capture processing device 50 performs processes such as controlling the camera 30, image processing for frame images, calibration of the image sensor 32, and processing for acquiring dark images.
[0029] FIG. 2 is a diagram showing an example of the configuration of the imaging processing device 50. As shown in FIG.
[0030] As shown in FIG. 2, the imaging processing device 50 includes a processing unit 500, an operation unit 510, a display unit 520, and a storage unit 530.
[0031] The operation unit 510 is used by the user to input operation information, and outputs the input operation information to the processing unit 500. The functions of the operation unit 510 can be realized by input devices such as a keyboard, a mouse, buttons, a touch panel, and a touch pad.
[0032] The display unit 520 displays the image generated by the processing unit 500. The function of the display unit 520 can be realized by an LCD (Liquid Crystal Display), a touch panel display, or the like.
[0033] The storage unit 530 stores programs, data, etc. for the processing unit 500 to perform various calculation processes and control processes. The storage unit 530 is also used as a working area for the processing unit 500, and is also used to temporarily store calculation results, etc., executed by the processing unit 500 in accordance with the various programs. The functions of the storage unit 530 can be realized by a RAM (Random Access Memory), a ROM (Read Only Memory), a hard disk, etc.
[0034] The processing unit 500 performs processes such as controlling the camera 30, image processing for frame images, calibration of the image sensor 32, and processing for acquiring dark images. The functions of the processing unit 500 include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and a This can be realized by executing a program stored in the storage unit 530 using various processors such as a digital processing unit (DSP) or a digital signal processor (DSP). The processing unit 500 includes an image processing unit 502, a correction coefficient calculation unit 504, and a camera control unit 506.
[0035] The image processing unit 502 generates one image from multiple frame images captured by the camera 30. Here, the images generated are TEM images or electron diffraction pattern images. The image processing unit 502 performs blackout processing, sensitivity correction processing for correcting the sensitivity of each sensor pixel of the image sensor 32, counting processing, and integration processing on the multiple frame images to generate an image. Details of each processing will be described later.
[0036] The correction coefficient calculation unit 504 calculates a plurality of correction coefficients for correcting the sensitivities of a plurality of sensor pixels that constitute the image sensor 32. In the sensitivity correction process, the image processing unit 502 corrects the sensitivities of the plurality of sensor pixels of the image sensor 32 using the plurality of correction coefficients calculated by the correction coefficient calculation unit 504.
[0037] The camera control unit 506 controls the camera 30. The camera control unit 506 performs processing to acquire a dark image used, for example, in black subtraction processing. The dark image is an image captured when no electron beam is incident on the camera 30. The camera control unit 506 acquires control information for the electron optical system 10 from the electron optical system control unit 40, and controls the camera 30 based on the acquired control information to acquire the dark image. For example, the camera control unit 506 determines whether or not an electron beam is incident on the camera 30 based on the control information of the electron optical system 10, and when it is determined that no electron beam is incident on the camera 30, controls the camera 30 to acquire the dark image.
[0038] 2. Image Processing Unit FIG. 3 is a flowchart showing an example of the flow of image generation processing by the image processing unit 502.
[0039] The image processing unit 502 generates one image from multiple frame images captured by the camera 30. As shown in Fig. 3, the image processing unit 502 performs frame image acquisition processing S10, black subtraction processing S20, sensitivity correction processing S30, counting processing S40, and integration processing S50. This allows one image to be generated from multiple frame images. The following describes the case where a TEM image is captured by the camera 30 and an image is generated.
[0040] (1) Frame image acquisition process S10 In the electron optical system 10, the irradiation system 14 irradiates the sample S with an electron beam, and the imaging system 16 forms a TEM image on the image sensor 32 using electrons that have passed through the sample S. In this state, the camera control unit 506 causes the camera 30 to capture a preset number of frame images. As a result, the camera 30 outputs the set number of frame images. The output frame images are sent to the processing unit 500. Here, the description will be given assuming that the processing unit 500 has acquired M (M>2) frame images.
[0041] (2) Blackout processing S20 Next, the image processing unit 502 performs blackout subtraction processing S20 on each of the acquired M frame images. The blackout subtraction processing S20 is a process of subtracting a dark image from a frame image. By performing the blackout subtraction processing S20, regular noise in the image sensor 32 can be removed.
[0042] FIG. 4 is a diagram for explaining the black subtraction process S20.
[0043] 4, the image processing unit 502 subtracts the dark image 4 from the frame image 2. Specifically, the image processing unit 502 subtracts the corresponding pixel value of the image pixel 2a of the frame image 2 from the pixel value of the image pixel 2a. The pixel values of the image pixels 4a of the dark image 4 obtained by the black subtraction process S20 are subtracted from the pixel values of the image pixels 4a of the dark image 4 obtained by the black subtraction process S20. This allows the regular noise of the image sensor 32 to be removed from the frame image 2. By the black subtraction process S20, M frame images 2A can be obtained from the M frame images 2 from which the regular noise of the image sensor 32 has been removed. In the example shown in FIG. 4, the frame image 2 has 5×5 image pixels 2a, but the number of pixels in the frame image 2 is not particularly limited. For example, the frame image 2 may have 4000×4000 image pixels 2a.
[0044] (3) Sensitivity correction process S30 The image processing unit 502 performs sensitivity correction processing S30 for correcting the sensitivity of the sensor pixels on each of the M frame images 2A that have been subjected to black subtraction processing.
[0045] FIG. 5 is a diagram for explaining the sensitivity correction process S30.
[0046] The image processing unit 502 corrects the pixel value of each image pixel 2a in the frame image 2A using a correction coefficient. A sensitivity correction table 6 is stored in the storage unit 530. As shown in FIG. 5, the sensitivity correction table 6 is a table that stores correction coefficients calculated for each sensor pixel. In the sensitivity correction table 6, the coordinates of the sensor pixel are registered in association with the correction coefficients for correcting the sensitivity of the sensor pixel. In the example shown in FIG. 5, the sensitivity correction table 6 has a plurality of cells 6a that correspond one-to-one to the plurality of sensor pixels that make up the image sensor 32, and a correction coefficient is stored in each of the plurality of cells 6a.
[0047] The image processing unit 502 corrects the pixel value of each image pixel 2a in the frame image 2A using the correction coefficient stored in the corresponding cell 6a. For example, the pixel value of each image pixel 2a in the frame image 2A is divided by the correction coefficient stored in the corresponding cell 6a. By the sensitivity correction process S30, M frame images 2B in which the sensitivity of the sensor pixels has been corrected can be obtained from M frame images 2A.
[0048] (4) Counting process S40 Next, the image processing unit 502 performs a counting process S40 on each of the M frame images 2B for which the sensitivity of the sensor pixels has been corrected. First, the reason for performing the counting process S40 will be described below.
[0049] As described above, the camera 30 is a direct detection camera that directly detects electrons with the image sensor 32. FIG.
[0050] 6, the image sensor 32 includes a support layer 320, a wiring layer 322, and a sensory layer 324. The support layer 320 supports the wiring layer 322 and the sensory layer 324. The wiring layer 322 is disposed on the sensory layer 324. The wiring layer 322 includes stacked metal layers that form a plurality of wires, a plurality of vias, and the like. The wiring layer 322 also includes stacked insulating layers that provide insulation between the wires.
[0051] A plurality of photodiodes 325 are formed in the sensitive layer 324. The photodiodes 325 are isolated from each other by element isolation sections having an STI (shallow trench isolation) structure or a LOCOS (Local Oxidation of Silicon) structure. One photodiode 325 constitutes one sensor pixel 3.
[0052] The sensitive layer 324 is a semiconductor layer having a thickness of, for example, about 50 μm. When electrons are incident on the photodiode 325, electron-hole pairs are generated by the photoelectric effect. The image sensor 32 converts these electrons (or holes) into a voltage and reads it out as an electrical signal. Although not shown, each sensor pixel 3 has a built-in sensor (not shown) that amplifies the minute electrical signal generated in the photodiode 325. An amplifier is formed to amplify the electric signal generated by the photodiode 325. The electric signal generated by the photodiode 325 is extracted by a plurality of wires formed in the wiring layer 322. In the image sensor 32, the sensitive layer 324 is made thin to suppress the interaction between the electron beam and the semiconductor layer, thereby reducing noise.
[0053] FIG. 7 is a graph showing the amount of signal generated (amount of charge) and its frequency when one incident electron is incident on any sensor pixel 3 of the image sensor 32.
[0054] In one sensor pixel 3, the amount of signal generated by the photoelectric effect follows a Landau distribution, as shown in FIG. 7. This is because, by making the sensitive layer 324 thin, incident electrons pass through the sensitive layer 324 without completely losing their energy within the sensitive layer 324. For example, if the sensitive layer 324 is made of silicon, the thickness of the sensitive layer 324 is 50 μm or less, and the thickness of the wiring layer 322 is 10 μm or less, when electrons with an acceleration voltage of 100 kV or more are incident on the image sensor 32, the amount of signal generated by the photoelectric effect follows a Landau distribution. In other words, when the thickness of the sensitive layer 324 is 50 μm or less, the thickness of the wiring layer 322 is 10 μm or less, and the acceleration voltage is 100 kV or more, the output value of the sensor pixel 3 follows a Landau distribution.
[0055] Thus, in an image sensor 32 in which the output signals of each of the multiple sensor pixels 3 follow a Landau distribution, even if an image is generated by simply accumulating the frame image 2, the linearity between the pixel value of each image pixel 2a of the frame image 2 and the number of incident electrons is insufficient.
[0056] Therefore, in order to improve the linearity between the pixel value of each image pixel 2a of the frame image 2 and the number of incident electrons, the image processing unit 502 performs a counting process S40 on each of the M frame images 2B. In the counting process S40, the frame image 2B is binarized and the incident electrons are counted.
[0057] 8 is a diagram illustrating the counting process S40. For example, if the threshold is set to 140, when the pixel value of each image pixel 2a in the frame image 2B is greater than 140, the pixel value is set to "1," and when the pixel value is 140 or less, the pixel value is set to "0." This makes it possible to obtain a binarized frame image 2C. Here, the threshold is set to a value that is greater than noise and small enough to exclude noise. This reduces the possibility of counting noise as incident electrons or of overcounting incident electrons.
[0058] In the frame image 2C, the image pixel 2a corresponding to the sensor pixel 3 into which an electron is incident is represented by "1," and the image pixel 2a corresponding to the sensor pixel 3 into which no electron is incident is represented by "0." In this way, by performing the counting process S40, it is possible to know the number of electrons incident on the image sensor 32 per frame and the positions of the sensor pixels 3 into which the electrons are incident.
[0059] (5) Accumulation process S50 The image processing unit 502 generates a TEM image by integrating the binarized M frame images 2C. The image processing unit 502 integrates the pixel values of the corresponding image pixels 2a in the M frame images 2C.
[0060] Through the above processing, a TEM image with high linearity between pixel values and the number of incident electrons can be generated from multiple frame images 2. Image processing unit 502 displays the generated TEM image on display unit 520, and the image generation processing ends.
[0061] 3. Image sensor sensitivity correction 3.1. Sensor pixel sensitivity In the image sensor 32, the sensitivity differs for each sensor pixel 3. The image sensor 32 has an amplifier for each sensor pixel 3, and one of the factors that causes the sensitivity to differ is variation in the characteristics of the amplifier due to manufacturing errors, etc.
[0062] When the sensitivity differs for each sensor pixel 3 in this way, a relative difference occurs between the sensor pixels 3 in the Landau distribution indicated by the output signal of each sensor pixel 3. This relative difference in sensitivity affects the counting process S40.
[0063] For example, if the sensitivity of the target sensor pixel 3 is lower than the average sensitivity of all sensor pixels 3 constituting the image sensor 32, the amount of signal obtained from incident electrons in the target sensor pixel 3 decreases relatively. Therefore, even if electrons are incident on the target sensor pixel 3, they may be determined to be below the threshold in the counting process S40 and not be counted as incident electrons, i.e., there is a possibility of counting errors. Also, if the sensitivity of the target sensor pixel 3 is higher than the average sensitivity of all sensor pixels 3 constituting the image sensor 32, the amount of signal due to noise increases, and electrons may be counted as incident electrons even though they are not incident, i.e., there is a possibility of miscounting.
[0064] Therefore, by correcting the sensitivities of a plurality of sensor pixels 3 having different sensitivities, the accuracy of the counting process S40 can be improved.
[0065] As a calibration method for correcting sensitivity, for example, in the case of a CMOS image sensor intended to detect visible light, one method is to obtain the output value of each sensor pixel using uniform illumination, and then calculate a normalization coefficient for each sensor pixel so that the output value of each sensor pixel is uniform among the sensor pixels, thereby obtaining a correction coefficient. However, in the image sensor 32, the signal amount obtained from incident electrons follows a Landau distribution, so the correction coefficient cannot be calculated using this method.
[0066] 3.2. Sensor pixel sensitivity calibration method FIG. 9 is a flowchart showing an example of the process of the correction coefficient calculation unit 504.
[0067] First, the correction coefficient calculation unit 504 acquires a plurality of frame images 2 captured under conditions in which electrons incident on the image sensor 32 follow a Poisson process (S100).
[0068] To capture the frame image 2, first, the electron optical system 10 is adjusted so that the electrons incident on the image sensor 32 follow a Poisson process. Specifically, an electron beam is irradiated into a vacuum region where the sample S is not present, and the electron optical system 10 is adjusted to achieve a parallel irradiation condition in which the electron beam is uniformly irradiated onto the image sensor 32. In this state, the electron optical system 10 is adjusted so that the average and variance of the number of electrons incident on each sensor pixel 3 per frame are equal. Furthermore, the average number of electrons incident on each sensor pixel 3 per frame is set to be less than one. The average number of electrons incident on each sensor pixel 3 per frame is preferably 0.1 or less, i.e., 0.1 e / pixel / frame or less. By adjusting the electron optical system 10, the number of electrons incident on each sensor pixel 3 per frame can be adjusted. By irradiating the image sensor 32 with electrons under these conditions, a Poisson process is established.
[0069] It is assumed here that electrons incident on one sensor pixel 3 of the image sensor 32 do not enter the adjacent sensor pixel 3.
[0070] Next, the electrons incident on the image sensor 32 are subjected to a Poisson process. Electrons are irradiated onto the sensor 32, and a preset number of frame images 2 are captured by the camera 30. For example, several hundred to several thousand frame images 2 are captured. The greater the number of frame images 2, the more statistical fluctuations can be reduced. Here, the explanation will be given assuming that N (N>2) frame images 2 are acquired.
[0071] The above steps allow N frame images 2 to be captured. The N frame images 2 captured by the camera 30 are sent to the image capture processing device 50. As a result, the correction coefficient calculation unit 504 can acquire the N frame images 2.
[0072] The process of capturing the above-described N frame images 2 is performed automatically by the camera control unit 506 controlling the electron optical system control unit 40 and the camera 30. Note that the user may also capture the N frame images 2 by operating the electron microscope 100.
[0073] Furthermore, in the process S100 for acquiring N frame images 2 described above, the value of each image pixel 2a in the frame images 2 is a pixel value, but the value of each image pixel 2a in the frame images 2 may also be a voltage value. In other words, the output value of the sensor pixel 3 may be a pixel value or a voltage value.
[0074] Next, the correction coefficient calculation unit 504 acquires information on the output value for each sensor pixel 3 from the acquired N frame images 2, and creates a histogram of the output values for each sensor pixel 3 (S102).
[0075] The correction coefficient calculation unit 504 extracts the pixel values of the image pixels 2a at the same coordinates from each of the N frame images 2. As a result, N pixel values are obtained for each image pixel 2a at the same coordinates. The pixel values of the image pixels 2a have values that correspond to the output values of the corresponding sensor pixels 3. Therefore, N output values are obtained for each sensor pixel 3 from the N frame images 2. In other words, N output values are sampled for each sensor pixel 3.
[0076] The correction coefficient calculation unit 504 creates a histogram for each sensor pixel 3 from the information on the output values acquired for each sensor pixel 3 .
[0077] Fig. 10 is a histogram of the output values of an arbitrary sensor pixel 3. In the histogram of the output values of the sensor pixel 3 shown in Fig. 10, the horizontal axis represents the output value of the sensor pixel 3, and the vertical axis represents the frequency.
[0078] Next, the correction coefficient calculation unit 504 calculates the mode of the output values from the histogram (S104). The mode of the output values is the peak position of the histogram. The mode calculated from the histogram of the output values of an arbitrary sensor pixel 3 shown in FIG. 10 was 876. The correction coefficient calculation unit 504 finds the mode for each sensor pixel 3 from the histogram created for each sensor pixel 3.
[0079] The correction coefficient calculation unit 504 creates a mode table 8 by associating the obtained mode with the positions of the sensor pixels 3 .
[0080] 11 is a diagram showing an example of the mode table 8. The mode table 8 has a plurality of cells 8a corresponding to a plurality of sensor pixels 3. The mode calculated for each sensor pixel 3 is stored in the cell 8a at the coordinates corresponding to the sensor pixel 3 from which the mode was obtained.
[0081] Next, the correction coefficient calculation unit 504 averages the modes calculated for each sensor pixel 3 to calculate an average mode (S106).
[0082] The correction coefficient calculation unit 504 calculates the average mode by dividing the sum of all modes stored in the mode table 8 by the number of sensor pixels 3 (cells 8a). The average mode calculated from the mode table 8 shown in FIG. 11 was 873.76.
[0083] Next, the correction coefficient calculation unit 504 divides the mode calculated for each sensor pixel 3 by the average mode to calculate a plurality of correction coefficients (S108).
[0084] The mode stored in each cell 8a of the mode table 8 is divided by the average mode. This allows the creation of the sensitivity correction table 6 shown in Fig. 5. The sensitivity correction table 6 has a plurality of cells 6a that correspond one-to-one to the plurality of sensor pixels 3 that make up the image sensor 32. Each cell 6a stores a correction coefficient for correcting the output value output from the corresponding sensor pixel 3.
[0085] The correction coefficient calculation unit 504 ends the process after creating the sensitivity correction table 6. As described above, in the sensitivity correction process S30 shown in Fig. 3, the sensitivity of each sensor pixel 3 is corrected using the sensitivity correction table 6. This allows the sensitivity of each sensor pixel 3 to be calibrated.
[0086] 4. Acquiring dark images 4.1. Dark images In the blackout process S20, a dark image 4 is used. The dark image 4 is an image captured when no electron beam is incident on the camera 30. Here, the output value of the sensor pixel 3 is offset. For example, if the offset is 60, the output value of the sensor pixel 3 when no electron beam is incident on the camera 30 will be 60. In the camera 30, the image sensor 32 directly detects electrons, so the image sensor 32 will be damaged by the electron beam. If noise increases due to this damage, the output value of the image sensor 32 will also increase by the amount of the noise. For example, if the offset is 60 and the output value increased by noise is 50, the output value of the sensor pixel 3 when no electron beam is incident on the camera 30 will be 110.
[0087] In this way, since the output value of the sensor pixel 3 changes due to electron beam damage, it is desirable to update the dark image 4 used in the black subtraction process S20. In the electron microscope 100, the dark image 4 can be updated automatically.
[0088] Specifically, in the electron microscope 100, the camera control unit 506 acquires control information for the electron optical system 10 from the electron optical system control unit 40, and controls the camera 30 based on the acquired control information to acquire the dark image 4. The camera control unit 506 determines whether or not electrons are incident on the camera 30 based on the control information for the electron optical system 10, and if it determines that electrons are not incident on the camera 30, controls the camera 30 to acquire the dark image 4.
[0089] Furthermore, if the image sensor 32 is damaged by the electron beam and noise increases, the accuracy of the counting process S40 will decrease. Therefore, in the electron microscope 100, the camera control unit 506 determines the degree of damage to the image sensor 32 based on the dark image 4, and notifies the user to replace the image sensor 32 depending on the determination result.
[0090] 4.2. Dark image update process FIG. 12 is a flowchart showing an example of the dark image update process of the camera control unit 506.
[0091] First, the camera control unit 506 receives control information for the electron optical system 10 from the electron optical system control unit 40. The control information of the electron-optical system 10 includes information on the status of each part constituting the electron-optical system 10. The electron-optical system control unit 40 and the image capture processing device 50 are connected to each other so that they can communicate with each other via, for example, a serial cable. The electron-optical system control unit 40 sends the control information of the electron-optical system 10 to the image capture processing device 50 in response to a request from, for example, a camera control unit 506.
[0092] The camera control unit 506 determines whether electrons are incident on the camera 30 based on the control information of the electron optical system 10 (S202). The camera control unit 506 determines that electrons are not incident on the camera 30 when, for example, no electron beam is emitted from the electron source 12, the fluorescent screen 18 is closed, or a blanking device (not shown) of the electron source 12 blocks the electron beam. These states can be known from the control information of the electron optical system 10.
[0093] If the camera control unit 506 determines that electrons are incident on the camera 30 (Yes in S202), it returns to step S200 and acquires control information for the electro-optical system 10 (S200). The camera control unit 506 repeats step S200 for acquiring control information for the electro-optical system 10 and the determination step S202 until it determines that electrons are not incident on the camera 30.
[0094] If the camera control unit 506 determines that no electrons are incident on the camera 30 (No in S202), it controls the camera 30 to acquire a dark image 4 (S204). The camera control unit 506 causes the camera 30 to capture a frame image 2 in a state where no electrons are incident on the camera 30. This makes it possible to acquire a dark image 4. The dark image 4 may be a single frame image 2 captured in a state where no electrons are incident on the camera 30, or may be an image obtained by averaging multiple frame images 2 captured in a state where no electrons are incident on the camera 30.
[0095] The camera control unit 506 stores the acquired dark image 4 in the storage unit 530 as the dark image 4 for the black subtraction process S20 (S206).
[0096] The camera control unit 506 determines whether a predetermined time has elapsed since the dark image 4 was acquired (S208). Here, the predetermined time is the time from when the dark image 4 was acquired until the next dark image 4 is acquired. The predetermined time is set in advance. The predetermined time may be, for example, 24 hours or 168 hours. The user may be able to set the predetermined time as desired. The camera control unit 506 waits until the predetermined time has elapsed since the dark image 4 was acquired in process S204 (No in S208).
[0097] If the camera control unit 506 determines that the predetermined time has elapsed (Yes in S208), it acquires control information for the electro-optical system 10 from the electro-optical system control unit 40 (S210). Then, the camera control unit 506 determines whether electrons are incident on the camera 30 based on the control information for the electro-optical system 10 (S212).
[0098] If the camera control unit 506 determines that electrons are incident on the camera 30 (Yes in S212), it returns to step S210 and acquires control information for the electro-optical system 10 (S210). The camera control unit 506 repeats step S210 for acquiring control information for the electro-optical system 10 and the determination step S212 until it determines that electrons are not incident on the camera 30.
[0099] When it is determined that electrons are not incident on the camera 30 (No in S212), the camera control unit 506 controls the camera 30 to acquire a dark image 4 (S214).
[0100] The process S210 for acquiring control information for the electron optical system 10, the process S212 for determining whether electrons are incident, and the process S214 for acquiring the dark image 4 are all processes S200. , is performed in the same manner as in processes S202 and S204. In the following, the dark image 4 newly acquired in process S214 is referred to as a new dark image 4A, and the dark image 4 stored in the storage unit 530 as the dark image 4 for the black subtraction process S20 is referred to as an existing dark image 4B.
[0101] Next, the camera control unit 506 compares the new dark image 4A with the existing dark image 4B to determine whether the pixel values of the multiple image pixels 4a in the new dark image 4A have increased due to electron beam damage (S216).
[0102] For example, the camera control unit 506 compares the average value (average pixel value) of the pixel values of the multiple image pixels 4a in the new dark image 4A with the average value (average pixel value) of the pixel values of the multiple image pixels 4a in the existing dark image 4B. If the average pixel value of the new dark image 4A is greater than the average pixel value of the existing dark image 4B, the camera control unit 506 determines that the pixel value has increased due to electron beam damage.
[0103] When the camera control unit 506 determines that the pixel value has increased due to electron beam damage (Yes in S216), it stores the new dark image 4A in the storage unit 530 as the dark image 4 for the blackout process S20 (S222). At this time, the existing dark image 4B stored in the storage unit 530 is erased. In this way, the dark image 4 for the blackout process S20 is updated.
[0104] Next, the camera control unit 506 determines whether the average pixel value of the dark image 4 stored in the storage unit 530 is greater than a threshold value (S220). The threshold value may be set in advance, or may be set to any value by the user.
[0105] When the camera control unit 506 determines that the average pixel value of the dark image 4 is greater than the threshold value (Yes in S220), it notifies the user to replace the image sensor 32 (S222).
[0106] For example, the camera control unit 506 displays a message on the display unit 520 prompting the user to replace the image sensor 32. Note that the notification method is not limited to notification by message, and notification may be made using sound, vibration, light, or the like.
[0107] If the camera control unit 506 determines that the pixel value has not increased due to electron beam damage (No in S216), if it determines that the average pixel value of the dark image 4 is not greater than the threshold value (No in S220), or after the notification process S222, it determines whether the user has issued an instruction to end the dark image update process (S224). For example, if the user has input an instruction to end the dark image update process via the operation unit 510, the camera control unit 506 determines that the user has issued an instruction to end.
[0108] If the camera control unit 506 determines that the user has not issued an end instruction (No in S224), it returns to step S208 and determines whether a predetermined time has passed since the dark image 4 was acquired (S208). The camera control unit 506 waits until a predetermined time has passed since the dark image 4 was acquired in step S214 (No in S208).
[0109] In this way, the camera control unit 506 repeats the steps S208, S210, S212, S214, S216, S218, S220, S222, and S224 until it is determined that the user has issued an instruction to end the process.
[0110] If the camera control unit 506 determines that the user has issued an instruction to end the process (Yes in S224), the camera control unit 506 ends the dark image update process.
[0111] 5. Effects The electron microscope 100 includes an electron optical system 10 that irradiates a sample S with an electron beam and forms an image with electrons that have transmitted through the sample S, a camera 30 that includes an image sensor 32 having a plurality of sensor pixels 3 and captures frame images 2 based on output values output from each of the plurality of sensor pixels 3 when electrons are incident on the image sensor 32, and a correction coefficient calculation unit 504 that calculates a plurality of correction coefficients for correcting the sensitivity of the plurality of sensor pixels 3. The correction coefficient calculation unit 504 also obtains the most frequent value of the output values for each sensor pixel 3 from the plurality of frame images 2 captured under conditions where the electrons incident on the image sensor 32 follow a Poisson process, and calculates a plurality of correction coefficients based on the most frequent value obtained for each sensor pixel 3.
[0112] Therefore, the sensitivity of a plurality of sensor pixels 3 having different sensitivities can be corrected in the electron microscope 100. This can improve the accuracy of the counting process S40.
[0113] In the electron microscope 100, the correction coefficient calculation unit 504 calculates an average mode by averaging the modes found for each sensor pixel 3, and calculates multiple correction coefficients by dividing the mode by the average mode for each sensor pixel 3. Therefore, in the electron microscope 100, even in the case of an image sensor 32 in which the output values output from each of the multiple sensor pixels 3 in response to electrons incident on the image sensor 32 follow a Landau distribution, multiple correction coefficients can be calculated to correct the sensitivities of multiple sensor pixels 3 that have different sensitivities.
[0114] In the electron microscope 100, the camera 30 is a direct detection camera that directly detects electrons with an image sensor 32. Therefore, the electron microscope 100 can acquire a high-resolution TEM image.
[0115] The electron microscope 100 includes an electron optical system control unit 40 that controls the electron optical system 10 and a camera control unit 506 that controls the camera 30, and the camera control unit 506 acquires control information for the electron optical system 10 from the electron optical system control unit 40, controls the camera 30 based on the acquired control information, and acquires the dark image 4. Therefore, the electron microscope 100 can automatically acquire the dark image 4.
[0116] In the electron microscope 100, the camera control unit 506 determines whether or not electrons are incident on the camera 30 based on the control information of the electron optical system 10, and if it determines that electrons are not incident on the camera 30, it controls the camera 30 to acquire the dark image 4. Therefore, in the electron microscope 100, the dark image 4 can be acquired automatically.
[0117] The method for calibrating the image sensor 32 in the electron microscope 100 includes the steps of: determining the mode of output values for each sensor pixel 3 from multiple frame images 2 captured under conditions in which electrons incident on the image sensor 32 follow a Poisson process; and calculating multiple correction coefficients for correcting the sensitivities of the multiple sensor pixels 3 based on the mode determined for each sensor pixel 3. This makes it possible to correct the sensitivities of multiple sensor pixels 3 that have different sensitivities from one another. This improves the accuracy of the counting process S40.
[0118] 6. Variations 6.1. First Variant In the above embodiment, it has been described that electrons incident on one sensor pixel 3 of the image sensor 32 do not intrude into adjacent sensor pixels 3, but there are cases where electrons incident on one sensor pixel 3 intrude into other adjacent sensor pixels 3. In this case, for example, in the process S100 for acquiring frame images 2 shown in FIG. 9, the number of frame images 2 to be acquired is increased to increase the number of samplings of output values. This makes it possible to reduce the influence of electrons incident on one sensor pixel 3 intruding into other adjacent sensor pixels 3. It can be reduced.
[0119] 6.2. Second Variant In the above-described embodiment, it has been explained that electrons incident on one sensor pixel 3 of the image sensor 32 do not penetrate into adjacent sensor pixels 3, but there are cases in which electrons incident on one sensor pixel 3 penetrate into other adjacent sensor pixels 3.
[0120] In this case, the number of electrons incident on the image sensor 32 does not match the number of electrons identified in the frame image 2. Therefore, processing is performed to match the number of electrons incident on the image sensor 32 and the number of electrons identified in the frame image 2. For example, one image pixel 2a of interest and multiple image pixels 2a adjacent to that one image pixel 2a are grouped together, the center of gravity position is calculated from the pixel values of each image pixel 2a, and the image pixel 2a that overlaps with the center of gravity position is set as the image pixel 2a corresponding to the sensor pixel 3 into which the electrons were incident. In this way, the sensor pixel 3 into which the electrons were incident may be identified using a grouping method that groups multiple image pixels 2a into one group.
[0121] 6.3. Third Variant FIG. 13 is a flowchart showing a modified example of the dark image update process of the camera control unit 506.
[0122] 12, the camera control unit 506 compared the new dark image 4A with the existing dark image 4B to determine whether the pixel values of the multiple image pixels 4a in the new dark image 4A had increased due to electron beam damage (S216). That is, in the dark image update process shown in FIG. 12, the dark image 4 was updated when the pixel values had increased due to electron beam damage.
[0123] 13, the determination process S216 does not have to be performed. That is, after a new dark image 4A is acquired in process S214, the new dark image 4A is always stored in the storage unit 530 as the dark image 4 for the blackout process S20, and the existing dark image 4B is deleted from the storage unit 530. In this way, in the dark image update process, the latest dark image 4 may always be used as the dark image 4 for the blackout process S20.
[0124] 6.4. Fourth Variant FIG. 14 is a flowchart showing a modified example of the dark image update process of the camera control unit 506.
[0125] 12 described above, the camera control unit 506 performed the process S208 of determining whether a predetermined time has elapsed since acquiring the dark image 4. That is, in the dark image update process shown in Fig. 12, when it was determined that the predetermined time had elapsed (Yes in S208) and when it was determined that electrons were not incident on the camera 30 (No in S212), the dark image 4 was acquired (S214).
[0126] 14, the camera control unit 506 performs a process S209 to determine whether or not the user has given an instruction to start acquiring the dark image 4. That is, in the dark image update process shown in Fig. 13, if it is determined that the user has given an instruction to start acquiring the dark image 4 (Yes in S209) and if it is determined that electrons are not incident on the camera 30 (No in S212), the dark image 4 is acquired (S214).
[0127] For example, when the user inputs an instruction to start acquiring the dark image 4 via the operation unit 510, the camera control unit 506 determines that the user has issued an instruction to start acquiring the dark image 4.
[0128] The above-described embodiment and modifications are merely examples, and the present invention is not limited to these. For example, the embodiments and modifications can be combined as appropriate.
[0129] The present invention is not limited to the above-described embodiments, and various modifications are possible. For example, the present invention includes configurations that are substantially identical to the configurations described in the embodiments. A substantially identical configuration means, for example, a configuration with the same function, method, and result, or a configuration with the same purpose and effect. The present invention also includes configurations in which non-essential parts of the configurations described in the embodiments are replaced. The present invention also includes configurations that achieve the same effects or purposes as the configurations described in the embodiments. The present invention also includes configurations in which publicly known technology is added to the configurations described in the embodiments. [Explanation of symbols]
[0130] 2...frame image, 2A...frame image, 2B...frame image, 2C...frame image, 2a...image pixel, 3...sensor pixel, 4...dark image, 4A...new dark image, 4B...existing dark image, 4a...image pixel, 6...sensitivity correction table, 6a...cell, 8...mode table, 8a...cell, 10...electron optical system, 12...electron source, 14...illumination system, 16...imaging system, 18...fluorescent screen, 20...specimen stage, 22...specimen holder, 24...goniometer, 30 ...camera, 32...image sensor, 40...electron optical system control unit, 50...imaging processing device, 100...electron microscope, 140...condenser lens, 160...objective lens, 162...intermediate lens, 164...projection lens, 320...support layer, 322...wiring layer, 324...sensitive layer, 325...photodiode, 500...processing unit, 502...image processing unit, 504...correction coefficient calculation unit, 506...camera control unit, 510...operation unit, 520...display unit, 530...storage unit
Claims
1. an electron optical system that irradiates an electron beam onto a sample and forms an image using electrons that have transmitted through the sample; a camera including an image sensor having a plurality of sensor pixels, and configured to capture a frame image based on output values output from each of the plurality of sensor pixels when electrons are incident on the image sensor; a correction coefficient calculation unit that calculates a plurality of correction coefficients for correcting the sensitivities of the plurality of sensor pixels; Including, The correction coefficient calculation unit determining a mode of output values for each of the sensor pixels from a plurality of the frame images captured under conditions in which electrons incident on the image sensor follow a Poisson process; calculating an average mode by averaging the modes obtained for each of the sensor pixels; The electron microscope calculates the plurality of correction coefficients by dividing the mode by the average mode for each sensor pixel.
2. In claim 1, The image sensor is an electron microscope, wherein output values output from each of the plurality of sensor pixels when electrons are incident on the image sensor follow a Landau distribution.
3. In claim 2, The electron microscope, wherein the camera is a direct detection camera that directly detects electrons with the image sensor.
4. In any one of claims 1 to 3, an electron optical system control unit that controls the electron optical system; a camera control unit that controls the camera; Including, The camera control unit acquiring control information for the electron optical system from the electron optical system control unit; The electron microscope controls the camera based on the acquired control information to acquire a dark image.
5. In claim 4, The camera control unit determining whether electrons are incident on the camera based on the control information; When it is determined that no electrons are incident on the camera, the electron microscope controls the camera to acquire the dark image.
6. an electron optical system that irradiates an electron beam onto a sample and forms an image using electrons that have transmitted through the sample; A method for calibrating an image sensor in an electron microscope, the method including: an image sensor having a plurality of sensor pixels; and a camera that captures a frame image based on output values output from each of the plurality of sensor pixels when electrons are incident on the image sensor, the method comprising: A step of obtaining a mode of output values for each of the sensor pixels from a plurality of the frame images captured under conditions in which electrons incident on the image sensor follow a Poisson process; calculating an average mode by averaging the modes calculated for each of the sensor pixels; calculating a plurality of correction coefficients for correcting the sensitivity of the plurality of sensor pixels by dividing the mode by the average mode for each of the sensor pixels; A calibration method including:
Citation Information
Patent Citations
Sensitivity unevenness correction method and device of camera for transmission electron microscope
JP2011003336A
Energy ray detector, detection device, and equipment
JP2022002317A