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

Abstract

In the present invention, a noise removal system comprises a processing unit that: processes a target signal corresponding to an output signal which corresponds to the amount of entry light and is outputted from a vacuum tube sensor which has a photoelectric surface for emitting electrons in response to entry light and outputs the output signal; and derives an output value for each prescribed measurement time. The processing unit is configured to be able to execute an abnormal value handling process for: dividing a measurement period into n (n is an integer of 2 or more) sections; deriving signal values in the n sections from the target signal; and when deriving an output value in the measurement period from the signal values in the n sections, deriving the output value from the signal values in the n sections so that the magnitude of the maximum signal value that is largest among the signal values does not affect the magnitude of the output value.

Description

Signal processing circuit, photodetector, and signal processing method

[0001] One aspect of this disclosure relates to a signal processing circuit, a photodetector, and a signal processing method.

[0002] One type of optical sensor is the vacuum tube sensor, which has a photocathode that emits electrons in response to incident light, and detects light by multiplying the electrons emitted from the photocathode.

[0003] Japanese Patent Publication No. 2015-141705

[0004] Vacuum tube sensors can be used, for example, in the light detection section of a laser scanning microscope. The inventors have found that in such cases, due to various noise components, abnormal values ​​with outputs larger than the normal values ​​due to the signal light may be detected, making it difficult to use the information at the time the abnormal output value was detected in the acquired image.

[0005] On the other hand, there is a noise reduction technique, for example, 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 identified, and the value of the pixel is replaced with an alternative value calculated from the values ​​of surrounding pixels, or an alternative value calculated from the values ​​of the pixel acquired at the time before and after the pixel. However, in the method described in Patent Document 1, the data configured as image data is processed as described above and reconstructed into an image. Therefore, there was a problem, especially in cases where high-speed processing of noise is required, such as in real-time observation.

[0006] Therefore, one aspect of this disclosure aims 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.

[0007] One aspect of the present disclosure is a signal processing circuit comprising: [1] "a signal processing circuit having a photocathode that emits electrons in response to incident light and a processing unit that processes a target signal corresponding to the output signal from a vacuum tube sensor that outputs an output signal corresponding to the amount of light of the incident light, and derives an output value for each predetermined measurement period, wherein the processing unit is configured to perform abnormal value handling processing when dividing the measurement period into n (where n is an integer of 2 or more) intervals, deriving a signal value in each of the n intervals from the target signal, and deriving an output value for the measurement period from the signal values ​​in the n intervals, such that the magnitude of the largest maximum signal value among the signal values ​​does not affect the magnitude of the output value."

[0008] In this signal processing circuit, the processing unit divides the measurement period into n intervals, derives the signal value for each of the n intervals from the target signal, and derives the output value for the measurement period from the signal values ​​in the n intervals. Furthermore, when the processing unit derives the output value for the measurement period, it is configured to perform an anomaly handling process so that the magnitude of the largest signal value among the n intervals does not affect the magnitude of the output value. This allows for the deriving of the output value for the measurement period after performing anomaly handling processing as needed. In other words, because the handling of anomalies is performed at the level of numerical data (output value) rather than image data, high-speed processing is possible.

[0009] A signal processing circuit relating to one aspect of this disclosure may be [2] "the signal processing circuit according to [1], wherein in the abnormal value handling process, the processing unit derives the average value of the remaining signal values ​​in the n intervals, excluding the maximum signal value, as the output value." In this case, the output value can be derived from the signal values ​​in the n intervals in such a way that the magnitude of the maximum signal value does not affect the magnitude of the output value.

[0010] A signal processing circuit relating to one aspect of this disclosure may be [3] "the signal processing circuit according to [1], wherein the processing unit derives the median value of the signal values ​​in the n intervals as the output value in the abnormal value handling process." In this case, the output value can be derived from the signal values ​​in the n intervals in such a way that the magnitude of the maximum signal value does not affect the magnitude of the output value.

[0011] A signal processing circuit relating to one aspect of this disclosure may be [4] "a signal processing circuit according to any one of [1] to [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 corresponding to the maximum signal value is narrower than the width of each of the n sections." In this case, it is possible to suppress the complexity of processing for abnormal values, which can occur when an event indicating an abnormal value spans multiple sections.

[0012] A signal processing circuit relating to one aspect of this disclosure is [5] "When the processing unit derives the output value during the measurement period, the first value based on the maximum signal value is the number of electrons P emitted from the photocathode when the incident light corresponding to the maximum signal value is incident on the photocathode." enoise The fluctuations in the number of electrons σ and the signal quantity Q that appears in the target signal when one photoelectron is emitted from the photocathode are given. single The signal processing circuit may be any of [1] to [4] described above, which executes the abnormal value handling process if the first value is greater than or equal to the second value based on the above, and executes a derivation process to derive the average value of the signal values ​​in the n intervals as the output value if the first value is smaller than the second value. In this case, if an event indicating an abnormal value occurs during the measurement period, the abnormal value handling process can be executed, and if no event indicating an abnormal value occurs, a derivation process to derive the average value of the signal values ​​in the n intervals as the output value can be executed.

[0013] A signal processing circuit relating to one aspect of this disclosure may be [6] "the signal processing circuit according to [5], wherein the first value is the value obtained by subtracting from the maximum signal value any one of the following signal values: the smallest minimum signal value among the n intervals, the average value of the remaining signal values ​​in the n intervals excluding the maximum signal value, the median value of the remaining signal values ​​in the n intervals excluding the maximum signal value, or the maximum signal value." In this case, it is possible to suitably determine whether or not an event indicating an abnormal value occurred during the measurement period.

[0014] A signal processing circuit relating to one aspect of this disclosure is [7] "The second value is Q single (P enoise The signal processing circuit may be the one described in [5] or [6], based on -mσ (where m is 2 or greater). In this case, it is possible to suitably determine whether or not an event indicating an abnormal value occurred during the measurement period.

[0015] A signal processing circuit relating to one aspect of this disclosure may be [8] "a 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." In such a vacuum tube sensor, since a solid element such as an avalanche diode is used, it becomes easier to appropriately perform the above-mentioned abnormal value handling processing.

[0016] A photodetector relating to one aspect of this disclosure is [9] "a photodetector comprising the vacuum tube sensor and a signal processing circuit described in any of [1] to [8]". This photodetector 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.

[0017] A photodetector relating to one aspect of this disclosure may be

[10] "the photodetector according to [9], wherein the vacuum tube sensor further comprises an avalanche diode that multiplies electrons from the photocathode." In such a vacuum tube sensor, since a solid element such as an avalanche diode is used, it becomes easier to appropriately perform the above-mentioned abnormal value handling process.

[0018] A signal processing method relating to one aspect of the present disclosure is

[11] "a signal processing method that includes processing 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, and deriving an output value for each predetermined measurement period, wherein the measurement period is divided into n (n is an integer of 2 or more) intervals, a signal value in each of the n intervals is derived from the target signal, and when deriving the output value for the measurement period from the signal values ​​in the n intervals, the output value is derived from the signal values ​​in the n intervals in such a way that the magnitude of the largest maximum signal value among the signal values ​​in the n intervals does not affect the magnitude of the output value." According to this signal processing method, for the reasons described above, high-speed processing of events showing abnormal values ​​becomes possible.

[0019] According to one aspect of this disclosure, it is 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.

[0020] It is a configuration diagram of a laser scanning microscope. It is a diagram for explaining the scanning of excitation light on a sample. It is a cross-sectional view of a vacuum tube sensor. It is a diagram for explaining the signal processing flow. It is a diagram for explaining X-ray noise. It is a diagram showing an observation example of X-ray noise. It is a diagram for explaining a method of calculating pixel values in a reference example. It is a diagram for explaining a method of calculating pixel values in an embodiment. It is a diagram for explaining the case of extremely low illuminance. It is a flowchart for explaining a processing flow. It is a diagram for explaining a determination process. (a) and (b) are diagrams for explaining a determination process. (a) and (b) are diagrams showing examples of images in which noise is generated, (a) is an example in the case of extremely low illuminance, and (b) is an example in the case of medium illuminance. (a) and (b) are diagrams showing examples of images obtained when a noise removal process is executed, (a) is an example in the case of extremely low illuminance, and (b) is an example in the case of medium illuminance. (a) and (b) are diagrams showing examples of images obtained when a determination process is executed, (a) is an example in the case of extremely low illuminance, and (b) is an example in the case of medium illuminance. It is a configuration diagram of a laser scanning microscope according to a modified example.

[0021] Hereinafter, embodiments of one aspect of the present disclosure will be described in detail with reference to the drawings. In the following description, the same or corresponding elements are denoted by the same reference numerals, and redundant descriptions are omitted.

[0022] As shown in FIG. 1, the laser scanning microscope 1 includes a light source 2, a dichroic mirror 3, scanning mirrors 4 and 5, an objective lens 6, and a light detection unit A (light detection device) including a vacuum tube sensor 7. The laser scanning microscope 1 is, for example, a confocal laser scanning microscope, irradiates the sample S with the excitation light L1 (irradiation light) output from the light source 2, and detects the measurement light L2 generated in the sample S in response to the irradiation of the excitation light L1 by the vacuum tube sensor 7. The sample S is an observation object 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).

[0023] The 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). The dichroic mirror 3 is an optical element that reflects the excitation light L1 while transmitting the measurement light L2. The scanning mirrors 4 and 5 are mirrors for scanning the irradiation position of the excitation light L1 with respect to the sample S. The scanning mirrors 4 and 5 are rotatable, for example, around different rotation axes, and scan the irradiation position of the excitation light L1 along the XY plane (a plane perpendicular to the irradiation direction of the excitation light L1 with respect to the sample S).

[0024] The objective lens 6 is arranged to face the sample S. The excitation light L1 output from the light source 2 is reflected in sequence by the dichroic mirror 3 and the scanning mirrors 4 and 5, and then condensed 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 then reflected by the scanning mirror 5 and the scanning mirror 4, passes through the dichroic mirror 3, and enters the vacuum tube sensor 7 of the light detection unit A. Between the vacuum tube sensor 7 and the dichroic mirror 3, a pinhole member 8 in which a pinhole 8a for blocking the measurement light L2 generated and arriving outside the focal point is formed is arranged. The vacuum tube sensor 7 is a light detector that detects the measurement light L2. Details of the vacuum tube sensor 7 will be described later.

[0025] As shown in FIG. 2, in the laser scanning microscope 1 in this embodiment, the observation surface of the sample S is virtually divided into a plurality of regions R arranged, for example, in a grid pattern, and while scanning the irradiation position of the excitation light L1 with respect to the sample S so that these regions R are irradiated in sequence, measurement is performed. In the laser scanning microscope 1, as an observation result, an image composed of a plurality of pixels P, with one pixel P corresponding to each region R, is output. Hereinafter, a pixel will refer to a pixel constituting the observation image.

[0026] 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.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] As shown in FIG. 4, the light detection unit A includes a vacuum tube sensor 7, a signal processing circuit C, and a control unit 24. The signal processing circuit C includes a current-voltage converter (current-voltage conversion unit) 21, an AD (analog-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 executes construction processing of an observation image and the like based on the input signal.

[0033] The current-voltage converter 21 is constituted by, for example, a transimpedance amplifier (TIA amplifier). An analog current signal output from the vacuum tube sensor 7 is input to the current-voltage converter 21. The current-voltage converter 21 converts the current signal into an analog voltage signal while doubling the signal intensity.

[0034] The current-voltage converter 21 converts the current signal into a voltage signal at a predetermined cut-off frequency f ｃ . Usually, there is a limit to the frequency that can be doubled in a TIA amplifier circuit, and the gain decreases in the high-frequency range. The cut-off frequency is defined, for example, as a value at which the gain decreases by 3 dB from the normal value when the frequency exceeds the cut-off frequency. There is a known relationship of the following formula (1) between the cut-off frequency f ｃ and the rise time τ ｒ of the output waveform signal. Although the value of the constant 0.35 in formula (1) may vary slightly, there is an inverse proportional relationship between the cut-off frequency f <o:p>and the rise time τ ｒ . The rise time τ ｒ is the time interval between two points on the rising edge of the output waveform signal. Generally, the section in which the signal intensity changes from 10% to 90% of the signal intensity after the rise (10 - 90% section) is defined as the rise time τ ｒ . As can be seen from formula (1), when the cut-off frequency f ｃ increases (when the bandwidth is broadened), the rise time τ ｒ becomes shorter, that is, the response waveform becomes sharper.

[0035] 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.

[0036] 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.

[0037] Figure 5 is a diagram illustrating X-ray noise, one of the various types of noise that exhibit abnormal values. 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 constitute X-ray noise and can be addressed by this disclosure, but for the sake of simplicity, only characteristic X-rays will be described below.

[0038] 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 following embodiments, X-ray noise caused by such characteristic X-rays will be described as an event showing an abnormal value.

[0039] Figure 6 shows an example of X-ray noise observation. Figure 6 shows the pulse signal (single pulse) of the target to be measured (measurement signal) and the pulse signal (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 (pulse height) of the noise signal is much larger than the intensity (pulse height) of the measurement signal. The pulse width (full width at half maximum) of the noise signal is about twice that of the pulse width (full width at half maximum) 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 obtained from the measurement results that the signal amount and occurrence probability of the noise signal are constant.

[0040] 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.

[0041] 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.

[0042] 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 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 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).

[0043] 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.

[0044] Figure 8 is a diagram illustrating the method for calculating pixel values ​​according to the embodiment. As shown in Figure 8, in the calculation method according to the embodiment, the measurement period (time per pixel P) is divided into n (where n is an integer of 2 or more) intervals of the same time width (four in this example), the signal value in each interval is calculated from the target signal ST, and the output value (value of pixel P) for the measurement period is calculated from the signal values ​​in the four intervals. This process is performed by the processing unit 25 (circuit unit 23) shown in Figure 4.

[0045] In other words, the processing unit 25 sets up four measurement windows, each having a time width corresponding to one of four sections obtained by dividing the measurement period into four parts, and calculates the value of pixel P from the signal values ​​in these measurement windows. The signal value in each section (measurement window) is, for example, the average value of the target signal ST in that section (the integral value divided by the time width). In the example in Figure 8, the signal values ​​in the four sections are 108, 8, 5, and 2 in order of earliest measurement time. The section with a signal value of 108 has a larger signal value compared to the other sections due to the influence of noise signals. These signal values ​​are calculated by the processing unit 25 from the target signal ST, which is a digital voltage signal output from the AD converter 22 shown in Figure 4.

[0046] The processing unit 25 performs noise reduction processing, which is one of the abnormal value handling processes, and calculates the average value of the remaining signal values ​​after excluding the largest maximum signal value among the signal values ​​in the four intervals as the output value (value of pixel P) for the measurement period (n-division filter processing). In the example in Figure 8, the average value of the remaining signal values ​​8, 5, and 2 after excluding the largest maximum signal value 108 among the four signal values ​​108, 8, 5, and 2 is (8 + 5 + 2) / 3 = 5, and the value of pixel P is 5. If the above noise reduction processing is not performed, the averaged measurement value in the measurement window will be (108 + 8 + 5 + 2) / 4 = 30.8. In other words, the value of pixel P will be 30.8, which is more than six times the value after noise processing. Thus, in the calculation method according to the embodiment, in order so that the magnitude of the maximum signal value (here 108) does not affect the magnitude of the value of pixel P (here 5), the value of pixel P is calculated from the signal values ​​in the four intervals by specifically calculating the value of pixel P from the remaining signal values ​​after excluding the maximum signal value. This allows for the calculation of the pixel P value while excluding the effects of X-ray noise. Furthermore, if the same processing is performed for all measurement periods, the pixel P value may be 5, which is the average value of the intervals as described above, or it may be 20, which is the sum of the values ​​for the entire measurement period (5 x 4 intervals = 20). In this specification, "removing noise" means removing at least a portion of the noise (reducing the noise), and does not necessarily mean that all noise is completely removed.

[0047] Furthermore, in the laser scanning microscope 1, the cutoff frequency f of the current-voltage converter 21 ｃ For example, the bandwidth is widened to 5 MHz or higher. In this case, the pulse width W1 of the noise signal to be removed that appears in the target signal ST (sensor output) becomes narrower than the width W2 of each of the four sections. This makes it possible to suppress the noise signal to be removed from appearing across multiple sections, and X-ray noise can be effectively removed. 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 ｃWhen the bandwidth is increased, not only does the pulse width of the measurement signal narrow, but the pulse width of the noise signal also narrows. Therefore, it becomes easier to keep noise pulses within a single interval. As a result, the difference between the interval containing noise pulses and the interval without noise pulses becomes larger, making it possible to determine whether a noise signal has been generated or whether the signal value for each interval has increased overall (i.e., whether the actual amount of incident light itself has increased). Therefore, especially in the case of observations where a predetermined amount of light continues to be incident, it becomes easy to determine whether or not noise reduction processing should be performed on the measurement period. In addition, the larger difference between the interval containing noise pulses and the interval without noise pulses makes it easier to identify the intervals that should be removed. Note that although the noise pulse appears within a single interval in Figure 8, in reality, noise pulses may appear across two intervals. In the noise reduction method according to the embodiment, at least a portion of the noise can be removed even in such cases.

[0048] 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 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, and the signal values ​​in the four intervals are 1, 0, 0, and 0 in order of earliest measurement time. In this example, even in the interval where the measurement signal was measured, the signal value is small, at 1. If the calculation method according to the embodiment described above is applied in this case, the average value of the remaining signal values, excluding the largest maximum signal value of 1 among the four signal values, becomes 0, and the value of pixel P becomes 0. Thus, when the calculation method according to the embodiment is applied in the case of extremely low illuminance, there is a risk that the measurement signal with extremely low intensity 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.

[0049] 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. Figures 11 and 12 are diagrams illustrating the determination process. The processing in the laser scanning microscope 1 will be explained below in accordance with the flowchart in Figure 10.

[0050] 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. Next, the processing unit 25 divides the measurement period into n intervals and calculates the signal value for each interval from the target signal ST (step S3).

[0051] Next, the processing unit 25 determines whether the determination formula is satisfied (step S4). The details of the determination formula will be described later. If the determination formula is satisfied (YES in step S4), the processing unit 25 performs noise reduction processing and calculates the average value of the remaining (n-1) signal values ​​after removing the largest maximum signal value from the n intervals as the output value (value of pixel P) (step S5). On the other hand, if the determination formula is not satisfied (NO in step S4), the processing unit 25 performs normal calculation processing and calculates the average value of the signal values ​​in the n intervals as the output value (value of pixel P) (step S6). After the execution of step S5 or S6, processing for the next measurement period (pixel P) is performed.

[0052] The determination formula is expressed by formula (2). As shown in Figure 11, Wmax is the largest signal value among the n intervals, and Wmin is the smallest signal value among the n intervals.

[0053] As shown in Figure 12(a), the detection efficiency of the vacuum tube sensor 7 is PDE, and the number of electrons incident on the photocathode 12 due to noise is P. ephotocathod 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. Xray Assuming 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 ephotocathod This is expressed by equation (4). Number of electrons P enoise The fluctuation (standard deviation) σ is expressed by equation (5).

[0054] Figure 12(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. The signal quantity (number of charges) Q of the single-pulse signal. single This is expressed by equation (6). Signal quantity Q single This is the integral value (area) of the single-pulse signal shown in Figure 12(b). V hsingle is the pulse height (peak value) of the single-pulse signal. FWHM is the full width at half maximum of the single-pulse signal. The FWHM of the single-pulse signal is the cutoff frequency f of the current-voltage converter 21. ｃ Between FWHM = 1 / (2f ｃ The relationship is as follows. As shown in Figure 12(b), the fluctuation in the pulse height of the noise signal is expressed by equation (7).

[0055] Based on the above, the determination formula in equation (8) is set. As shown in Figure 11, N pixel dwell is the number of sampling points (measurement points) by the AD converter 22 during the measurement period (time per pixel P). n is the number of divisions of the measurement period described above. dwellThis represents the time interval of the measurement period (time per pixel P). Number of sampling points N pixel dwell The sampling frequency S of the AD converter 22 is ｒ and using the time width tdwell, N pixel dwell = t dwell S ｒ This is expressed as follows. Therefore, the determination formula in equation (2) above can be obtained from equation (8). The left side (first value) of equations (2) and (8) is the difference between the maximum signal value Wmax and the minimum signal value Wmin in n intervals. If the maximum signal value Wmax is increased due to the influence of a noise signal, the first value has a value corresponding to the magnitude (pulse height) of the noise signal.

[0056] The right-hand side (second value) of equations (2) and (8) will be explained. The signal quantity Q of a single-pulse signal. single The number of electrons P emitted from the photocathode 12 due to noise. enoise The value obtained by multiplying by (N) corresponds to the signal strength of the noise signal. pixel dwell By dividing by ( / n), a value corresponding to the signal value per section divided into n parts is calculated. By comparing this value with the first value, it is possible to determine whether or not noise signals are included in the target signal ST during the measurement period. In 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 Q. single (P enoise It is based on -6σ, but the second value is Q single (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.

[0057] In step S4 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 S5), and if no noise occurred, a normal calculation process can be performed (step S6).

[0058] 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 the image obtained when the calculation method of the reference example (Figure 7) is applied, Figure 14 corresponds to the image obtained when the calculation method of the above embodiment (without judgment processing) is applied, and Figure 15 corresponds to the image obtained when the calculation method of the above 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.

[0059] 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 14(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]

[0060] In the signal processing circuit C used in the photodetector A of the laser scanning microscope 1, the processing unit 25 divides the measurement period into n intervals, calculates the signal value in each of the n intervals from the target signal ST, and calculates the output value for the measurement period from the signal values ​​in the n intervals. Furthermore, when the processing unit 25 calculates the output value for the measurement period, it is configured to perform noise reduction processing so that the magnitude of the largest maximum signal value Wmax among the signal values ​​in the n intervals does not affect the magnitude of the output value. This makes it possible to calculate the output value for the measurement period after removing high-power noise (X-ray noise in the above example) as needed. In other words, since the noise reduction processing is performed at the level of numerical data, namely 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).

[0061] 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.

[0062] In the noise reduction process, the processing unit 25 calculates the average value of the remaining signal values ​​after excluding the maximum signal value Wmax from the signal values ​​in n intervals as the output value for the measurement period. This allows the output value for the measurement period to be calculated from the signal values ​​in n intervals in a way that the magnitude of the maximum signal value Wmax does not affect the magnitude of the output value.

[0063] Cutoff frequency f of the current-voltage converter 21 ｃ However, the pulse width of the noise signal to be removed that appears in the sensor output is set to be narrower than the width of each of the n intervals. This suppresses the appearance of the noise signal to be removed across multiple intervals, thereby preventing the high-output noise removal process from becoming overly complex.

[0064] When the processing unit 25 calculates the output value during the measurement period, the first value based on the maximum signal value Wmax is the number of electrons P emitted from the photocathode 12 when incident light (e.g., characteristic X-rays) that causes the noise to be removed is incident on the photocathode 12. enoise The electron number fluctuation σ and the signal quantity Q that appears in the target signal ST when one photoelectron is emitted from the photocathode 12 are considered. single 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 average value of the signal values ​​over n intervals as the output value (steps S4 to S6). This allows noise reduction processing to be performed if noise occurs during the measurement period, and a calculation process to calculate the average value of the signal values ​​over n intervals as the output value if no noise occurs.

[0065] The first value of the determination formula is the value obtained by subtracting the smallest minimum signal value Wmin among the signal values ​​in n intervals from the maximum signal value Wmax. This allows for a suitable determination of whether or not noise occurred during the measurement period.

[0066] The second value of the decision formula is Q single (P enoise It is based on -mσ). This allows for a suitable determination of whether or not noise occurred during the measurement period. In the above embodiment, m is 6. In this case, even when the number of pixels P included in the observed image is extremely large, high-output noise can be suitably removed.

[0067] 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. Furthermore, 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, making it easy to generate high-power noise based on characteristic X-rays. For this reason, it is particularly preferable to apply this disclosure to such a vacuum tube sensor 7, as noise reduction processing is important and easy to perform appropriately.

[0068] The noise reduction method (signal processing method) according to the embodiment includes a processing step of processing a target signal ST corresponding to the 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. In the processing step, the measurement period is divided into n (n is an integer of 2 or more) intervals, the signal value in each of the n intervals is calculated from the target signal ST, and the output value for the measurement period is calculated from the signal values ​​in the n intervals. In the processing step, the output value is calculated from the signal values ​​in the n intervals such that the magnitude of the largest maximum signal value Wmax among the signal values ​​in the n intervals does not affect the magnitude of the output value.

[0069] This disclosure is not limited to the embodiments described above. The high-power noise to be removed is not limited to X-ray noise. Figure 16 is a configuration diagram of a modified laser scanning microscope 1. The laser scanning microscope 1 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 1 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 1. Like X-ray noise, the noise caused by the stimulation light L3 is measured almost simultaneously with the measurement signal. The laser scanning microscope 1 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.

[0070] In the above embodiment, the processing unit 25 calculated the average value of the remaining signal values ​​after excluding the maximum signal value Wmax from the signal values ​​in n intervals as the output value for the measurement period. However, the processing unit 25 may also calculate the median value of the signal values ​​in the n intervals as the output value for the measurement period during the noise reduction process. For example, as in the example in Figure 8, if the signal values ​​in the four intervals are 108, 8, 5, and 2 in order of earliest measurement time, the median value for the four intervals will be 6.5, and the value of pixel P will be 6.5. Thus, although the maximum signal value Wmax has an influence on the selection of the numerical value to be used for the median, the maximum signal value Wmax is the most significant value and is therefore not used when actually deriving the magnitude of the median. In other words, no matter what the magnitude of the maximum signal value Wmax is, it does not affect the magnitude of the median. Therefore, even in this case, the output value can be calculated from the signal values ​​in n intervals in such a way that the magnitude of the maximum signal value Wmax does not affect the magnitude of the output value.

[0071] In the above embodiment, the first value of the determination formula was the value obtained by subtracting the smallest minimum signal value Wmin among the signal values ​​in n intervals from the maximum signal value Wmax. However, the first value may be the value obtained by subtracting the average value of the remaining signal values ​​excluding the maximum signal value Wmax from the maximum signal value Wmax, the median value of the remaining signal values ​​excluding the maximum signal value Wmax from the maximum signal value Wmax, or any one of the remaining signal values. In this case as well, it is possible to suitably determine whether or not noise occurred during the measurement period. Alternatively, the first value may be the maximum signal value Wmax itself. For example, if the measured signal is relatively small, it is possible to determine whether or not noise occurred during the measurement period without subtracting the minimum signal value Wmin corresponding to the magnitude of the measured signal from the maximum signal value Wmax.

[0072] The vacuum tube sensor 7 does not necessarily 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 above embodiment, 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 can be set according to the application. Note that it is necessary to divide the measurement period into n intervals and identify the interval that contains events that show abnormal values ​​such as high-power noise, so the measurement period needs to be of a certain length or longer, and it is preferable that it is at least twice the temporal element of the data shown by the event showing the abnormal value (for example, the pulse width when the electrical output shown by the event showing the abnormal value is converted into a voltage signal). In the above embodiment, the number of divisions n of the measurement period was 4, but the number of divisions n may be an integer of 2 or more, for example it may be 2.

[0073] In the above embodiment, 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.

[0074] In the embodiments described above, an example of the present disclosure being applied to a laser scanning microscope was explained, but the present disclosure is applicable to other configurations, for example, a flow cytometer (flow cytometry) or specimen testing.

[0075] 7...Vacuum tube sensor, 12...Photocathode, 21...Current-voltage converter (current-voltage conversion unit), 25...Processing unit, C...Signal processing circuit, ST...Target signal, Wmax...Maximum signal value, Wmin...Minimum signal value.

Claims

1. A signal processing circuit comprising a processing unit that processes 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, and derives an output value for each predetermined measurement period, wherein the processing unit is configured to perform abnormal value handling processing when dividing the measurement period into n (where n is an integer of 2 or more) intervals, deriving a signal value in each of the n intervals from the target signal, and deriving an output value for the measurement period from the signal values ​​in the n intervals, such that the magnitude of the largest maximum signal value among the signal values ​​does not affect the magnitude of the output value.

2. The signal processing circuit according to claim 1, wherein the processing unit, in the abnormal value handling process, derives the average value of the remaining signal values ​​after excluding the maximum signal value from the signal values ​​in the n intervals as the output value.

3. The signal processing circuit according to claim 1, wherein the processing unit derives the median value of the signal values ​​in the n intervals as the output value in the abnormal value handling processing.

4. The signal processing circuit according to any one of claims 1 to 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 corresponding to the maximum signal value is narrower than the width of each of the n intervals.

5. When the processing unit derives the output value during the measurement period, the first value based on the maximum signal value is the number of electrons P emitted from the photocathode when the incident light corresponding to the maximum signal value is incident on the photocathode. enoise The fluctuations in the number of electrons σ and the signal quantity Q that appears in the target signal when one photoelectron is emitted from the photocathode are given. single A signal processing circuit according to any one of claims 1 to 4, wherein if the value is greater than or equal to the second value based on the above, the abnormal value handling process is executed, and if the first value is smaller than the second value, a derivation process is executed to derive the average value of the signal values ​​in the n intervals as the output value.

6. The signal processing circuit according to claim 5, wherein the first value is the value obtained by subtracting from the maximum signal value the smallest minimum signal value among the signal values ​​in the n intervals, the average value of the remaining signal values ​​in the n intervals excluding the maximum signal value, the median value of the remaining signal values ​​in the n intervals excluding the maximum signal value, and one of the remaining signal values, or the maximum signal value.

7. The second value mentioned above is Q single (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. A light detection device comprising the vacuum tube sensor and the signal processing circuit according to any one of claims 1 to 8.

10. The photodetector according to claim 9, wherein the vacuum tube sensor further comprises an avalanche diode for multiplying electrons from the photocathode.

11. A signal processing method comprising a processing step of processing 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, and deriving an output value for each predetermined measurement period, wherein the processing step divides the measurement period into n (where n is an integer of 2 or more) intervals, derives a signal value in each of the n intervals from the target signal, and derives the output value for the measurement period from the signal values ​​in the n intervals in such a way that the magnitude of the largest maximum signal value among the signal values ​​in the n intervals does not affect the magnitude of the output value.

Images