Signal processing circuit, light detection device, and signal processing method

Abstract

A signal processing circuit according to the present invention comprises a processing unit that: has a photoelectric surface that emits electrons in response to incident light; converts, into a digital signal at a prescribed sampling frequency, a target signal corresponding to an output signal from a vacuum tube sensor that outputs an output signal corresponding to the amount of incident light; and derives an output value for each prescribed measurement period. The processing unit is configured such that when deriving the output value of a measurement period, the processing unit can execute an abnormal value handling process in which the number of pieces of data corresponding to the pulse width of an abnormal value signal appearing in the target signal are excluded in descending order of the signal value from a plurality of pieces of data included in the target signal in the measurement period, and the output value is derived from the remaining plurality of pieces of data.

Description

Signal processing circuit, optical detection device, and signal processing method

[0001] The present disclosure relates to a signal processing circuit, an optical detection device, and a signal processing method.

[0002] As an optical sensor, there is a vacuum tube sensor that has a photocathode that emits electrons in response to incident light and multiplies and detects the electrons emitted from the photocathode.

[0003] Japanese Patent Application Laid-Open No. 2015-141705

[0004] It is conceivable to use a vacuum tube sensor as an optical detection unit in, for example, a laser scanning microscope. In that case, the inventors have found that, due to various noise components, an abnormal value having an output larger than the normal value due to signal light is detected, and it may be difficult to use the information when an abnormal output value is detected in the acquired image.

[0005] On the other hand, as a technique related to noise removal, for example, there is one described in Patent Document 1. In the method described in Patent Document 1, pixels in which noise has occurred in the acquired X-ray image are specified, and the values of the pixels are replaced with alternative values calculated from the values of the pixels around the pixels or alternative values calculated from the values of the pixels acquired at the previous and subsequent times. However, in the method described in Patent Document 1, data configured as image data is processed as described above and reconfigured into an image. Therefore, there has been a problem particularly in cases where high-speed processing for noise is required, such as real-time observation.

[0006] Therefore, an object of the present disclosure is to provide a signal processing circuit, an optical detection device, and a signal processing method capable of high-speed processing for an event indicating an abnormal value.

[0007] The signal processing circuit of the present disclosure is a signal processing circuit comprising: [1] "a processing circuit that has a photocathode that emits electrons in response to incident light and outputs an output signal corresponding to the amount of light of the incident light from a vacuum tube sensor, which converts a target signal corresponding to the output signal from the vacuum tube sensor into a digital signal at a predetermined sampling frequency and derives an output value for each predetermined measurement period, wherein the processing unit is configured to perform an abnormal value handling process when deriving the output value for the measurement period, which excludes a number of data corresponding to the pulse width of an abnormal value signal appearing in the target signal from a plurality of data included in the target signal during the measurement period, in descending order of signal value, and derives the output value from the remaining plurality of data."

[0008] In this signal processing circuit, the processing unit is configured to perform anomaly handling processing when deriving the output value during the measurement period. This involves excluding a number of data points corresponding to the pulse width of the abnormal signal appearing in the target signal from multiple data points included in the target signal during the measurement period, in descending order of signal value, and deriving the output value from the remaining data points. This allows for the deriving of the output value during the measurement period after performing anomaly handling processing as needed. In other words, because the handling of events indicating abnormal values ​​is performed at the level of numerical data (output value) rather than image data, high-speed processing is possible. This enables high-speed processing of events indicating abnormal values.

[0009] The signal processing circuit of the present disclosure is [2] "a signal processing circuit comprising a processing unit that converts a target signal corresponding to the output signal from a vacuum tube sensor having a photocathode that emits electrons in response to incident light and outputs an output signal corresponding to the amount of light of the incident light into a digital signal at a predetermined sampling frequency and derives an output value for each predetermined measurement period, wherein the processing unit is configured to perform abnormal value handling processing when deriving the output value for the measurement period, by excluding a number of consecutive data, including data corresponding to the maximum signal value, from a plurality of data included in the target signal for the measurement period, based on a predetermined set ratio which is the ratio of the number of sampling points before and after the sampling point corresponding to the maximum signal value, and deriving the output value from the remaining data among the plurality of data."

[0010] In this signal processing circuit, the processing unit is configured to perform anomaly handling processing when deriving the output value during the measurement period. This involves excluding a predetermined number of consecutive data points, including the data corresponding to the maximum signal value, from the multiple data points included in the target signal during the measurement period, and deriving the output value from the remaining data points. This allows for the deriving of the output value during the measurement period after performing anomaly handling processing as needed. In other words, because the handling of anomalies is performed at the numerical data level of the output value rather than image data, high-speed processing is possible. Furthermore, by excluding a predetermined number of consecutive data points, including the data corresponding to the maximum signal value, the exclusion of non-anomalous signal values ​​can be suppressed. Therefore, the output value during the measurement period can be derived with high accuracy.

[0011] The signal processing circuit of the present disclosure includes [3] "a current signal corresponding to the amount of incident light with a predetermined cutoff frequency f ｃ A current-to-voltage conversion unit converts the voltage signal to a current-to-voltage signal, and the sampling frequency S ｒ The system further comprises an AD converter that converts the signal to a digital signal, and the number of signals corresponding to the pulse width of the abnormal value signal is AS ｒ / f ｃ (A is a constant between 1 and 4), and may be the signal processing circuit described in [1]. Alternatively, the signal processing circuit of the present disclosure may be [4] "a current signal corresponding to the amount of incident light with a predetermined cutoff frequency f ｃ A current-to-voltage conversion unit converts the voltage signal to a current-to-voltage signal, and the sampling frequency S ｒ The system further comprises an AD converter that converts the data into a digital signal, and the number of consecutive data is AS ｒ / f ｃ (A is a constant between 1 and 4), and the signal processing circuit described in [2] may also be used. In this case, abnormal value handling processing can be performed appropriately.

[0012] The signal processing circuit of the present disclosure is described in [5] as follows: "When deriving the output value during the measurement period, if the first value based on the maximum value of the target signal during the measurement period is the number of electrons P emitted from the photoelectric surface when the incident light corresponding to the abnormal value signal is incident on the photoelectric surface" enoise and the fluctuation σ of the number of electrons, and the pulse height V of the signal that appears in the target signal when one photoelectron is emitted from the photoelectric surface hsingle If it is equal to or greater than the second value based on these, the abnormal value corresponding process is executed. If the first value is smaller than the second value, the derivation process for deriving the output value from the plurality of data during the measurement period is executed without executing the abnormal value corresponding process. The signal processing circuit according to any one of [1] to [4] may be used. In this case, when an event indicating an abnormal value occurs during the measurement period, the abnormal value corresponding process is executed. When an event indicating an abnormal value does not occur, the derivation process for deriving the output value from the data during the measurement period can be executed without executing the abnormal value corresponding process.

[0013] The signal processing circuit of the present disclosure is described in [6] as follows: "The first value is a value obtained by subtracting any one value of the minimum value of the target signal during the measurement period, the average value of the remaining target signals excluding the maximum value, and the median value of the target signal during the measurement period from the maximum value of the target signal during the measurement period, or the maximum value. The signal processing circuit according to [5] may be used. In this case, it is possible to suitably determine whether an event indicating an abnormal value has occurred during the measurement period.

[0014] The signal processing circuit of the present disclosure is described in [7] as follows: "The second value is based on V hsingle (P enoise -mσ) (m is 2 or more). The signal processing circuit according to [5] or [6] may be used. In this case, it is possible to suitably determine whether an event indicating an abnormal value has occurred during the measurement period.

[0015] The signal processing circuit of the present disclosure may also be the signal processing circuit according to any one of [1] to [7], wherein the vacuum tube sensor further comprises an avalanche diode that multiplies electrons from the photocathode. Since such a vacuum tube sensor uses a solid element such as an avalanche diode, it becomes easier to appropriately perform the above-mentioned abnormal value handling processing.

[0016] The signal processing circuit of the present disclosure may also be [9] "a current-voltage conversion unit that further converts a current signal corresponding to the amount of incident light into a voltage signal at a predetermined cutoff frequency, wherein the cutoff frequency is set such that the pulse width of the voltage signal indicated by the abnormal value signal is less than half of the measurement period, as described in any of [1] to [8]." In this case, the number of data to be removed can be reduced, so that the output value can be derived with higher accuracy.

[0017] The optical detection device of the present disclosure is

[10] "an optical detection device comprising the vacuum tube sensor and a signal processing circuit as described in any of [1] to [9]". This optical detection device makes it possible to suppress the impact on time response characteristics, improve real-time response to events showing abnormal values ​​and data accuracy, and remove high-output noise.

[0018] The light detection device of the present disclosure may also be the light detection device according to

[10] , wherein the vacuum tube sensor further comprises an avalanche diode that multiplies electrons from the photocathode. In such a vacuum tube sensor, a solid element such as an avalanche diode is used, making it easier to appropriately perform the above-mentioned abnormal value handling process.

[0019] The signal processing method of the present disclosure is

[12] "a signal processing method that includes a processing step of converting a target signal corresponding to the output signal from a vacuum tube sensor having a photocathode that emits electrons in response to incident light and outputting an output signal corresponding to the amount of light of the incident light into a digital signal at a predetermined sampling frequency, and deriving an output value for each predetermined measurement period, wherein in the processing step, a number of data corresponding to the pulse width of an abnormal value signal appearing in the target signal are excluded from a plurality of data included in the target signal during the measurement period in order of decreasing signal value, and the output value is derived from the remaining plurality of data." According to this signal processing method, for the reasons described above, high-speed processing of events indicating abnormal values ​​becomes possible.

[0020] The signal processing method of the present disclosure is

[13] "a signal processing method that includes a processing step of converting a target signal corresponding to the output signal from a vacuum tube sensor having a photocathode that emits electrons in response to incident light and outputting an output signal corresponding to the amount of light of the incident light into a digital signal at a predetermined sampling frequency, and deriving an output value for each predetermined measurement period, wherein in the processing step, from a plurality of data included in the target signal during the measurement period, a number of consecutive data including data corresponding to the maximum signal value is excluded by a set ratio, which is the ratio of the number of sampling points before and after the sampling point corresponding to the maximum signal value, and the output value is derived from the remaining data of the plurality of data." According to this signal processing method, for the reasons described above, high-speed processing of events showing abnormal values ​​becomes possible.

[0021] This disclosure makes it possible to provide a signal processing circuit, an optical detection device, and a signal processing method that can process events exhibiting abnormal values ​​at high speed.

[0022] Figure 1 is a diagram illustrating the configuration of a laser scanning microscope. Figure 2 is a diagram illustrating the scanning of excitation light onto a sample. Figure 3 is a cross-sectional view of a vacuum tube sensor. Figure 4 is a diagram illustrating the signal processing flow. Figure 5 is a diagram illustrating X-ray noise. Figure 6 is a diagram showing an example of X-ray noise observation. Figure 7 is a diagram illustrating the method for calculating pixel values ​​in a reference example. Figure 8 is a diagram illustrating the method for calculating pixel values ​​in the first embodiment. Figure 9 is a diagram illustrating the case of extremely low illumination. Figure 10 is a flowchart illustrating the processing flow. Figures 11(a) and (b) are diagrams illustrating the determination process. Figure 12 is a graph showing the relationship between the electron-hole pair production constant and the energy required to produce an electron-hole pair. Figures 13(a) and (b) are diagrams showing examples of images with noise, where (a) is an example for extremely low illumination and (b) is an example for medium illumination. Figures 14(a) and (b) show examples of images obtained when noise reduction processing is performed, with (a) being an example for extremely low illumination and (b) being an example for medium illumination. Figures 15(a) and (b) show examples of images obtained when judgment processing is performed, with (a) being an example for extremely low illumination and (b) being an example for medium illumination. Figure 16 is a diagram illustrating the method for calculating pixel values ​​in the second embodiment. Figure 17 is a diagram illustrating the noise reduction processing in the second embodiment. Figure 18 is a diagram illustrating the case of extremely low illumination. Figures 19(a) and (b) show examples of images with noise, with (a) being an example for extremely low illumination and (b) being an example for medium illumination. Figures 20(a) and (b) show examples of images obtained when noise reduction processing is performed, with (a) being an example for extremely low illumination and (b) being an example for medium illumination. Figures 21(a) and (b) show examples of images obtained when the judgment process is performed, with (a) being an example for extremely low illumination and (b) being an example for medium illumination. Figures 22(a), (b), and (c) are diagrams to explain the noise reduction process when the expected value of the measured light intensity does not change over time. Figures 23(a) and (b) are diagrams to explain the noise reduction process when the expected value of the measured light intensity changes over time.Figures 24(a) and 24(b) illustrate a method for replacing sampling points in sections containing noise pulses. Figure 25 is a graph showing simulation results when the expected value of the measured light intensity changes over time. Figure 26 is a graph showing an enlarged portion of Figure 26. Figure 27 is a configuration diagram of a modified laser scanning microscope.

[0023] Embodiments of this disclosure will be described in detail below with reference to the drawings. In the following description, the same or equivalent elements will be denoted by the same reference numerals, and redundant descriptions will be omitted. [First Embodiment]

[0024] As shown in Figure 1, the laser scanning microscope 1 comprises a light source 2, a dichroic mirror 3, scanning mirrors 4 and 5, an objective lens 6, and a photodetector A (photodetector) including a vacuum tube sensor 7. The laser scanning microscope 1 is, for example, a confocal laser scanning microscope, which irradiates a sample S with excitation light L1 (irradiation light) output from the light source 2, and detects measurement light L2 generated in the sample S in response to the irradiation of excitation light L1 using the vacuum tube sensor 7. The sample S is the object to be observed and is, for example, placed on a stage. For example, the sample S is a cell, and the measurement light L2 is fluorescence (fluorescence signal).

[0025] Light source 2 is a point light source composed of, for example, a CW (Continuous Wave) laser, and outputs laser light as excitation light L1 (irradiation light). Dichroic mirror 3 is an optical element that reflects the excitation light L1 while transmitting the measurement light L2. Scanning mirrors 4 and 5 are mirrors for scanning the irradiation position of the excitation light L1 on the sample S. Scanning mirrors 4 and 5 are, for example, rotatable around different axes of rotation, and scan the irradiation position of the excitation light L1 along the XY plane (a plane perpendicular to the direction in which the excitation light L1 is irradiated onto the sample S).

[0026] The objective lens 6 is positioned to face the sample S. The excitation light L1 output from the light source 2 is reflected sequentially by the dichroic mirror 3 and scanning mirrors 4 and 5, then focused by the objective lens 6 and irradiated onto the sample S. The measurement light L2 generated in the sample S passes through the objective lens 6, is reflected by the scanning mirrors 5 and 4, passes through the dichroic mirror 3, and enters the vacuum tube sensor 7 of the photodetector A. A pinhole member 8 with a pinhole 8a formed therein is positioned between the vacuum tube sensor 7 and the dichroic mirror 3 to block measurement light L2 that has been generated and arrived outside the focal point. The vacuum tube sensor 7 is a photodetector that detects the measurement light L2. Details of the vacuum tube sensor 7 will be described later.

[0027] As shown in Figure 2, in the laser scanning microscope 1 of this embodiment, the observation surface of the sample S is virtually divided into multiple regions R arranged, for example, in a grid pattern, and measurements are performed while scanning the irradiation position of the excitation light L1 on the sample S so that these regions R are irradiated sequentially. The laser scanning microscope 1 outputs an image as an observation result, in which one pixel P corresponds to each region R, and the image is composed of multiple pixels P. Hereafter, "pixel" will refer to the pixel that makes up the observation image.

[0028] As shown in Figure 3, the vacuum tube sensor 7 is an electron tube comprising a housing portion 11 that defines the internal vacuum space, and a photocathode 12 and an electron detection unit 13 arranged within the housing portion 11. The electron detection unit 13 includes a semiconductor electron detection element, such as an avalanche diode. In this example, the vacuum tube sensor 7 is configured as a hybrid photodetector (HPD), an electron tube that combines the photocathode 12 and the electron detection unit 13, and increases the electron multiplication efficiency by accelerating electrons (photoelectrons) emitted from the photocathode 12 with a desired acceleration voltage and injecting them into the electron detection unit 13.

[0029] The housing 11 includes a stem 14, a side tube 15, a converging electrode 16, and an input panel 17. The stem 14 is formed, for example, in the shape of a disc and constitutes the bottom of the housing 11. The side tube 15 is formed in the shape of a cylinder, for example, made of ceramic, and is connected to the stem 14. The converging electrode 16 is formed in the shape of a cylinder, for example, made of a conductive material, and is connected to the side tube 15, forming a cylindrical tube together with the side tube 15. If the converging electrode 16 is not provided, the side tube 15 and the input panel 17 are directly connected.

[0030] The input panel 17 is formed, for example, in the shape of a disc and is positioned opposite the stem 14 to form the top of the housing portion 11. The input panel 17 is provided to cover the opening formed by the focusing electrode 16. The input panel 17 is made of a material that is transparent to the measurement light L2 (photons).

[0031] A photocathode 12 is formed on the inner surface 17a of the input panel 17. The inner surface 17a is the inner surface (stem 14 side) of the input panel 17. Measurement light L2 transmitted through the input panel 17 is incident on the photocathode 12. The photocathode 12 emits electrons (photoelectrons) E in response to the incident light (photons) of measurement light L2. Note that the incident light may also contain various X-rays as noise components, as described later. In this example, the photocathode 12 is a semiconductor photocathode formed from a material containing GaAsP, but it may also be a semiconductor photocathode containing other semiconductor materials, or an alkali photocathode containing alkali metal materials. During operation, an acceleration voltage of, for example, about -8kV is applied between the photocathode 12 and the electron detection unit 13. Electrons E emitted from the photocathode 12 are accelerated by the acceleration voltage between the photocathode 12 and the electron detection unit 13, and are focused by the focusing electrode 16 before being incident on the electron detection unit 13.

[0032] The electron detection unit 13 (electron multiplication unit) includes an avalanche diode, which is a semiconductor electron detection element. In this example, the avalanche diode is made of silicon. Electrons E emitted from the photocathode 12 are incident on the electron detection unit 13. When electrons E accelerated according to the acceleration voltage are incident on the electron detection unit 13, electron implantation multiplication occurs in accordance with the acceleration voltage, and the electrons E are multiplied (electron irradiation gain G1). Furthermore, the electrons E are further multiplied by avalanche multiplication that occurs inside the electron detection unit 13 according to the voltage applied to the avalanche diode (avalanche gain G2). In this way, the electron detection unit 13 multiplies the incident electrons E. During operation, a reverse bias voltage of, for example, about 500V is applied to the avalanche diode.

[0033] A connector section 18, for example, an SMA (Sub Miniature Type A) connector, is connected to the stem 14, and a current signal corresponding to the number of electrons E after multiplication by the electron detection section 13 is output from the connector section 18 to the outside of the vacuum tube sensor 7. The number of electrons E is proportional to the amount of light (number of photons) of the measurement light L2 incident on the photocathode 12. In other words, the vacuum tube sensor 7 outputs an output signal corresponding to the amount of light of the measurement light L2 incident on the photocathode 12.

[0034] As shown in Figure 4, the light detection unit A comprises a vacuum tube sensor 7, a signal processing circuit C, and a control unit 24. The signal processing circuit C comprises a current-voltage converter (current-voltage conversion unit) 21, an AD (analog-to-digital) converter 22, and a circuit unit 23. The current-voltage converter 21, the AD converter 22, and the circuit unit 23, as the signal processing circuit C, perform predetermined processing on the output signal from the vacuum tube sensor 7 and output it to the control unit 24. The control unit 24 performs image construction processing and other operations based on the input signal.

[0035] The current-voltage converter 21 is configured, for example, by a transimpedance amplifier (TIA amplifier). The current-voltage converter 21 receives an analog current signal output from the vacuum tube sensor 7. The current-voltage converter 21 converts this current signal into an analog voltage signal while multiplying its signal strength.

[0036] The current-voltage converter 21 has a predetermined cutoff frequency f ｃ This converts the current signal into a voltage signal. Typically, there is a limit to the frequency at which a TIA amplifier circuit can multiply, and the gain decreases in the high-frequency range. The cutoff frequency is defined, for example, as the value above which the gain drops by 3 dB from its normal value. Cutoff frequency f ｃ and the rise time τ of the output waveform signal ｒ It is known that the following relationship (1) exists between and . Note that the value of the constant 0.35 in equation (1) may change slightly, but the cutoff frequency f ｃ and rise time τ ｒ There is an inverse relationship between them. Rise time τ ｒ The rise time τ is the time interval between two points on the rising edge of the output waveform signal. Generally, the interval in which the signal strength changes from 10% to 90% of the signal strength after the rising edge (10-90% interval) is called the rise time τ. ｒ It is defined as follows. As can be seen from equation (1), the cutoff frequency f ｃ As it increases (as the bandwidth increases), the rise time τ ｒ The interval becomes shorter, meaning the response waveform becomes sharper.

[0037] The AD converter 22 processes the analog voltage signal output from the current-voltage converter 21 at a predetermined sampling frequency S ｒ This converts it into a digital voltage signal. The circuit unit 23 is composed of an integrated circuit such as an FPGA (Field Programmable Gate Array). The target signal ST, which is a digital voltage signal output from the AD converter 22, is input to the circuit unit 23. The target signal ST is a signal corresponding to the analog current signal (output signal) output from the vacuum tube sensor 7. In this example, the circuit unit 23 functions as a processing unit 25 that processes the target signal ST. Hereafter, the circuit unit 23 will also be referred to as the processing unit 25. The processing unit 25 calculates (derives) the value of each pixel P in the observed image based on the target signal ST. Details of the processing by the processing unit 25 will be described later.

[0038] The control unit 24 is composed of, for example, a computer equipped with a processor such as a CPU and a storage medium such as RAM or ROM. The control unit 24 functions as an image processing unit that constructs an observation image based on the values ​​of each pixel P output from the processing unit 25. The control unit 24 may also be given the function of a control unit that controls the operation of each part of the laser scanning microscope 1.

[0039] Figure 5 is a diagram illustrating X-ray noise, one of the various types of noise that indicate an abnormal value. X-ray noise is observed in the laser scanning microscope 1. As shown in Figure 5, when electrons E emitted from the photocathode 12 are incident on the electron detection unit 13, characteristic X-rays or bremsstrahlung X-rays may be emitted from the electron detection unit 13. Both are X-ray noise and can be dealt with by this embodiment, but for the sake of simplicity, only characteristic X-rays will be described below.

[0040] When characteristic X-rays are incident on the photocathode 12, many electrons are generated in the photocathode 12. Some of these electrons are annihilated within the photocathode 12, but most of the remaining electrons are emitted from the photocathode 12 toward the electron detection unit 13. In this case, when one characteristic X-ray is incident on the photocathode 12, not one electron is emitted as when a photon is incident, but rather, for example, dozens of electrons are emitted. When these electrons are incident on the electron detection unit 13, the output signal from the electron detection unit 13 increases, causing the value of pixel P to become excessively large, and in some cases, the pixel P may appear as a bright spot in the observed image. In the laser scanning microscope 1 according to the first embodiment described below, X-ray noise caused by such characteristic X-rays will be described as an event showing an abnormal value.

[0041] Figure 6 shows an example of X-ray noise observation. Figure 6 shows the pulse signal (measurement signal), which is a single pulse of the target to be measured, and the pulse signal (abnormal value signal), which is the noise signal of the X-ray noise to be removed, as measured by an oscilloscope. In Figure 6, the horizontal axis is time and the vertical axis is signal intensity (voltage). As shown in Figure 6, the intensity of the noise signal, i.e., the pulse height of the noise signal, is much larger than the intensity of the measurement signal, i.e., the pulse height of the measurement signal. The pulse width (FWHM) of the noise signal is about twice the pulse width (FWHM) of the measurement signal. Furthermore, the noise signal is measured almost simultaneously with the measurement signal. This is because the noise signal caused by characteristic X-rays emitted from the electronic detection unit 13 is measured almost simultaneously with the measurement signal, which is measured in response to the incidence of the measurement light L2. The inventors actually measured the noise signal while changing the amount of incident light L2, and from the measurement results, they obtained the finding that the signal amount and occurrence probability of the noise signal are constant.

[0042] Figure 7 is a diagram illustrating the method for calculating pixel values ​​in a reference example. Figure 7 shows an example of measurement results when acquiring data corresponding to one pixel P, that is, one pixel constituting an observed image. The measurement period shown in Figure 7 corresponds to the time that excitation light L1 is irradiated onto one pixel P. In the laser scanning microscope 1, this time is, for example, about 1 μs. Excitation light L1, which is CW light, is output from the light source 2. These points are the same in Figures 8, 9, and 11, which will be described later.

[0043] As shown in Figure 7, the sensor output from the vacuum tube sensor 7 includes a measurement signal. This "sensor output" corresponds to the "analog voltage signal" output from the current-voltage converter 21 in Figure 4. This measurement signal may be, for example, a single pulse or a signal consisting of a DC component. As shown in Figure 7, if X-ray noise occurs during the measurement period, a noise signal will appear in the sensor output from the vacuum tube sensor 7. In reality, the sensor output from the vacuum tube sensor 7 is output as a signal that combines the measurement signal and the noise signal, but for the sake of simplicity, the measurement signal and the noise signal are described separately. This is also true in Figures 8, 9, and 11, which will be discussed later.

[0044] In the example calculation method, a measurement window with a time width corresponding to the entire measurement period is set, and the output value during the measurement period (the value of one pixel P in the example of Figure 7) is calculated from the averaged measurement values ​​in the measurement window. In the example of Figure 7, for comparison with the first embodiment described later, the measurement window is virtually divided into four sections of the same time width, and the signal values ​​in these sections are assumed to be 108, 8, 5, and 2 in order of earliest measurement time, similar to the first embodiment described later. In this case, the section with a signal value of 108 is assumed to have a larger signal value compared to the other sections due to the influence of noise signals. These signal values ​​are calculated from the target signal ST, which is a digital voltage signal output from the AD converter 22 shown in Figure 4. In this case, if the average value per section is used in the four sections described above, the averaged measurement value in the measurement window becomes (108 + 8 + 5 + 2) / 4 = 30.8, and the value of pixel P becomes 30.8. Note that the value of pixel P may also be the sum of the measurement values ​​within the measurement period instead of the averaged value, in which case the value of pixel P becomes 123. Thus, in the calculation method of the example, if a noise signal occurs within the measurement window range, the noise signal has a significant impact on the value of pixel P. As a result, the value of pixel P may become excessive, and there is a risk that the pixel P will appear as a bright spot in the observed image. Furthermore, since the only discernible event is that the output signal has become larger, it is not possible to determine whether a noise signal has occurred or whether the signal value for each section has become larger overall (i.e., whether the actual amount of incident light itself has increased).

[0045] One way to address such problems is to perform measurements using a photon counting method. In this case, X-ray noise is also measured as a single photon, so the noise signal can be identified. However, because it is a digital judgment based on a set threshold, the dynamic range becomes low. Another way to address this is to set the acceleration voltage low and operate the vacuum tube sensor 7. In this case, the energy of the electrons is reduced to begin with, making it difficult to generate X-rays and thus X-ray noise. However, the internal gain becomes low, reducing the detection efficiency, and it becomes particularly difficult to observe single photons. Therefore, the laser scanning microscope 1 removes X-ray noise using the following method.

[0046] Figure 8 is a diagram illustrating the method for calculating pixel values ​​according to the first embodiment. In the calculation method according to the first embodiment, when calculating the output value (value of pixel P) during the measurement period (time per pixel P), sampling data with a number of removals D1, which is a number corresponding to the pulse width Wn of the noise signal appearing in the target signal ST, are excluded in descending order of signal value from a plurality of sampling data included in the target signal ST during the measurement period, and the output value during the measurement period is calculated from the remaining plurality of sampling data, thereby executing a noise reduction process, which is one of the abnormal value handling processes (sampling filter process). This process is executed by the processing unit 25 (circuit unit 23) shown in Figure 4. The target signal ST is a digital voltage signal output from the AD converter 22 shown in Figure 4, and is a signal corresponding to the analog current signal (output signal) output from the vacuum tube sensor 7. The plurality of sampling data included in the target signal ST are obtained by the AD converter 22 when the analog voltage signal output from the current-voltage converter 21 is sampled at a sampling frequency S ｒ It is generated by converting it into a digital voltage signal.

[0047] The removal count D1 is a value corresponding to the number of sampling data points included in the noise signal (the number of sampling points for one waveform of the noise signal), and AS ｒ / f ｃ It is set to A is a constant between 1 and 4, and S ｒis the sampling frequency of the AD converter 22, and f ｃ is the cutoff frequency of the current-voltage converter 21. If the measurement signal that appears in the target signal ST when one photoelectron is emitted from the photocathode 12 is defined as a single-pulse signal, and FWHM is the full width at half maximum of the single-pulse signal, then the FWHM of the single-pulse signal is the cutoff frequency f ｃ Between FWHM = 1 / (2f ｃ The relationship is as follows: In this case, the pulse width of the single-pulse signal is 2FWHM = 1 / f ｃ This is expressed as follows, and the number of sampled data points contained in a single pulse signal is S ｒ / f ｃ The constant A is set according to the pulse width of the noise signal to be removed. For example, in this example, the noise signal to be removed is a noise signal caused by X-ray noise, and as mentioned above, the pulse width Wn of the noise signal is about twice the pulse width of the measurement signal (Figure 6). Therefore, in this example, the constant A is set to 2. In this case, the number of sampled data points included in the noise signal caused by X-ray noise is 2S. ｒ / f ｃ It is represented as follows.

[0048] In this example, when the processing unit 25 calculates the output value (value of pixel P) during the measurement period (time per pixel P), it removes a number of samples D1 = 2S from multiple sample data included in the target signal ST during the measurement period. ｒ / f ｃ The sampling data is excluded in descending order of signal value, and a noise reduction process is performed to calculate the output value for the measurement period from the remaining multiple sampling data. For example, the processing unit 25 calculates the average value of the remaining multiple sampling data as the output value for the measurement period. This makes it possible to exclude noise signals with large outputs from the calculation result, and to calculate the pixel P value while excluding the effect of X-ray noise. In this specification, "removing noise" means removing at least a portion of the noise (reducing the noise), and is not necessarily limited to cases where all noise is completely removed.

[0049] Furthermore, in the laser scanning microscope 1, the cutoff frequency f of the current-voltage converter 21 ｃ The frequency range is widened to such that the pulse width Wn of the noise signal becomes smaller than half of the measurement period, specifically, for example, 5 MHz or higher. In this case, the pulse width Wn of the noise signal to be removed that appears in the target signal ST (sensor output) becomes narrower. As mentioned above, the cutoff frequency f ｃ As it increases, the rise time τ ｒ The frequency becomes shorter, and the response waveform becomes sharper. Cutoff frequency f ｃ When the bandwidth is increased, not only does the pulse width of the measurement signal become narrower, but the pulse width of the noise signal also becomes narrower.

[0050] On the other hand, when the intensity of the measurement light L2 is extremely low (in the case of extremely low illuminance), applying the calculation method according to the first embodiment may result in the following problems. Figure 9 is a diagram illustrating the case of extremely low illuminance. As shown in Figure 9, in the case of extremely low illuminance, the intensity of the measurement signal is extremely small. In the example in Figure 9, no noise is generated. As shown in Figure 9, if the calculation method according to the first embodiment described above is applied in this case and the sampling data with a removal number D1 is removed in order of decreasing signal value, the measurement signal may be excluded from the calculation result, and the measurement signal may not be reflected in the measurement result. However, since signals with extremely low intensity can be removed, it can function as a dark pulse filter to remove dark pulses.

[0051] Therefore, the following determination process may be used to determine whether or not noise occurred during the measurement period. If noise occurred during the measurement period, a noise reduction process may be executed. If no noise occurred, a normal calculation process (derivation process) may be executed to calculate the average value of the signal values ​​over n intervals as the output value. Figure 10 is a flowchart illustrating the processing flow. Figure 11 is a diagram illustrating the determination process. The processing in the laser scanning microscope 1 will be explained below in accordance with the flowchart in Figure 10.

[0052] First, the processing unit 25 receives a trigger from the control unit 24 to start the measurement period (pixel P) (step S1). Next, the processing unit 25 receives the target signal ST (digital voltage signal) for the measurement period from the AD converter 22 (step S2). In step S2, for example, the processing unit 25 receives digital voltage signals for a number of measurement points corresponding to the time width of the measurement period.

[0053] Next, the processing unit 25 determines whether the determination formula is satisfied (step S3). The details of the determination formula will be described later. If the determination formula is satisfied (YES in step S3), the processing unit 25 performs noise reduction processing and removes a number of noises D1 = 2S from multiple sample data included in the target signal ST during the measurement period. ｒ / f ｃ The sampling data is removed in descending order of signal value, and the average value of the remaining multiple sampling data is calculated as the output value for the measurement period (step S4). On the other hand, if the determination formula is not satisfied as a result of the determination (NO in step S3), the processing unit 25 performs a normal calculation process and calculates the output value for the measurement period from multiple sampling data for the measurement period without removing the sampling data of the number to be removed D1 (step S5). For example, in step S5, the processing unit 25 calculates the average value of all sampling data for the measurement period as the output value for the measurement period. After the execution of step S4 or S5, processing for the next measurement period (pixel P) is performed.

[0054] The determination formula is expressed by formula (2). As shown in Figure 8, the maximum value Max is the maximum value of the target signal ST during the measurement period, and the minimum value Min is the minimum value of the target signal ST during the measurement period.

[0055] As shown in Figure 11(a), the detection efficiency of the vacuum tube sensor 7 is denoted as PDE, and the number of electrons incident on the photocathode 12 due to noise is P. ephotocathode Therefore, the number of electrons P emitted from the photocathode 12 due to noise is... enoise This is expressed by equation (3). When the noise is X-ray noise, the energy of the characteristic X-ray is E. XrayAssuming that the electron-hole pair production constant of the photocathode 12 (the energy required for ionization at the photocathode 12) is κphotocathode, then the number of electrons P ephotocathode This is expressed by equation (4). Number of electrons P enoise The fluctuation (standard deviation) σ is expressed by equation (5).

[0056] Figure 12 is a graph showing the relationship between the electron-hole pair production constant and the energy required to produce an electron-hole pair. The vertical axis of the graph in Figure 12 represents the electron-hole pair production constant κphotocathode of the photocathode 12. The horizontal axis of the graph in Figure 12 represents the energy Eg required to produce an electron-hole pair. The data point DP in the graph in Figure 12 represents the case where the material of the photocathode 12 contains GaAs. The energy of the characteristic X-ray is, for example, 1700 eV. Therefore, from the graph in Figure 12, it can be seen that when characteristic X-rays are incident on the photocathode 12, an electron-hole pair is produced and electrons are emitted from the photocathode 12.

[0057] Figure 11(b) schematically shows the single-pulse signal that appears in the target signal ST (sensor output) when a single photoelectron is emitted from the photocathode 12, and the noise signal that appears in the target signal ST when the noise to be removed is incident on the photocathode 12. V shown in Figure 11(b) hsingle V is the pulse height (peak value) of the single-pulse signal. As shown in Figure 11(b), the fluctuation in the pulse height of the noise signal is expressed by equation (6). hsingle Let e ​​be the elementary charge, and G be the sensor gain provided by the vacuum tube sensor 7. sensor The TIA gain from the TIA amplifier is set to G ＴＩＡ If we assume that Δt is the half-width of the time waveform of the single-pulse signal, then it can be expressed by equation (7).

[0058] Based on the above, the determination formula in equation (2) is set. The left side of equation (2) (first value) is the difference between the maximum value Max and the minimum value Min during the measurement period. If the maximum value Max is increased due to the influence of a noise signal, the first value will have a value corresponding to the magnitude (pulse height) of the noise signal.

[0059] The right-hand side (second value) of equation (2) is the pulse height of the noise signal when fluctuations are taken into consideration. Pulse height V of a single-pulse signal hsingle The number of electrons P emitted from the photocathode 12 due to noise. enoise The value obtained by multiplying by corresponds to the pulse height (magnitude) of the noise signal. As mentioned above, the pulse width Wn of the noise signal caused by X-ray noise is about twice the pulse width of the measured signal (Figure 6). Therefore, in this example, the pulse height V hsingle Number of electrons P enoise The value obtained by multiplying by 1 / 2 is multiplied by 1 / 2. This coefficient is expressed as 1 / A using the constant A mentioned above. Also, when calculating the second value, the number of electrons P enoise From the number of electrons P enoise The value used is obtained by subtracting 6σ, which is six times the fluctuation σ. This allows the judgment to be made while taking into account the fluctuation of the noise signal equivalent to 6σ. In this example, the second value is V. hsingle (P enoise It is based on -6σ, but the second value is V hsingle (P enoise It may be based on -mσ) (where m is 2 or greater). That is, m is not limited to 6; for example, it can be an integer such as 2, 3, 4, 5, 7, 8, or a value with a fractional part after the decimal point, such as 2.5 or 3.5. In other words, m can be any real number greater than or equal to 2. m can be a real number greater than or equal to 2, 3, 4, 5, 6, etc.

[0060] In step S3 of Figure 10, by performing a determination using the determination formula (2), it is possible to determine whether or not noise occurred during the measurement period. If noise occurred during the measurement period, a noise reduction process can be performed (step S4), and if no noise occurred, a normal calculation process can be performed (step S5).

[0061] Figure 13 shows an example of an image with noise, Figure 14 shows an example of an image obtained when noise reduction processing is performed, and Figure 15 shows an example of an image obtained when judgment processing is performed. In Figures 13 to 15, (a) is an example in the case of extremely low illumination, and (b) is an example in the case of medium illumination (when the intensity of the measurement light L2 is normal). Figure 13 corresponds to an image obtained when the calculation method of the reference example (Figure 7) is applied, Figure 14 corresponds to an image obtained when the calculation method of the first embodiment (without judgment processing) is applied, and Figure 15 corresponds to an image obtained when the calculation method of the first embodiment (with judgment processing) is applied. The images in Figures 13 to 15 are images obtained by observing a sample having multiple areas with different brightness levels (the letters "H", "P", and "K" are written on a black background) with a laser scanning microscope, and the images were obtained while generating noise through simulation.

[0062] In the image of Figure 13(b), bright spots are generated in the black areas due to noise. Comparing Figure 13(b) and Figure 14(b), the bright spots are reduced in the image of Figure 14(b), indicating that X-ray noise can be removed by noise reduction processing. Comparing Figure 13(a) and Figure 14(a), the signal amount (the signal representing the letter "K") is reduced in the image of Figure 14(a), indicating that the signal amount is reduced by noise reduction processing in the case of extremely low illumination. Comparing Figure 13(a) and Figure 14(a), the dark noise (bright spots generated in the black areas) is reduced in the image of Figure 13(a), indicating that dark noise can be reduced by performing noise reduction processing. Comparing Figure 15(b) and Figure 14(b), the bright spots are reduced in the image of Figure 15(b), similar to the image of Figure 14(b), indicating that X-ray noise can be removed by noise reduction processing. Comparing Figure 15(a) with Figures 13(a) and 14(a), the signal level (the signal representing the letter "K") in Figure 15(a) is higher than in Figure 14 and is at the same level as in Figure 13. This shows that the decrease in signal level can be suppressed even in extremely low light conditions by performing the judgment process. [Function and Effects]

[0063] In the signal processing circuit C used in the photodetector A of the laser scanning microscope 1, the processing unit 25 is configured to perform noise reduction processing when calculating the output value during the measurement period. This involves removing a number of sampled data points D1 corresponding to the pulse width of the noise signal to be removed that appears in the target signal ST, in descending order of signal value, from multiple sampled data points included in the target signal ST during the measurement period, and then calculating the output value from the remaining multiple sampled data points. This allows for the calculation of the output value during the measurement period after removing high-power noise (X-ray noise in the above example) as needed. For example, if the measurement period corresponds to one pixel P, the output value can be used as the value of pixel P. In other words, because the noise reduction processing is performed at the level of numerical data (output value) rather than image data, high-speed processing is possible. This enables high-speed processing of high-power noise (X-ray noise in the above example).

[0064] More specifically, for example, if the measurement period corresponds to one pixel P, the output value can be used as the value of pixel P. In this way, noise can be removed before calculating the value of pixel P, rather than after. This makes it possible to remove high-output noise while improving real-time performance and data accuracy. That is, in the method described in Patent Document 1, the pixel in which noise occurred is identified after image acquisition (after calculating the pixel value), and the value of that pixel is replaced with an alternative value, resulting in low real-time performance. Therefore, for example, when displaying the acquired image as live video, there is a risk that noise will appear in the live video. In contrast, the signal processing circuit C used in the photodetector A of the laser scanning microscope 1 removes high-output noise before calculating the value of pixel P, thus improving real-time performance. Therefore, for example, when displaying the acquired image as live video, it is possible to suppress the appearance of noise in the live video. Also, since it is not necessary to perform noise processing after image acquisition, data analysis can be carried out immediately after image acquisition. Furthermore, in the method described in Patent Document 1, the data accuracy is low because the value of the pixel in which noise occurred is replaced with an alternative value. In contrast, the signal processing circuit C used in the photodetector A of the laser scanning microscope 1 calculates the value of pixel P using signals other than high-power noise acquired during the measurement period. Therefore, the value of pixel P is calculated using only measured data, which improves the accuracy of the data. Furthermore, while the method described in the above-mentioned Patent Document 1 may lead to increased processing complexity and an increase in the amount of data to be processed, the signal processing circuit C used in the photodetector A of the laser scanning microscope 1 can suppress this increase in data processing volume.

[0065] The signal processing circuit C used in the light detection unit A of the laser scanning microscope 1 processes the output signal, which is an analog current signal output from the vacuum tube sensor 7, at a predetermined cutoff frequency f ｃ A current-voltage converter 21 converts the analog voltage signal to an analog voltage signal, and the analog voltage signal is sampled at a sampling frequency S ｒ It includes an AD converter 22 that converts to a digital voltage signal, and the rejection number D1 is ASｒ / f ｃ This setting allows for the effective removal of high-power noise, such as that based on characteristic X-rays.

[0066] When the processing unit 25 calculates the output value during the measurement period, the first value based on the maximum value Max of the target signal ST during the measurement period is the number of electrons P emitted from the photocathode 12 when the incident light causing the noise to be removed is incident on the photocathode 12. enoise The electron number fluctuation σ and the pulse height V of the signal that appears in the target signal ST when one photoelectron is emitted from the photocathode 12 are considered. hsingle If the value is greater than or equal to the second value based on the above, noise reduction processing is performed. If the first value is smaller than the second value, a calculation process is performed to calculate the output value from multiple sample data during the measurement period without excluding the sample data for which the number of removals D1 was removed (steps S3 to S5). In this case, if noise occurs during the measurement period, noise reduction processing is performed, and if no noise occurs, a normal calculation process is performed to calculate the output value from the sample data during the measurement period without excluding the sample data for which the number of removals D1 was removed. Furthermore, by performing the judgment process, the normal calculation process can be performed even in the case of extremely low illumination, thus suppressing the reduction in signal amount.

[0067] The first value of the determination formula is the value obtained by subtracting the minimum value Min of the target signal ST during the measurement period from the maximum value Max of the target signal ST during the measurement period. This allows for a suitable (highly accurate) determination of whether or not noise occurred during the measurement period.

[0068] The second value is V hsingle (P enoise It is based on -mσ). This allows for a suitable (more accurate) determination of whether or not noise occurred during the measurement period. In the first embodiment described above, m is 6. In this case, even when there is a large variation in the height of high-output noise, high-output noise can be removed with greater accuracy. Therefore, even when the number of pixels P included in the observed image is extremely large, high-output noise can be suitable (more accurate) removed.

[0069] The vacuum tube sensor 7 has an avalanche diode (electron detection unit 13) that multiplies electrons from the photocathode 12. In such a vacuum tube sensor 7, since a solid element such as an avalanche diode is used, it is easy to perform noise reduction processing appropriately. In addition, in such a vacuum tube sensor 7, since electrons are accelerated and incident on the avalanche diode, high-energy electrons are incident on the internal structure of the vacuum tube sensor 7, and high-power noise based on characteristic X-rays is likely to occur. For this reason, it is particularly preferable to apply this embodiment to such a vacuum tube sensor 7 because noise reduction processing is important and easy to perform appropriately.

[0070] Cutoff frequency f of the current-voltage converter 21 ｃ However, the frequency is such that the pulse width Wn of the noise signal becomes smaller than half of the measurement period. In this case, the number of data to be removed can be reduced, so the output value can be derived with higher accuracy. More specifically, it is basically undesirable to make the measurement time, that is, the time per pixel P in this embodiment, too long, so it is difficult to significantly increase the number of sampled data per pixel P. On the other hand, when calculating the value of pixel P, the more sampled data that can be used, the smaller the error (standard deviation) when calculating the average value. Therefore, if the number of sampled data to be removed can be reduced, the number of sampled data that can be used to calculate the value of pixel P can be increased relatively, and the error (standard deviation) when calculating the average value will be smaller. In other words, in order to reduce the number of sampled data to be removed, it is preferable that the cutoff frequency fc of the current-voltage converter 21 is large, so it is preferable that the cutoff frequency fc of the current-voltage converter 21 is such that the pulse width Wn of the noise signal becomes smaller than half of the measurement period.

[0071] The noise reduction method (signal processing method) according to the first embodiment is a target signal ST corresponding to an output signal from a vacuum tube sensor 7 which has a photocathode 12 that emits electrons in response to incident light and outputs an output signal corresponding to the amount of light of the incident light, wherein the sampling frequency S is predetermined. ｒThe process includes a step of processing the target signal ST which has been converted into a digital voltage signal. In the processing step, the output value for the measurement period is calculated from the target signal ST during the measurement period. In the processing step, from a plurality of sampling data included in the target signal ST during the measurement period, sampling data with a number of removals D1 corresponding to the pulse width Wn of the noise signal to be removed that appears in the target signal ST is excluded in descending order of signal value, and the output value is calculated from the remaining plurality of sampling data. [Second Embodiment]

[0072] The laser scanning microscope 1 of the second embodiment is similar in configuration to the laser scanning microscope 1 of the first embodiment. The laser scanning microscope 1 of the second embodiment differs from the laser scanning microscope 1 of the first embodiment mainly in terms of operation. The differences in operation of the laser scanning microscope 1 from the first embodiment will be mainly described below.

[0073] Figure 16 is a diagram illustrating the method for calculating pixel values ​​in the second embodiment. As shown in Figure 16, the target signal ST includes a plurality of sampling points SP. In the calculation method according to the second embodiment, when calculating the output value (value of pixel P) during the measurement period (time per pixel P), a portion of consecutive sampling data, including the sampling data corresponding to the maximum signal value, is excluded from the plurality of sampling data included in the target signal ST during the measurement period. The output value during the measurement period is then calculated from the remaining sampling data among the plurality of sampling data, thereby performing noise reduction processing, which is one of the abnormal value handling processes (sampling filter processing). In other words, in the calculation method according to the second embodiment, a number of consecutive sampling points SP (removal number D2) including the sampling data corresponding to the maximum signal value are excluded from the plurality of sampling points SP included in the target signal ST during the measurement period, and the output value during the measurement period is calculated from the remaining sampling points SP. For example, the processing unit 25 calculates the average value of the remaining sampling data among the plurality of sampling data as the output value during the measurement period. The noise reduction processing is performed by the processing unit 25 (circuit unit 23) shown in Figure 4.

[0074] The number of samples to be removed D2 is a value corresponding to the number of sampling data points (number of sampling points SP for one waveform of the noise signal) that appear in the target signal ST, AS ｒ / f ｃ It is set to A is a constant between 1 and 4, and S ｒ is the sampling frequency of the AD converter 22, and f ｃ is the cutoff frequency of the current-voltage converter 21. The constant A is set according to the pulse width of the noise signal to be removed. For example, in this embodiment as well, the noise signal to be removed is a noise signal caused by X-ray noise, and as described above, the pulse width Wn of the noise signal is about twice the pulse width of the measurement signal (Figure 6). Therefore, in this embodiment as well, the constant A is set to 2. In this case, the number of sampling data points included in the noise signal caused by X-ray noise is 2S. ｒ / f ｃ It is represented as follows.

[0075] Figure 17 is a diagram illustrating the noise reduction process of the second embodiment. As shown in Figure 17, the target signal ST includes a sampling point MP1 measured at time T1, a sampling point MP2 measured at time T2 prior to time T1, and a sampling point MP3 measured at time T3 later than time T1. Sampling point MP1 corresponds to the maximum value Max of the target signal ST during the measurement period (see Figure 16). Sampling points MP2 and MP3 correspond to the minimum value Min of the target signal ST during the measurement period (see Figure 16).

[0076] Typically, the time waveform of a noise signal is not temporally symmetrical. Therefore, the rise time τ1 and fall time τ2 of the noise signal are different from each other. The rise time τ1 is the time interval between two points on the rising edge of the noise signal. The fall time τ2 is the time interval between two points on the falling edge of the noise signal. The rise time τ1 is defined as the time interval (10-90% interval) in which the signal intensity of the noise signal changes from 10% to 90% of the signal intensity after the rise (maximum value Max). The fall time τ2 is defined as the time interval (90-10% interval) in which the signal intensity of the noise signal changes from 90% to 10% of the signal intensity after the rise (maximum value Max). For convenience, in Figure 17, the time interval from time T2 to time T1 is shown as the rise time τ1, and the time interval from time T1 to time T3 is shown as the fall time τ2.

[0077] The rise time τ1 and fall time τ2 are determined according to the characteristics of the vacuum tube sensor 7 and the characteristics of the signal processing circuit C. Generally, the fall time τ2 is longer than the rise time τ1. Therefore, if sampling points SP with a removal number D2 are excluded so as to be temporally symmetrical with respect to sampling point MP1, sampling points SP included in the noise signal may remain, and the measurement signal may not be reflected in the measurement result. Accordingly, in the calculation method according to the second embodiment, in addition to excluding sampling point MP1, sampling points SPa measured from time T2 to time T1 and sampling points SPb measured from time T1 to time T3 are each excluded by a number based on a predetermined setting ratio.

[0078] The setting ratio is the ratio of the number of sampling points measured from time T2 to time T1 to the number of sampling points measured from time T1 to time T3. The setting ratio is preset based on the measured time waveform of the target signal ST. The time waveform of the target signal ST is determined according to the characteristics of the vacuum tube sensor 7 and the bandwidth of the TIA amplifier. Figure 17 shows an example where "the number of sampling points measured from time T1 to time T2 : the number of sampling points measured from time T1 to time T3 = 1:4". In the example in Figure 17, in addition to sampling point MP1, one sampling point SPa measured between time T1 and time T2, and four sampling points SPb measured between time T1 and time T3 are excluded. This makes it possible to exclude large noise signals from the calculation results, and to calculate the pixel P value while excluding the effect of X-ray noise.

[0079] On the other hand, when the intensity of the measurement light L2 is extremely low (in the case of extremely low illuminance), applying the calculation method according to the second embodiment may result in the following problems. Figure 18 is a diagram illustrating the case of extremely low illuminance. As shown in Figure 18, in the case of extremely low illuminance, the intensity of the measurement signal is extremely small. In the example in Figure 18, no noise is generated. As shown in Figure 18, if the calculation method according to the second embodiment is applied in this case and a portion of the continuous sampling data, including the sampling data corresponding to the maximum signal value, is excluded from the calculation result, and there is a risk that the measurement signal will not be reflected in the measurement result. However, since signals with extremely low intensity can be removed, it can function as a dark pulse filter to remove dark pulses.

[0080] Therefore, in the calculation method according to the second embodiment, the normal calculation process (derivation process) described in the first embodiment may be performed. The normal calculation process determines whether or not noise occurred during the measurement period by the determination process described in the first embodiment, performs noise removal processing if noise occurred during the measurement period, and calculates the average value of the signal values ​​of n intervals as the output value if no noise occurred. In the second embodiment as well, the noise removal process is performed according to the flowchart in Figure 10.

[0081] Figure 19 shows an example of an image with noise, Figure 20 shows an example of an image obtained when noise reduction processing is performed, and Figure 21 shows an example of an image obtained when judgment processing is performed. In Figures 19 to 21, (a) is an example in the case of extremely low illumination, and (b) is an example in the case of medium illumination (when the intensity of the measurement light L2 is normal). Figure 19 corresponds to an image obtained when the calculation method of the reference example (Figure 7) is applied, Figure 20 corresponds to an image obtained when the calculation method of the second embodiment (without judgment processing) is applied, and Figure 21 corresponds to an image obtained when the calculation method of the second embodiment (with judgment processing) is applied. The images in Figures 19 to 21 are images obtained by observing a sample having multiple areas with different brightness levels (the letters "H", "P", and "K" are written on a black background) with a laser scanning microscope, and the images were obtained while generating noise through simulation.

[0082] In the image of Figure 19(b), bright spots are generated in the black areas due to noise. Comparing Figure 19(b) with Figure 20(b), the bright spots are reduced in the image of Figure 20(b), indicating that X-ray noise can be removed by noise reduction processing. Comparing Figure 19(a) with Figure 20(a), the signal amount (the signal representing the letter "K") is reduced in the image of Figure 20(a), indicating that the signal amount is reduced by noise reduction processing at extremely low illumination. However, comparing Figure 19(a) with Figure 20(a), the dark noise (bright spots generated in the black areas) is reduced in the image of Figure 20(a), indicating that dark noise can be reduced by performing noise reduction processing. Furthermore, comparing Figure 21(b) with Figure 20(b), the bright spots are reduced in the image of Figure 21(b), similar to the image of Figure 20(b), indicating that X-ray noise can be removed by noise reduction processing. Comparing Figure 21(a) with Figures 19(a) and 20(a), the signal intensity (the signal representing the letter "K") in Figure 21(a) is higher than in Figure 20 and is at the same level as in Figure 19. This shows that the decrease in signal intensity can be suppressed even in extremely low light conditions by performing the judgment process. [Function and Effects]

[0083] In the signal processing circuit C used in the photodetector of the laser scanning microscope 1, the processing unit 25 is configured to perform noise reduction processing when calculating the output value during the measurement period. This process involves excluding a predetermined number of consecutive sampled data, including the sampled data corresponding to the maximum signal value, from multiple sampled data included in the target signal ST during the measurement period, based on a set ratio, and deriving the output value from the remaining sampled data. This allows for the deriving of the output value during the measurement period after removing high-power noise (X-ray noise in the above example) as needed. For example, if the measurement period corresponds to one pixel P, the output value can be used as the value of pixel P. In other words, because the system addresses abnormal values ​​at the numerical data level of the output value rather than image data, high-speed processing is possible. This enables high-speed processing of high-power noise (X-ray noise in the above example). Furthermore, by excluding a predetermined number of consecutive data, including the data corresponding to the maximum signal value, based on a set ratio, it is possible to suppress the exclusion of signal values ​​that are not abnormal. Therefore, the output value during the measurement period can be derived with high accuracy.

[0084] In this embodiment as well, the signal processing circuit C used in the photodetector A of the laser scanning microscope 1 includes a current-voltage converter 21 that converts the output signal, which is an analog current signal output from the vacuum tube sensor 7, into an analog voltage signal at a cutoff frequency fc, and an AD converter 22 that converts the analog voltage signal into a digital voltage signal at the sampling frequency Sr. The number of consecutive data points, i.e., the number of removals D2, is set to ASr / fc. This makes it possible to suitably remove, for example, high-power noise based on characteristic X-rays.

[0085] In this embodiment as well, when the processing unit 25 calculates the output value during the measurement period, the first value based on the maximum value Max of the target signal ST during the measurement period is the number of electrons P emitted from the photocathode 12 when the incident light causing the noise to be removed is incident on the photocathode 12. enoiseThe electron number fluctuation σ and the pulse height V of the signal that appears in the target signal ST when one photoelectron is emitted from the photocathode 12 are considered. hsingle If the value is greater than or equal to the second value based on the above, noise reduction processing is performed. If the first value is smaller than the second value, a calculation process is performed to calculate the output value from multiple sample data during the measurement period without excluding the sample data for which the number of removals D2 is excluded (steps S3 to S5). In this case, if noise occurs during the measurement period, noise reduction processing is performed, and if no noise occurs, a normal calculation process is performed to calculate the output value from the sample data during the measurement period without excluding the sample data for which the number of removals D2 is excluded. Furthermore, by performing the judgment process, the normal calculation process can be performed even in the case of extremely low illumination, thus suppressing the reduction in signal quantity.

[0086] In this embodiment as well, the first value of the determination formula is the value obtained by subtracting the minimum value Min of the target signal ST during the measurement period from the maximum value Max of the target signal ST during the measurement period. This makes it possible to accurately determine whether or not noise occurred during the measurement period.

[0087] In this embodiment as well, the second value is V hsingle (P enoise This is based on -mσ. This allows for a more accurate determination of whether or not noise occurred during the measurement period. In the second embodiment described above, m is 6. In this case, even when there is a large variation in the height of high-power noise, high-power noise can be removed with greater accuracy. Therefore, even when the number of pixels P included in the observed image is extremely large, high-power noise can be removed with greater accuracy.

[0088] In this embodiment as well, the cutoff frequency f of the current-voltage converter 21 ｃ However, the frequency is such that the pulse width Wn of the noise signal becomes smaller than half of the measurement period. In this case, the number of data points to be removed can be reduced, so the output value can be derived with higher accuracy.

[0089] The noise reduction method (signal processing method) according to the second embodiment is a target signal ST corresponding to an output signal from a vacuum tube sensor 7 which has a photocathode 12 that emits electrons in response to incident light and outputs an output signal corresponding to the amount of light of the incident light, wherein the sampling frequency S is predetermined. ｒ The process includes a step to process the target signal ST, which has been converted into a digital voltage signal. In the processing step, the output value for the measurement period is calculated from the target signal ST during the measurement period. In the processing step, from the multiple sampling data contained in the target signal ST during the measurement period, a number of consecutive data including the sampling data corresponding to the maximum signal value is excluded by a predetermined set ratio, i.e., the number of removals D2, and the output value is calculated from the remaining data among the multiple data.

[0090] Here, we will explain the points to note in the noise reduction process of the second embodiment. Figure 22(a) schematically represents the time change of the analog current signal SJ output from the vacuum tube sensor 7 when the expected value EV of the light intensity L2 per measurement period (time per pixel P) does not change over time and is uniform, such as in a confocal microscope. Assume that a noise pulse NP occurs in this analog current signal SJ. At this time, in the target signal ST, a portion of consecutive sampling points SP, including the sampling point SP corresponding to the maximum signal value of the target signal ST, are to be removed. Here, as shown in Figure 22(b), the maximum signal value of the target signal ST corresponds to the maximum signal value of the noise pulse NP. Also, a portion of consecutive sampling points SP, including the sampling point SP corresponding to the maximum signal value of the target signal ST, are included in the noise pulse NP in the target signal ST. Therefore, as shown in Figure 22(c), after the sampling points SP in the section AR containing the noise pulse NP are removed, the average value of the signal values ​​of multiple sampling points SP in the remaining section is calculated as the output value for the measurement period. In this case, the average value of the signal values ​​of multiple sampling points SP in the remaining section is close in magnitude to the average value of the expected light intensity EV during the measurement period, so the observed image can be reconstructed with high accuracy.

[0091] On the other hand, Figure 23(a) schematically represents the time evolution of an analog current signal SJ when the expected value EV of the light intensity L2 per measurement period changes over time, such as in flow cytometry. Suppose a noise pulse NP appears in this analog current signal SJ. In this case as well, as shown in Figure 23(b), the maximum signal value of the target signal ST corresponds to the maximum signal value of the noise pulse NP. Furthermore, a contiguous portion of sampling points SP, including the sampling point SP corresponding to the maximum signal value of the target signal ST, is included in the noise pulse NP in the target signal ST. Therefore, as shown in Figure 24(a), the sampling point SP in the section AR containing the noise pulse NP is removed, and the average value of the signal values ​​of multiple sampling points SP in the remaining section is calculated as the output value for the measurement period. At this time, the average value of the signal values ​​of multiple sampling points SP in the remaining section may differ significantly from the average value of the expected value EV of the light intensity per measurement section, depending on where the removal occurred. Consequently, a problem arises in which the accuracy of reconstructing the observed image decreases. Therefore, in such cases, as shown in Figure 24(b), for example, the sampling point SP within section AR can be replaced with a sampling point SPd corresponding to the average value of the sampling point SP immediately preceding section AR and the sampling point SP immediately following section AR. This replaces the signal value of the sampling point SP within section AR with the average value of the sampling point SP immediately preceding section AR and the sampling point SP immediately following section AR. By replacing the signal value of the sampling point SP within section AR with a value close to the average value of the expected light intensity EV in section AR, the average value of the sampling point SP per measurement section and the expected light intensity EV become closer, allowing for accurate reconstruction of the observed image.

[0092] Figure 25 is a graph showing the simulation results when the expected value EV of the light intensity of the measurement light L2 changes over time. Figure 26 is a graph showing an enlarged portion of Figure 25. In Figures 25 and 26, the horizontal axis represents the number of photons, and the vertical axis represents the count. In this simulation, the time window was set to 5 μs, and within that time window, the distribution of count values ​​for each number of photons was obtained from the target signal ST obtained by irradiating with measurement light L2 whose light intensity distribution follows a normal distribution. Line B1 shows the case where characteristic X-rays are not generated. Line B2 shows the case where characteristic X-rays are generated and the noise reduction processing of this embodiment is not performed. Lines B3 and B4 show the case where characteristic X-rays are generated and the noise reduction processing of this embodiment is performed. Line B3 shows the case where, as in Figure 24(a), the sampling point SP in the section AR containing the noise pulse NP is removed, and the average value of the signal values ​​of multiple sampling points SP in the remaining section is derived as the output value during the measurement period. Line B4 shows the case where the sampling point SP within section AR containing the noise pulse NP is replaced with a sampling point SPd corresponding to the average value of the signal values ​​of the sampling points SP before and after section AR, as shown in Figure 24(b).

[0093] As is clear from line B3, when the noise reduction process of this embodiment is performed to remove the signal value of sampling point SP within section AR, and then the number of photons is calculated based on the average value of the signal values ​​of sampling point SP in the remaining section, the measured number of photons will be smaller than the original distribution for the reasons mentioned above. In contrast, as is clear from line B4, by replacing the signal value of sampling point SP within section AR with the average value of the signal values ​​of sampling point SP before and after section AR, the measured number of photons can be brought closer to the original distribution. Therefore, the observed image can be reconstructed with high accuracy.

[0094] This disclosure is not limited to the first and second embodiments described above. The high-power noise to be removed is not limited to X-ray noise. Figure 27 is a configuration diagram of a modified laser scanning microscope 1A. In addition to the configuration of the laser scanning microscope 1 of the first or second embodiment, the laser scanning microscope 1A further includes a light source 9 for applying light stimulation to a sample S. The light source 9 outputs stimulation light L3 toward the sample S. In this case, the response of the sample S (e.g., a living organism) to the light stimulation can be observed. Noise may also be generated when the stimulation light L3 enters the optical system of the laser scanning microscope 1A as stray light. This noise caused by the stimulation light L3 is also one of the high-power noises to be removed in the laser scanning microscope 1A. Noise caused by the stimulation light L3 is measured almost simultaneously with the measurement signal, similar to X-ray noise. The laser scanning microscope 1A can also remove noise caused by the stimulation light L3. Furthermore, it can remove not only noise caused by some incident light, but also noise signals caused by some event occurring in the vacuum tube sensor 7.

[0095] In the first and second embodiments described above, the vacuum tube sensor 7 does not need to have an avalanche diode. For example, the vacuum tube sensor 7 may be a photomultiplier tube equipped with a dynode as an electron multiplier unit that multiplies electrons from the photocathode 12, or it may be any other vacuum tube sensor as long as it has a photocathode. In the first and second embodiments described above, the measurement period corresponded to the time that excitation light L1 was irradiated onto one pixel P, but it is not limited to this, and an appropriate measurement period may be set depending on the application. In the first and second embodiments described above, the first value of the determination formula was the value obtained by subtracting the minimum value Min from the maximum value Max during the measurement period, but the first value may be the value obtained by subtracting the average value of the remaining target signal ST after excluding the maximum value Max from the maximum value Max during the measurement period, or the median value of the target signal ST during the measurement period. In this case as well, it is possible to suitably determine whether or not noise occurred during the measurement period. The first value of the determination formula described above may be the maximum value Max itself. For example, if the measurement signal is relatively small, it is possible to determine whether or not noise occurred during the measurement period without subtracting the minimum value Min, which corresponds to the magnitude of the measurement signal, from the maximum value Max.

[0096] In the first and second embodiments described above, the processing unit 25 (circuit unit 23) calculated the value of each pixel P in the observed image based on the target signal ST, but the control unit 24 may perform these processes. In other words, the signal processing circuit C may include the control unit 24. The control unit 24 may function as the processing unit 25 that processes the target signal ST instead of the circuit unit 23. The signal processing circuit C may have any configuration as long as it is a circuit capable of processing signals originating from electrons from the photocathode 12 of the vacuum tube sensor 7 in accordance with this disclosure. Similarly, the photodetector A does not have to include the control unit 24, and may have any configuration as long as it is a photodetector capable of processing signals originating from electrons from the photocathode 12 of the vacuum tube sensor 7 in accordance with this disclosure.

[0097] In the first and second embodiments described above, examples of the present disclosure being applied to a laser scanning microscope were explained. However, the present disclosure is applicable to other configurations, such as flow cytometers (flow cytometry) and specimen testing.

[0098] 7...Vacuum tube sensor, 12...Photocathode, 21...Current-voltage converter (current-voltage conversion unit), 22...AD converter, 25...Processing unit, C...Signal processing circuit, ST...Target signal, Max...Maximum value, Min...Minimum value.

Claims

1. A signal processing circuit comprising a processing unit that converts a target signal corresponding to the output signal from a vacuum tube sensor having a photocathode that emits electrons in response to incident light and outputs an output signal corresponding to the amount of light of the incident light into a digital signal at a predetermined sampling frequency and derives an output value for each predetermined measurement period, wherein the processing unit is configured to perform an abnormal value handling process when deriving the output value for the measurement period, which excludes a number of data corresponding to the pulse width of an abnormal value signal appearing in the target signal from a plurality of data included in the target signal during the measurement period, in descending order of signal value, and derives the output value from the remaining plurality of data.

2. A current signal corresponding to the amount of incident light is transmitted at a predetermined cutoff frequency f ｃ A current-to-voltage conversion unit converts the voltage signal to a current-to-voltage signal, and the sampling frequency S ｒ The system further comprises an AD converter that converts the signal to a digital signal, and the number of abnormal value signals corresponding to the pulse width is AS ｒ / f ｃ The signal processing circuit according to claim 1, wherein A is a constant between 1 and 4 (A is a constant between 1 and 4).

3. A signal processing circuit comprising a processing unit that converts a target signal corresponding to the output signal from a vacuum tube sensor having a photocathode that emits electrons in response to incident light and outputs an output signal corresponding to the amount of light of the incident light into a digital signal at a predetermined sampling frequency and derives an output value for each predetermined measurement period, wherein the processing unit is configured to perform abnormal value handling processing when deriving the output value for the measurement period, by excluding a number of consecutive data, including the data corresponding to the maximum signal value, from a plurality of data included in the target signal for the measurement period, based on a predetermined set ratio which is the ratio of the number of sampling points before and after the sampling point corresponding to the maximum signal value, and deriving the output value from the remaining data among the plurality of data.

4. A current signal corresponding to the amount of incident light is transmitted at a predetermined cutoff frequency f ｃ A current-to-voltage conversion unit converts the voltage signal to a current-to-voltage signal, and the sampling frequency S ｒ The system further comprises an AD converter that converts the data into a digital signal, and the number of consecutive data is AS ｒ / f ｃ The signal processing circuit according to claim 3, wherein A is a constant between 1 and 4 (A is a constant between 1 and 4).

5. When deriving the output value during the measurement period, the processing unit determines that when the incident light corresponding to the abnormal value signal is incident on the photoelectric surface, the first value based on the maximum value of the target signal during the measurement period is the number of electrons P emitted from the photoelectric surface enoise and the fluctuation σ of the number of electrons, and when the pulse height V of the signal appearing in the target signal when one photoelectron is emitted from the photoelectric surface hsingle is greater than or equal to the second value based on these, the abnormal value corresponding process is executed, and when the first value is smaller than the second value, the derivation process for deriving the output value from the plurality of data during the measurement period without executing the abnormal value corresponding process is executed. The signal processing circuit according to any one of claims 1 to 4.

6. The signal processing circuit according to claim 5, wherein the first value is the value obtained by subtracting one of the following values ​​from the maximum value of the target signal during the measurement period: the minimum value of the target signal during the measurement period, the average value of the remaining target signal after excluding the maximum value, and the median value of the target signal during the measurement period, or the maximum value.

7. The second value mentioned above is V hsingle (P enoise A signal processing circuit according to claim 5 or 6, based on -mσ (where m is 2 or greater).

8. The signal processing circuit according to any one of claims 1 to 7, wherein the vacuum tube sensor further comprises an avalanche diode for multiplying electrons from the photocathode.

9. The signal processing circuit according to claim 1 or 3, further comprising a current-voltage conversion unit that converts a current signal corresponding to the amount of incident light into a voltage signal at a predetermined cutoff frequency, wherein the cutoff frequency is set such that the pulse width of the voltage signal indicated by the abnormal value signal is less than half of the measurement period.

10. A light detection device comprising the vacuum tube sensor and the signal processing circuit according to any one of claims 1 to 9.

11. The photodetector according to claim 10, wherein the vacuum tube sensor further comprises an avalanche diode for multiplying electrons from the photocathode.

12. A signal processing method comprising a processing step of converting a target signal corresponding to the output signal from a vacuum tube sensor having a photocathode that emits electrons in response to incident light and outputting an output signal corresponding to the amount of light of the incident light into a digital signal at a predetermined sampling frequency, and deriving an output value for each predetermined measurement period, wherein in the processing step, a number of data corresponding to the pulse width of an abnormal value signal appearing in the target signal are excluded from a plurality of data included in the target signal during the measurement period, in descending order of signal value, and the output value is derived from the remaining plurality of data.

13. A signal processing method comprising a processing step of converting a target signal corresponding to the output signal from a vacuum tube sensor having a photocathode that emits electrons in response to incident light and outputting an output signal corresponding to the amount of light of the incident light into a digital signal at a predetermined sampling frequency, and deriving an output value for each predetermined measurement period, wherein in the processing step, a number of consecutive data including the data corresponding to the maximum signal value are excluded from a plurality of data included in the target signal during the measurement period, based on a predetermined set ratio which is the ratio of the number of sampling points before and after the sampling point corresponding to the maximum signal value, and the output value is derived from the remaining data among the plurality of data.

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