JP7174993B2 - Micro-tomography visualization device and method - Google Patents

Description

TECHNICAL FIELD The present invention relates to an apparatus and method for tomographically visualizing a predetermined physical quantity in an object to be measured.

In recent years, clinical application of optical coherence tomography (hereinafter referred to as "OCT") has been promoted for further development of medical diagnostic technology. OCT is a tomographic imaging method using low-coherence optical interference, and can visualize the morphological distribution of living tissue and the like with high spatial resolution on a microscale. In addition, the acquisition rate of two-dimensional OCT is higher than the video rate and has high temporal resolution. Taking advantage of such advantages of OCT, methods for tomographically visualizing the mechanical properties, hemodynamics, and the like of living tissue have also been proposed (for example, Patent Document 1).

WO2017/010461

By the way, optical mechanisms such as an optical scanner are arranged in the optical system of OCT, and the higher the control resolution of these mechanisms, the clearer the OCT image can be obtained. On the other hand, even if the resolution of the OCT image is increased, it is necessary to separately reduce the noise caused by the characteristics of the optical mechanism.

SUMMARY OF THE INVENTION The present invention has been made in view of such problems, and one of its purposes is to reduce system noise caused by characteristics of an optical mechanism and the like when generating an OCT image.

One aspect of the present invention is a micro-tomographic visualization device that performs tomographic visualization of a predetermined physical quantity in a measurement object. This device consists of a light source, a beam splitter that divides the light from the light source into a sample arm that passes through the object to be measured and a reference arm that passes through a reference mirror, and a beam splitter that directs the light guided by the sample arm in the depth direction of the object to be measured. A depth direction scanning unit that performs an A scan to scan, a lateral direction scanning unit that is driven to perform a B scan by shifting the axis of the A scan in a direction perpendicular to the depth direction, and an object reflected by the object to be measured A photodetector that detects interference light in which light and reference light reflected by a reference mirror are superimposed, and an optical interference signal that is input via the photodetector while controlling a depth direction scanning unit and a lateral direction scanning unit. and a processing unit for calculating the tomographic distribution of the physical quantity in the measurement object, and a display device for displaying the calculated physical quantity in a tomographic visualization manner. The processing unit intermittently drives the lateral scanning unit and acquires the optical interference signal while the lateral scanning unit is stopped.

Another aspect of the present invention is a micro tomographic visualization method for tomographically visualizing a predetermined physical quantity in an object to be measured by using optical coherence tomography. This method includes a scanning step of repeatedly performing an A-scan, in which light is scanned in the depth direction of the object to be measured, while shifting it by one line in a direction perpendicular to the depth direction, a sampling step of sampling optical interference data by the A-scan, A calculation step of calculating a tomographic distribution of a physical quantity in a measurement object based on the sampled optical interference data, and a display step of visualizing the physical quantity in the measurement object tomographically. In the sampling step, the sampling of the optical interference data is stopped while the A-scan is shifted by one line in the direction perpendicular to the depth direction.

Yet another aspect of the present invention is also a micro-tomographic visualization method. In this method, an A-scan for scanning light in the depth direction of the object to be measured is repeatedly performed while shifting one line at a time in a direction perpendicular to the depth direction, and a set number of lines of A-scan data for generating a two-dimensional tomographic image is obtained. , a phase difference calculation step of sequentially calculating the autocorrelation for the A scan data of two adjacent lines and calculating the phase difference every two lines, and the phase difference of each line based on the phase difference every two lines A noise calculation step of calculating system noise, a noise removal step of removing system noise from the phase difference calculated between each two lines, and a Doppler modulation frequency of calculating a Doppler modulation frequency based on the phase difference after removing the system noise A calculation step, a displacement speed calculation step of calculating the displacement speed based on the Doppler modulation frequency, and a display step of displaying the tomographic distribution of the physical quantity based on the displacement speed.

According to the present invention, it is possible to reduce system noise caused by the characteristics of the optical mechanism when generating an OCT image.

1 is a diagram schematically showing the configuration of a micro-tomographic visualization device according to an example; FIG. 4 is a timing chart showing sampling processing of optical interference data; FIG. 10 is a diagram showing the effect of reducing galvanometer drive noise; FIG. 10 is a diagram showing the effect of reducing galvanometer drive noise; FIG. 4 is a diagram showing system noise reduction processing; FIG. 4 is a diagram showing system noise reduction processing; FIG. 4 is a diagram showing system noise reduction processing; FIG. 4 is a diagram showing system noise reduction processing; 4 is a flowchart showing the flow of micro-tomographic visualization processing executed by a control calculation unit; It is a figure showing the 1st experimental result. FIG. 10 depicts the method and results of a second experiment; FIG. 10 depicts the method and results of a second experiment; FIG. 10 depicts the method and results of a second experiment; FIG. 10 depicts the method and results of a second experiment;

One embodiment of the present invention is a micro-tomographic visualization device using OCT. This apparatus includes a light source, a beam splitter, a depth direction scanning unit, a horizontal direction scanning unit, a photodetector, a processing unit, and a display device, and visualizes predetermined physical quantities in a measurement object tomographically. The “object to be measured” may be a living tissue such as skin or cartilage, or a regenerated tissue (tissue composed of cultured cells) such as regenerated skin or regenerated cartilage. Alternatively, it may be a material having a reflecting structure (interface) inside.

The optical system of this device is provided with a sample arm and a reference arm. A "beam splitter" may include a coupler. The depth direction scanning unit performs a so-called A scan in which the light guided to the sample arm is scanned in the depth direction of the object to be measured. The “depth direction scanning unit” may be one that performs A-scan by mechanical scanning driven by a reference mirror. Alternatively, the A-scan may be executed by software scanning, such as inverse Fourier transform of a spectral interference signal using a spectrometer, or inverse Fourier transform of a spectral interference signal obtained by sweeping the wavelength of a laser emitted from a light source. When TD-OCT (Time Domain OCT) is employed, the "depth direction scanning unit" may be an optical scanner arranged on the reference arm. When SD-OCT (Spectral Domain OCT) is employed, the “depth direction scanning unit” may be a spectroscope. When SS-OCT (Swept Source OCT) is adopted, the "depth direction scanning unit" may be a wavelength swept light source. The “horizontal direction scanning unit” may be an optical scanner that performs optical scanning using various mirrors such as a galvanomirror, a resonant mirror, and a polygon mirror.

As shown in an embodiment described later, the first optical scanner arranged on the reference arm may be a resonant scanner, and the second optical scanner arranged on the sample arm may be a galvanometer scanner. An A-scan is performed by driving the first optical scanner to obtain one-dimensional scanning data in the depth direction (also referred to as "A-scan data"). By driving the second optical scanner for each A scan, a B scan including scanning in the depth direction and vertical direction (horizontal direction) is performed to obtain two-dimensional scanning data (also referred to as "B scan data"). .

The object light from the sample arm and the reference light from the reference arm are combined (superimposed) to form interference light, which is detected by the photodetector. This interference light is input to the processing section as an optical interference signal. The processing unit intermittently drives (step drives) the optical scanner (second optical scanner), and stops sampling of the optical interference signal (A scan data) during the driving of the optical scanner. In other words, acquisition of the optical interference signal is performed while the optical scanner is stopped. Stop the optical scanner during acquisition of the optical interference signal. Therefore, the acquired optical interference signal is less likely to be contaminated with noise (also referred to as “optical scanner driving noise”) associated with driving the optical scanner (second optical scanner). That is, according to this aspect, optical scanner driving noise can be reduced.

The processing unit calculates a predetermined physical quantity caused by deformation or displacement of the internal tissue of the measurement target in association with the position of the tomography to be measured, and calculates the tomographic distribution of the physical quantity based on the calculation result. When the object to be measured is a living tissue, the “physical quantity” may be hemodynamics (blood velocity, etc.) or the flow of interstitial fluid (water permeability). Alternatively, it may be viscoelastic.

The depth direction scanning unit may include a drive circuit for reciprocatingly rotating the reference mirror, and an output circuit for outputting a pulse signal synchronized with the rotation of the reference mirror. A processing unit obtains a trigger signal based on the pulse signal. The trigger signal may be a rectangular pulse that rises when the reference mirror starts rotating in one direction and falls when it starts rotating in the other direction. The output circuit may generate a trigger signal based on the pulse signal and output it to the processing section. Alternatively, the processing unit may generate the trigger signal based on the pulse signal received from the output circuit.

The processing unit uses one of the rise and fall of the trigger signal as a drive trigger to start driving the optical scanner, and uses the other as a sampling trigger to start acquiring an optical interference signal (A scan data). The optical scanner stops at or before the sampling trigger turns on, and resumes driving at the same time the trigger signal turns on again. Step drive is thus realized. A single sampling of A-scan data is completed at or before the drive trigger is turned on. With such control, sampling of A-scan data can be stopped while the optical scanner is being driven.

If the depth-direction scanning unit is a resonant scanner, system noise occurs during A-scan execution. This system noise includes noise caused by driving the resonant scanner and noise caused by response delays (time constants) of optical devices and control devices. In addition, it may include instability of the phase difference depending on the optical system and fluctuations such as body movement of the measurement object. Therefore, the processing unit removes the system noise in the arithmetic processing of the tomographic distribution of the physical quantity. Specifically, the processing unit may calculate the autocorrelation in a predetermined range in the depth direction of the continuously acquired A-scan data, and calculate the phase difference based on the autocorrelation. Then, system noise may be calculated based on the calculated phase difference.

Specifically, the processing unit may sequentially calculate the autocorrelation of the A-scan data of two adjacent lines, and calculate the phase difference for each two lines. Auto-correlation may be Auto-Correlation Integral in which the integration range is set to a predetermined range in the depth direction. Details of this will be described later. The processing unit calculates an area average phase difference for a predetermined high-rigidity area in a predetermined line section of three lines or more including two lines and less than the set number of lines. The "high-rigidity region" may be set in advance as a region in which rigid body displacement is performed or estimated. For example, if the measurement target is skin, the epidermis region may be set as the high-rigidity region. Alternatively, it may be set as a region in which the multiplied correlation value is equal to or greater than the reference value. Then, the system noise for each line may be calculated by subtracting the area average phase difference from the phase difference for every two lines. Since system noise occurs like shot noise in each line, it is canceled and reduced in the process of calculating the area average phase difference. This is used inversely to estimate the system noise by subtracting the area average phase difference from the phase difference between two lines.

The processing unit may remove system noise from the phase difference calculated between each two lines for the lines corresponding to the predetermined line section. Then, the Doppler modulation frequency may be calculated based on the phase difference after removing the system noise, and the displacement speed may be calculated based on the Doppler modulation frequency.

Also, a micro-tomography visualization program using the above technology may be constructed. This program has a function of repeatedly executing an A-scan that scans light in the depth direction of the object to be measured by shifting it line by line in the direction perpendicular to the depth direction, a function of sampling optical interference data by the A-scan, and a function of A-scan. is shifted by one line in the direction perpendicular to the depth direction, a function of stopping sampling of the optical interference data, a function of calculating the tomographic distribution of the physical quantity in the measurement target based on the sampled optical interference data, and a function of tomographically visualizing the physical quantity in the object to be measured can be realized by a computer. This program may be recorded on a computer-readable recording medium.

Furthermore, the following micro-tomographic visualization program may be constructed. This program repeats the A-scan, which scans light in the depth direction of the object to be measured, while shifting it by one line in the direction perpendicular to the depth direction, and sets the number of lines of A-scan data to generate a two-dimensional tomographic image. , a function to sequentially calculate the autocorrelation for the A-scan data of two adjacent lines, a function to calculate the phase difference every two lines, and a function to calculate the system noise of each line based on the phase difference every two lines. a function to remove system noise from the phase difference calculated between each two lines; a function to calculate the Doppler modulation frequency based on the phase difference after removing the system noise; a function to calculate the Doppler modulation frequency based on the Doppler modulation frequency; and a function of displaying the fault distribution of the physical quantity based on the displacement velocity can be realized by a computer. This program may be recorded on a computer-readable recording medium.

This program further includes a function of calculating the area average phase difference for a predetermined high-rigidity area in a predetermined line section of three lines or more including two lines and less than the set number of lines, and a function of calculating the area average phase difference from the phase difference every two lines. A computer realizes a function of calculating the system noise of each line by subtracting the phase difference, and a function of removing the system noise from the phase difference calculated between each two lines for lines corresponding to a predetermined line section. can be made This program may be recorded on a computer-readable recording medium.

Hereinafter, examples embodying the present embodiment will be described in detail with reference to the drawings.
[Example]
FIG. 1 is a diagram schematically showing the configuration of a micro-tomographic visualization apparatus according to an embodiment. The apparatus of the present embodiment performs tomographic measurement and visualization of blood flow velocity in living tissue on a microscale. OCT detection is used for this tomographic measurement.

As shown in FIG. 1, the OCT apparatus 1 includes a light source 2, a sample arm 4, a reference arm 6, optical mechanisms 8 and 10, a photodetector 12, a processor 14 and a display device 16. Each optical element is connected to each other by an optical fiber. Although the illustrated example shows an optical system based on a Michelson interferometer, a Mach-Zehnder interferometer or other optical system may be employed. The OCT of this embodiment is implemented as TD-OCT (Time Domain OCT).

The light source 2 is a broadband light source composed of a Super Luminescent Diode (hereinafter referred to as "SLD"). Light emitted from the light source 2 is split by the coupler 18 , one of which is guided to the sample arm 4 and the other to the reference arm 6 . The coupler 18 has a function of splitting the light from the light source 2 toward the sample arm 4 and the reference arm 6 and a function of combining and interfering the lights returned from the sample arm 4 and the reference arm 6 respectively. have.

The optical mechanism 8 includes a collimator lens 30, a galvanometer scanner 32 and an objective lens . The galvanometer scanner 32 includes two-axis galvanometer mirrors and a galvanometer drive circuit 36 for driving them. The objective lens 34 is arranged to face an object to be measured (hereinafter referred to as "object W"). The target W is a biological tissue such as skin in this embodiment. Hereinafter, the depth direction of the object W will be described as the z-direction, and the directions perpendicular thereto as the x- and y-directions.

The light that has passed through the coupler 18 is guided to the galvanometer scanner 32 via the collimator lens 30, scanned in the x-direction and the y-direction, and irradiated onto the target W. This light is reflected by the surface and cross section of the object W to become backscattered light (reflected light). This reflected light is guided to the coupler 18 via the polarization controller 20 as object light. The polarization controller 20 adjusts the polarization state of the object light entering the coupler 18 .

The optical mechanism 10 is an RSOD (Rapid Scanning Optical Delay Line) mechanism. In the present embodiment, the RSOD employs a single-pass type in which the light is irradiated to the diffraction grating 42 described later once each time. Optical arrangement 10 includes collimator lens 40 , diffraction grating 42 , curved mirror 44 and resonant scanner 46 .

The resonant scanner 46 includes a reference mirror 50 , an actuator 52 that rotates (excites) the reference mirror 50 , a resonant drive circuit 54 that drives the actuator 52 , and a speed sensor 56 that detects the rotation speed of the reference mirror 50 . The resonant scanner 46 is an optical scanner that enables high-speed scanning using a driving coil and mechanical resonance. The speed sensor 56 may be a magnetic sensor including a Hall element or the like, and outputs an analog signal (sine wave signal) corresponding to the rotation speed of the reference mirror 50 .

Light passing through coupler 18 is guided to diffraction grating 42 via collimator lens 40 . This light is split into wavelengths by the diffraction grating 42 and focused on different positions on the reference mirror 50 by the curved mirror 44 . Rotating the reference mirror 50 at a minute angle enables high-speed optical path scanning and frequency modulation. Reflected light from the reference mirror 50 is guided to the coupler 18 via the polarization controller 22 as reference light. The polarization controller 22 adjusts the polarization state when the reflected reference light enters the coupler 18 again. The object light and the reference light are combined (superimposed) by the coupler 18 and the interference light is detected by the photodetector 12 . In a modified example, the light passing through the diffraction grating 42 may be focused on the reference mirror 50 by a lens instead of the curved mirror 44 .

Photodetector device 12 includes photodetector 60 and filter 62 . The interference light obtained by passing through the coupler 18 is detected as an optical interference signal by the photodetector 60 . This optical interference signal has its noise reduced by the filter 62 and is input to the processing unit 14 . Part of the interfering light is directly input to the photodetector 60 via the circulator 24 . As a result, the in-phase noise superimposed on the optical interference signal is reduced, and after the optical interference signal is amplified, only the signal in the required frequency band is taken out by the filter 62 .

The processing unit 14 includes a control calculation unit 70 , an A/D converter 72 and a D/A converter 74 . The optical interference signal that has passed through the photodetector 12 is input to the control calculator 70 via the A/D converter 72 .

The control calculation unit 70 has a CPU, ROM, RAM, hard disk, and the like. The control calculation unit 70 controls the entire optical system and performs calculation processing for image output by OCT using these hardware and software. A command signal from the control calculation unit 70 is input to each drive circuit for the light source 2, the optical mechanisms 8 and 10, etc. via the D/A converter 74. FIG. As will be described later, the detection signal (synchronization signal) of the speed sensor 56 is input to the processing section 14 via the resonant drive circuit 54 .

The control calculation unit 70 processes the optical interference signal input to the photodetector 12 and obtains a tomographic image of the target W by OCT. Then, based on the tomographic image data, the tomographic distribution of the physical quantity (blood velocity in this embodiment) inside the target W is calculated by a method described later.

The display device 16 is composed of, for example, a liquid crystal display, and displays the internal physical quantity (blood velocity) of the object W calculated by the control calculation unit 70 on the screen in a tomographic visualization manner.

A method of calculating the blood flow velocity will be described in detail below.
As described above, in OCT, the object light (reflected light from the object to be measured) that has passed through the sample arm 4 and the reference light that has passed through the reference arm 6 are combined and detected as an optical interference signal by the photodetector 12. . The control calculation unit 70 can acquire this optical interference signal as a tomographic image of the target W based on the intensity of the interference light.

(basic arithmetic processing)
By detecting the Doppler-modulated signal by OCT, the blood flow velocity distribution of the skin tissue can be calculated. In this embodiment, as described above, the depth direction (z direction) scanning method based on the RSOD method is adopted. Hilbert transform and neighborhood autocorrelation method are applied for high-resolution, high-accuracy, and real-time velocity detection.

ここで、λ_ｃはビームの中心波長であり、Δλはビームの半値全幅である。 The coherence length _lc , which is the resolution in the optical axis direction (depth direction) of OCT, is determined by the autocorrelation function of the light source. Here, the coherence length l _c is defined as the half width at half maximum of the comprehensive line of the autocorrelation function, and can be expressed by the following equation (1).

where _λc is the center wavelength of the beam and Δλ is the full width at half maximum of the beam.

ここで、ｄは集光レンズに入射するビーム径、ｆは集光レンズの焦点距離である。 On the other hand, the resolution in the direction perpendicular to the optical axis (beam scanning direction) is set to 1/2 of the beam spot diameter D based on the condensing performance of the condensing lens. The beam spot diameter ΔΩ can be expressed by the following formula (2).

Here, d is the beam diameter incident on the condenser lens, and f is the focal length of the condenser lens.

In this example, the center wavelength λ _c =1310 nm, the full width at half maximum Δλ=100 nm, and the coherence length l _c =7.56 μm. The beam spot diameter ΔΩ=41.0 μm, and the resolution in the xy direction was Δx=Δy=20.5 μm. The sampling frequency of A-scan data by the A/D converter 72 is set to 20 MHz. A tomographic image is displayed by averaging sampling signals at 7.56 μm/pixel based on the resolution in the z direction. In this embodiment, the scanning distance in the z-direction was set to 1162 μm, and the number of scans Jset in the x-direction was set to 400 (that is, 400 A-scans). In modifications, these values may be changed as appropriate.

ここで、Ｉ_ｉｎｃは測定対象への照射光強度、ｒ(z)は測定対象内部の奥行きｚ座標における反射係数、Ｇ(z)はコヒーレンス関数である。ｆ_ＲＳＯＤは参照鏡走査（Ａスキャン）によって生じるドップラー変調周波数、ｆ_ｄは対象Ｗの内部の組織変動または流動によって生じるドップラー変調周波数、ｖは参照鏡走査速度である。なお、「ドップラー変調周波数」とは、光の反射対象が変位したり、対象の屈折率が時間変化することで生じ、「ドップラー効果によりシフトする周波数」を意味する。 The optical interference signal I(z) obtained by OCT is obtained by the convolution integral shown in Equation (3) below.

Here, I _inc is the intensity of light irradiated onto the object to be measured, r(z) is the reflection coefficient at the depth z coordinate inside the object to be measured, and G(z) is the coherence function. _fRSOD is the Doppler modulation frequency caused by the reference mirror scan (A-scan), _fd is the Doppler modulation frequency caused by tissue variations or flows within the object W, and v is the reference mirror scan velocity. The "Doppler modulation frequency" means "a frequency shifted by the Doppler effect", which is caused by the displacement of a light reflecting object or the temporal change of the refractive index of the object.

Fast Fourier transform is applied to the optical interference signal I(z), and the Hilbert transform of the following equation (2) is applied to acquire the spectrum Ŝ(f) with a π/2 phase delay in the frequency domain. An analytic signal Γ(t)=s(t)+iŝ(t) is obtained by subjecting this spectrum Ŝ(f) to an inverse Fourier transform.

The square root (instantaneous amplitude) of the sum of the squares of the real part s(t) and the imaginary part Ŝ(t) of this analytic signal gives the signal intensity (signal envelope) of the OCT tomographic image. By using the Hilbert transform, not only the instantaneous amplitude but also the instantaneous phase can be obtained. The instantaneous frequency can also be calculated from the time derivative of the instantaneous phase. Therefore, it is particularly effective when processing a high-frequency modulated signal as in this embodiment. As a result, the detection resolution of the Doppler modulation frequency can be increased, and highly accurate and real-time detection can be realized.

ここで、ΔＴは光干渉信号の取得時間間隔、つまりＡスキャンの時間間隔を表している。Ａ(t)は光干渉信号の振幅（つまり後方散乱強度）を表す。隣接した光干渉信号の振幅は等しいと仮定し、Ａ(t)＝Ａ(t+ΔT)とする。 Here, the neighborhood autocorrelation method is used to obtain in real time the Doppler modulation frequency f _d caused by variations inside the object W. FIG. That is, regarding the optical interference signal (RF interference signal) obtained by depth z-direction scanning (A-scan), the adjacent j-th and j+1-th analytic signals in the x-direction scanning are Γ _j and Γ _j+1 , respectively. At this time, Γ _j+1 is represented by the following equation (5).

Here, ΔT represents the acquisition time interval of the optical interference signal, that is, the A-scan time interval. A(t) represents the amplitude of the optical interference signal (that is, the backscatter intensity). Assume that the amplitudes of adjacent optical interference signals are equal, and let A(t)=A(t+ΔT).

Since the scanning (rotational driving) of the reference mirror 50 by the resonant scanner 46 is periodic, it is assumed that the Doppler modulation frequency _fRSOD is constant. At this time, using the phase difference φ _j derived by the adjacent autocorrelation between the analytic signals Γ _j and Γ _j+1 , the Doppler modulation frequency f _d can be calculated from the following equation (6). Note that Γ _j ^* is the complex conjugate of Γ _j . The following formula (6) utilizes the fact that the instantaneous phase can be detected by the Hilbert transform. Furthermore, the detection accuracy of the Doppler modulation frequency _fd can be improved by performing ensemble averaging processing on the phase differences φ _i,j for N lines of A scan and pixel averaging (averaging for each pixel) in the z direction.

ここで、λ_ｃは光源の中心波長、ｎ_ｔは対象Ｗの内部の屈折率、θは血流の方向とビームの入射方向とがなす角度である。 By calculating the following equation (7) using this Doppler modulation frequency _fd , the blood flow velocity _vd can be obtained.

Here, _λc is the central wavelength of the light source, _nt is the refractive index inside the object W, and θ is the angle between the direction of blood flow and the incident direction of the beam.

(noise removal processing)
Although the above basic arithmetic processing enables tomographic visualization of the blood flow velocity, there is room for improvement in that the tomographic image contains noise due to various factors. In this embodiment, it is intended to sharpen the image by reducing such noise. Specifically, the noise caused by driving the galvanometer scanner and the noise caused by driving the resonant scanner are targeted for reduction.

(1) Reduction of Galvanometer Drive Noise When acquiring an OCT tomographic image, B scan (two-dimensional scan) is realized by repeatedly executing A scan (one-dimensional scan) in the z direction while shifting it in the x direction. A three-dimensional image can also be obtained by repeating the B scan while shifting it in the y direction. A one-dimensional image in the depth direction (depth direction, z direction) of the object W is an A-scan image, and a two-dimensional image obtained by arranging a plurality of A-scan images in a plurality of lines in the depth direction and the vertical direction is a B-scan image. is. Hereinafter, the sampling data obtained by the A-scan will also be referred to as "A-scan data", and the sampling data obtained by the B-scan will also be referred to as "B-scan data".

According to the inventors' verification, it was found that noise is generated by performing x-direction scanning for B-scan during execution of A-scan (hereinafter, this noise is also referred to as "galvano drive noise"). Therefore, in this embodiment, the galvanometer scanner 32 is intermittently driven (step-driven), and the A-scan data is sampled while the galvanometer mirror is stopped.

FIG. 2 is a timing chart showing sampling processing of optical interference data. FIG. 2A shows signal processing executed by the processing unit 14, and shows, from the top, a resonant control signal, a resonant velocity signal, a resonant clock signal, a data acquisition signal, an A/D trigger signal, and a galvano control signal. FIG. 2(B) is an enlarged view of part A in FIG. 2(A).

As shown in FIG. 2A, the control calculation unit 70 outputs a resonant control signal to the resonant drive circuit 54 when executing the OCT processing to drive the resonant scanner 46 (that is, excite the reference mirror 50). Along with this, the speed sensor 56 detects the rotational speed of the reference mirror 50 and outputs the detection signal to the resonant drive circuit 54 . Resonant driving circuit 54 outputs a synchronization signal based on the detection signal to D/A converter 74 . This synchronization signal includes a resonant velocity signal and a resonant clock signal.

The resonant speed signal is an analog signal (sine wave signal) output from speed sensor 56 . On the other hand, the resonant clock signal is a digital signal generated from the analog signal by the resonant drive circuit 54 . Specifically, it is a rectangular wave signal that rises when the rotation speed of the reference mirror 50 switches from negative to positive (from one direction to the other direction) and falls when it switches from positive to negative (from the other direction to one direction). be. In this embodiment, since the drive frequency of the resonant scanner 46 is 4 kHz, the period of the resonant clock signal is approximately 250 μsec.

In this embodiment, the D/A converter 74 outputs (bypasses) only the resonant clock signal among these synchronization signals to the A/D converter 72 . In a modification, the resonant drive circuit 54 may output only the resonant clock signal as the synchronizing signal. The resonant clock signal may be directly output to each of D/A converter 74 and A/D converter 72 .

The control calculation unit 70 outputs the data acquisition signal to the A/D converter 72 in synchronization with the acquisition timing of the optical interference signal. The A/D converter 72 takes in the optical interference signal while the data acquisition signal is turned on, and outputs it to the control calculation section 70 . A resonant clock signal can also be used as the A/D trigger signal.

The control calculation unit 70 samples optical interference data (optical interference signal) input from the photodetector 12 via the A/D converter 72 . As shown in FIG. 2B, the D/A converter 74 outputs a galvano control signal to the galvano drive circuit 36 with the rising edge of the resonant clock signal (A/D trigger signal) as a trigger, and outputs a galvano control signal for x-direction scanning. drive the galvanometer mirrors of The contact angle (rotational angle) of the galvanometer mirror is controlled according to the output value of the galvanometer control signal. The control calculation unit 70 also starts sampling the optical interference data triggered by the fall of the A/D trigger signal.

While the reference mirror 50 rotates in one direction, the x-direction scanning galvanomirror is driven, and after the x-direction scanning position has moved by one A-scan line, the galvanomirror stops being driven. After that, while the reference mirror 50 rotates in the other direction, optical interference data (A scan data) for one A scan is sampled. That is, the galvano-scanner 32 is intermittently step-driven, and sampling of optical interference data is performed while the galvano-scanner 32 is stopped. Therefore, it is possible to prevent or suppress the superimposition of the galvano-driven noise on the OCT tomographic image.

By the way, as shown in FIG. 2B, there is a time constant in the rise of the galvano control signal. Therefore, in the embodiment, sampling is started after a predetermined time delay from the output of the signal. As a result, the galvanomirror can be stopped after one line of scanning in the x direction has been completed, and optical interference data can be obtained in a stable state. Needless to say, the rotational drive cycle of the resonant scanner 46 is longer than the sum of the time constant of the galvano control signal (mechanical delay of the galvano scanner) and the time required to execute one A scan. In this embodiment, the galvano mirror is stopped before the galvano control signal falls.

The control calculation unit 70 turns off the data acquisition signal each time one B scan is completed, and executes calculation processing based on the sampled optical interference data. The period during which the data acquisition signal is turned on is a data acquisition period T1 for intermittently acquiring A-scan data for B-scan. A period during which the data acquisition signal is off is a signal acquisition waiting period T2. When the OCT tomographic image is to be three-dimensionally displayed, the waiting period T2 is used to drive the galvanomirror for y-direction scanning.

3 and 4 are diagrams showing the effect of reducing galvano drive noise. FIG. 3(A) shows the calculation result of this embodiment in which the galvanometer scanner is step-driven as described above. FIG. 3B shows the calculation result of a comparative example in which the galvanometer scanner is linearly driven at a constant speed. In the linear drive of the comparative example, sampling of optical interference data is also performed while the galvanometer scanner 32 is being driven. The upper part of each figure shows the OCT tomographic image, and the lower part shows the tomographic distribution of the blood flow velocity calculated based on the tomographic image. FIG. 4 shows variations in blood flow velocity calculation results near the epidermis (broken line area) in the lower part of FIG. FIG. 4A shows variations in calculation results according to this embodiment, and FIG. 4B shows variations in calculation results according to a comparative example.

Here, a biological skin tissue simulated material (hereinafter referred to as "bio skin") was set as the object W in the OCT apparatus 1, and the tomographic distribution of the blood flow velocity was calculated. Since there is no blood flow in this bioskin and no external load is applied, the blood flow velocity is essentially zero over the entire fault.

As shown in FIG. 3, according to the present embodiment, a relatively large region in which the blood flow velocity is zero was stably obtained. On the other hand, in the comparative example, a blood flow velocity distribution that should not exist is observed. According to FIG. 4, the standard deviation is suppressed smaller in this example than in the comparative example. In other words, it can be seen that the reduction of galvanometer drive noise according to the present embodiment is effectively reflected in the calculation result of the blood flow velocity.

(2) Reduction of System Noise As described above, the galvanometer scanner 32 is step-driven, and sampling is performed while the drive is stopped, thereby reducing noise. However, noise still remains as shown in FIG. Therefore, when the inventors conducted further verification, it was inferred that system noise was mixed in when the resonant scanner 46 was driven. That is, since the resonant scanner is operated by electromagnetic drive, the scanning cycle thereof fluctuates by several hundred picoseconds due to the occurrence of secondary induction or the like. This is considered to be one factor of system noise. In this embodiment, this system noise is reduced by the following method.

5 to 8 are diagrams showing system noise reduction processing. 5 and 6 show examples of tomographic images obtained in the calculation process. In each figure, the horizontal axis indicates the position in the x direction, and the vertical axis indicates the position in the z direction. 7 and 8 show variations in calculation results. In each figure, the horizontal axis indicates the detected blood flow velocity, and the vertical axis indicates the number of detections. The following description will be made with appropriate reference to FIGS. 5 to 8. FIG.

The example shown in the drawing shows the results of calculating the tomographic distribution of the blood flow velocity by setting the bioskin as the target W in the OCT apparatus 1 . Since this bioskin has no blood flow and no external load is applied, the blood flow rate should be zero.

FIG. 5A shows a B-scan tomographic image acquired by OCT. In this embodiment, a tomographic image is displayed in real time for each A scan. For this reason, although the image is actually displayed gradually from the left side (the position where the x coordinate is zero) to the right side in FIG.

ここで，Ｒ_ｉ，ｊは座標（ｉ，ｊ）に対応する自己相関係数を表している。 In this embodiment, instead of the autocorrelation for each sampling point (hereinafter also referred to as "point autocorrelation") shown in the above equation (6), the integral autocorrelation shown in the following equation (8) (autocorrelation by correlation integration Correlation: hereinafter also referred to as "autocorrelation integral") is calculated. FIG. 5B shows the results of the autocorrelation integration. Here, when calculating the autocorrelation for the A-scan data of two adjacent lines, an integration interval (-t _i /2 ≤ t ≤ t _i /2) is provided in the depth direction (z direction), and the phase difference calculation fluctuation reduce After that, as will be described later, the Doppler modulation frequency f _d at an arbitrary position on the z-coordinate in that integration interval is determined. The degree of noise reduction can be adjusted by setting the integration interval.

Here, R _i,j represents the autocorrelation coefficient corresponding to the coordinates (i,j).

上記式（９）から得られるドップラー変調周波数ｆ_ｄを用いて上記式（７）を演算することにより、血流速度ｖ_ｄを得ることができる。 When obtaining the phase difference φi _,j , ensemble averaging of N lines of A-scan is performed according to the following equation (9), thereby suppressing system noise (described later) that fluctuates like shot noise in each line.

By calculating the above equation (7) using the Doppler modulation frequency _fd obtained from the above equation (9), the blood flow velocity _vd can be obtained.

By the way, when performing the ensemble averaging of the above formula (9), an increase in the number of lines N leads to a decrease in the spatial resolution in the x and y directions and a decrease in the frame rate (that is, the temporal resolution). Therefore, before performing the ensemble averaging, the system noise e _j is estimated from the phase difference φ _i,j of the interference signal between the two lines and removed.

ここで、位相差φ_ｉ，ｊは、上記式（８）および（９）に基づき、２ライン間の自己相関積分にて得られる位相差である。この位相差φ_ｉ，ｊからシステムノイズｅ_ｊを除去することにより位相差φ_ｉ，ｊ ^Ｍを得る。 That is, the phase difference φ _i,j ^M generated by the displacement of the tissue of the target W (blood flow in this embodiment) can be detected from the A-scan data between two lines by the following equation (10).

Here, the phase difference φ _i,j is a phase difference obtained by autocorrelation integration between two lines based on the above equations (8) and (9). A phase difference φ _i,j ^M is obtained by removing the system noise e _j from this phase difference φ _i,j .

ここで、領域平均位相差φ^－ _ｊ ^Ｍは、対象Ｗにおいて剛体変位と仮定できる高剛性領域の位相差を表し、システムノイズのように各ラインにおいてショットノイズのように突発的(ランダム)に発生するノイズがその平均処理で低減されたものである。このため逆に、２ライン間の位相差φ_ｉ，ｊから領域平均位相差φ^－ _ｊ ^Ｍを減算することでシステムノイズｅ_ｊを推定できる。 For estimating the system noise e _j , an area average phase difference φ ⁻ _j ^M obtained by autocorrelation integration between two lines is used as shown in the following equation (11).

Here, the region average phase difference φ ⁻ _j ^M represents the phase difference in the high-rigidity region that can be assumed to be rigid body displacement in the target W, and is generated suddenly (randomly) like shot noise in each line like system noise. , the noise is reduced by the averaging process. Therefore, conversely, the system noise e _j can be estimated by subtracting the area average phase difference φ ⁻ _j ^M from the phase difference φ _i,j between two lines.

A “high-rigidity region” is a region that has higher rigidity than other regions and is subjected to or estimated to undergo rigid body displacement. This high-rigidity region tends to have a higher multiplication correlation value (|R _i |=Π _j=1 ^N |R _ij |) than other regions. For this reason, in this embodiment, for example, a region having a multiplication correlation value of 0.7 or more is defined as a "high-rigidity region". "Rigid body displacement" can be displacement due to body motion, for example. FIG. 5C illustrates the distribution of multiplication correlation values.

S and N represent areas in the z-direction and x-direction specifying the high-rigidity area, respectively, and the area with the area S×N as a window is the area for which the area average phase difference φ _−j ^M is ^to be obtained. That is, the region S means a sampling region set in the z-direction for a high-rigidity region (for example, epidermis in the case of skin), and is represented by the number of pixels (for example, S=5 pixels) in this embodiment. The area N means an area (window width) set in the x direction, and in this embodiment, the number of lines N of the above equation (9) is set. However, the number of lines N (for example, N=5 lines) is set to a value sufficiently smaller than the number of scans Jset in the x direction (the number of A scans for one frame of B scan data) (N<<Jset).

Since the area average phase difference φ ⁻ _j ^M is obtained by moving the area S×N, as shown in the following equation (12), the system noise e _j calculated for each area movement in the x direction is exceeded. It is given by averaging over the wrap area S×(N−1). FIG. 5(D) shows the calculation result of the system noise _ej thus obtained.

By removing the system noise e _j from the phase difference φ _i,j between the two lines according to the following equation (13) and performing ensemble averaging for the A scan N lines, the deformation behavior (displacement speed) inside the object W Calculate the phase difference φ _i,j ^M.

Using the phase difference φ _i,j ^M thus obtained, the Doppler modulation frequency f _d =φ _i,j ^M /2π is obtained, and the blood flow velocity v _d is obtained by calculating the above equation (7). can display its fault distribution. Note that ensemble averaging may be performed using the absolute value of the difference between the phase difference _{φi ,j} and the system noise ej for the above equation (13). When the blood flow has directionality between arteries and veins, it is possible to prevent the phase difference itself from being canceled by ensemble averaging. In addition, since autocorrelation is low in a region where blood flow exists, this tomographic display may be limited to a low autocorrelation region. Specifically, the arithmetic processing of the above formula (13) may be performed for a multiplied correlation value equal to or less than a predetermined value (for example, a region less than 0.7).

FIG. 6A shows the absolute value of the difference between the phase difference φ _i,j and the system noise e _j . FIG. 6B shows the result of calculating the blood flow velocity _vd by performing ensemble averaging of the above equation (13) using the absolute value. FIG. 6(C) shows the tomographic distribution of blood flow velocity _vd obtained for a low correlation region (multiplied correlation value is less than 0.7).

FIGS. 7A and 7B exemplify the case where the blood flow velocity is calculated based on the phase difference distribution before the system noise _ej is subtracted. FIG. 7A shows the case of using the point autocorrelation based on the above equation (6) as a comparative example. FIG. 7B shows a case where autocorrelation integration based on the above equation (8) is used as an example. In both figures, the calculation result with a peak near zero velocity indicates the blood flow velocity, and the calculation result with peaks on both sides indicates the system noise.

As is clear from the comparison of these figures, according to the present example, the blood flow velocity and system noise can be distinguished more clearly than the comparative example. Therefore, when the system noise e _j is subtracted based on the above equation (13), the blood flow velocity v _d can be accurately detected as shown in FIG. 7(C).

FIG. 8 shows the case where the number of lines N is changed for the above equations (11) and (12). FIG. 8A shows the case of N=2, and FIG. 8B shows the case of N=6. By comparing these, it can be seen that the blood flow velocity _vd can be detected with higher accuracy as the number of lines N is increased.

Next, the flow of specific processing executed by the control calculation unit 70 will be described.
FIG. 9 is a flow chart showing the flow of micro-tomographic visualization processing executed by the control calculation unit 70. As shown in FIG. This process is repeatedly executed at a predetermined calculation cycle. The control calculation unit 70 drives and controls the light source 2 and the optical mechanisms 8 and 10, and obtains an optical interference signal by OCT.

The control calculation unit 70 first clears the number of A scans Jscan and the number of acquisition lines J stored in a predetermined area of the RAM to zero (S10, S12). Here, "the number of A-scans Jscan" corresponds to the number of A-scans executed in the process of executing the B-scans. The “acquisition line number J” corresponds to the number of acquisitions of A-scan data counted for each real-time display of the blood flow velocity. Subsequently, one line of A-scan data is read (S14), and the number of A-scan times Jscan and the number of acquired lines J are incremented (S16).

The control arithmetic unit 70 applies a fast Fourier transform to the A-scan data for one line and performs frequency analysis (S18). Subsequently, bandpass filtering is performed so as to correspond to the modulation frequency in the optical mechanism 10 to improve the signal SN ratio (S20), and then Hilbert transform is performed (S22). At this time, if the A scan count Jscan is less than two lines (N in S24), the process returns to S14.

If the A-scan count Jscan is two or more lines (Y in S24), the control operation unit 70 uses the analysis signal obtained by the Hilbert transform in S22 to apply the above formula ( 8) perform the autocorrelation integration based on Also, the phase difference φ _i,j between the two lines is calculated based on the above equation (9) (S26). At this time, if the number of lines J for which the phase difference φ _i,j has been calculated has not reached the set line N (for example, 5 lines) for ensemble averaging (N of S28), the process returns to S14. At this time, each time the acquired line number J is incremented in S16, the two lines (a combination of adjacent A-scan data) subjected to autocorrelation integration are shifted in the x direction.

If the acquired line number J has reached N lines (Y in S28), the control calculation unit 70 calculates the multiplication correlation value |R _i | for every two adjacent lines of the A-scan data for the N lines. (S30). A region where the multiplication correlation value |R _i | is equal to or greater than the reference value |R _i |set (for example, 0.7) is set as a high stiffness region (S×N). Then, for this high-rigidity area, the area average phase difference φ ⁻ _j ^M is calculated based on the above equation (11) (S32), and the system noise e _j is calculated based on the above equation (12) (S34). Subsequently, based on the above equation (13), the system noise e _j is removed from the phase difference φ _i,j between each two lines, and ensemble averaging is performed for the N lines (S36). Thereby, the distribution of the phase difference φ _i,j ^M due to the deformation behavior inside the object W can be calculated.

The control calculation unit 70 calculates the Doppler modulation frequency ^fd using the phase difference φi _,jM (S38), and obtains the displacement velocity _vd by calculating the above equation (7 ₎ (S40). The distribution of the displacement velocity _vd is displayed as a blood flow velocity distribution (S42). At this time, if the number of A-scan times Jscan has not reached the number of lines Jset (400 lines in this embodiment) for one B-scan (N in S44), the process returns to S14. If the number of A scans Jscan has reached the Jset line (Y in S44), this processing is once terminated.

According to this embodiment, the blood flow velocity distribution is sequentially displayed each time the A scan is performed for N lines. The number of lines N is made sufficiently smaller than the number of lines Jset for one B scan (N<<Jset).

Next, the effects of this embodiment will be described.
The results of two types of experiments conducted to verify the noise reduction effect of the above-described micro-tomographic visualization processing will be described below. In these experiments, in order to consider the influence of the motion of the object W, a load mechanism (piezo actuator) (not shown) was arranged in parallel with the optical mechanism 8 to apply a periodic load to the object W. Specifically, a bioskin was used as the target W, and a piezoelectric element was brought into contact with the surface of the bioskin, and a sinusoidal driving force having a one-sided amplitude of 40 μm and a frequency of 0.25 Hz was applied.

(Verification experiment 1)
In verification experiment 1, the average value (average displacement velocity) of the z-direction displacement velocity (blood flow velocity) inside the object W was calculated while controlling the load mechanism. Since the object W is BIOSKIN, its displacement speed should be equivalent to the average displacement speed (about 58 μm/s) of the surface caused by the load mechanism.

FIG. 10 is a diagram showing the results of the first experiment. FIG. 10(A) shows the case where the point autocorrelation based on the above equation (6) is used as a first comparative example and the system noise e _j is not removed. FIG. 10B shows a second comparative example in which the autocorrelation integration based on the above equation (8) is used and the system noise e _j is not removed. FIG. 10(C) shows the case where the autocorrelation integration based on the above equation (8) is used as this embodiment and the system noise e _j is removed. The left side of each figure shows the case where the set number of lines N is 11 lines, and the right side shows the case where it is 5 lines. In each figure, the horizontal axis indicates the z-direction position, and the vertical axis indicates the calculated displacement velocity (blood flow velocity).

A comparison of FIGS. 10A and 10B shows that the use of autocorrelation integration can more effectively suppress variations in displacement speed than point autocorrelation. On the other hand, in either case, the variation can be made smaller by increasing the set number of lines N, that is, the number of lines for which the ensemble average is taken.

Further, according to the present embodiment shown in FIG. 10C, it is possible to further suppress variations in displacement speed. Even if the set number of lines N is set small, the difference in variation can be kept small. Also, the average value of the detected displacement velocities well agrees with the true value (high accuracy). In other words, it can be seen that even if the set number of lines N is reduced, the displacement speed can be obtained with high accuracy. This means that in addition to real-time processing by OCT detection, it is convenient for improving the spatial resolution of displacement velocity detection.

(Verification experiment 2)
In verification experiment 2, the result of calculating the fault distribution of the displacement velocity at the time when the displacement velocity of the surface of the object W is greatly changed by the load mechanism is shown. Since the object W is BIOSKIN, its displacement speed should be equal to the displacement speed of the surface by the load mechanism (gradually decreased from 65 μm/s to about 35 μm/s).

11-14 are diagrams representing the method and results of the second experiment.
FIG. 11(A) shows the control process of the load device. The horizontal axis in the figure indicates the passage of time, and the vertical axis indicates the displacement speed by the load mechanism. FIGS. 11(B) and (C) illustrate OCT images obtained during the course of the experiment. In FIG. 11A, the sinusoidal waveform represents the displacement of the piezoelectric element, and the rectangular pulse represents the frame acquisition timing for one B scan. In this experiment, calculation results are shown for the frame (B-scan image) at the time indicated by the dotted line frame, that is, the frame in which the displacement speed of the target W changes greatly.

12 to 14 show calculation results obtained during the course of the experiment. FIG. 12A shows a B-scan tomographic image acquired by OCT. FIG. 12B shows the phase difference φ _i,j obtained by autocorrelation integration. FIG. 12(C) shows the area average phase difference φ ⁻ _j ^M set near the surface of the object W. FIG. FIG. 13(A) shows a difference image obtained by subtracting the area average phase difference φ ⁻ _j ^M from the phase difference φ _i,j , and FIG. 13(B) shows the calculation result of the system noise e _j based on the difference image. By removing the system noise shown in FIG. 13(B) from the phase difference distribution shown in FIG. 12(B), the distribution of phase differences φ _i,j ^M due to the displacement velocity shown in FIG. 13(C) is obtained. By applying ensemble averaging to this phase difference distribution to obtain the Doppler modulation frequency _fd and calculating the displacement velocity, the tomographic distribution of the blood flow velocity shown in FIG. 14A is obtained. FIG. 14B shows the average displacement velocity obtained from the fault distribution. This result is consistent with the displacement speed by the load mechanism described above. That is, the effectiveness of the micro-tomographic visualization processing according to this example was confirmed.

As described above, according to the present embodiment, system noise is reduced in addition to galvano drive noise, and the displacement speed can be calculated with high accuracy. In other words, it is possible to effectively reduce noise caused by the characteristics of the optical mechanism, and improve the accuracy of physical quantity detection by OCT.

Although preferred embodiments of the present invention have been described above, it goes without saying that the present invention is not limited to these specific embodiments, and that various modifications are possible within the scope of the technical concept of the present invention. Nor.

In the above embodiment, an example was shown in which the object to be measured is a living tissue and the blood flow velocity is calculated as a physical quantity. In a modification, the viscoelasticity may be calculated as a physical quantity by calculating the displacement speed while applying a load from the load mechanism. Alternatively, the object to be measured may be a regenerated tissue (cultured cell) or the like. Since the above-described device can easily realize real-time performance, it may be applied to, for example, regenerative treatment of a living body to monitor tissue engraftment. The above apparatus can be applied to various uses and fields, such as the medical field such as cartilage diagnosis and skin diagnosis, as well as the cosmetic surgery field and the cosmetic industry field. Alternatively, the object to be measured may be a polymer base material (resin material), and viscoelasticity or the like may be calculated as a physical quantity.

In the above embodiment, an example of obtaining a two-dimensional tomographic image by OCT was shown, but it may be obtained three-dimensionally. That is, scanning may be performed not only in the depth direction (z direction) and x direction, but also in the y direction for tomographic visualization of the physical quantity of the tissue.

Although TD-OCT is used in the above embodiment, SS-OCT (Swept Source OCT), SD-OCT (Spectral Domain OCT), and other OCT may be used.

It should be noted that the present invention is not limited to the above-described embodiments and modifications, and can be embodied by modifying the constituent elements without departing from the scope of the invention. Various inventions may be formed by appropriately combining a plurality of constituent elements disclosed in the above embodiments and modifications. Also, some constituent elements may be deleted from all the constituent elements shown in the above embodiments and modifications.

1 OCT device, 2 light source, 4 sample arm, 6 reference arm, 8 optical mechanism, 10 optical mechanism, 12 photodetector, 14 processing unit, 16 display device, 18 coupler, 30 collimator lens, 32 galvano scanner, 34 objective lens , 36 galvanometer drive circuit, 40 collimator lens, 42 diffraction grating, 44 curved mirror, 46 resonant scanner, 50 reference mirror, 52 actuator, 54 resonant drive circuit, 56 speed sensor, 60 photodetector, 62 filter, 70 control arithmetic unit , W to be measured.

Claims (9)

A micro tomographic visualization device for tomographically visualizing a predetermined physical quantity in a measurement object,
a light source;
a beam splitter that splits the light from the light source into a sample arm that passes through the measurement object and a reference arm that passes through a reference mirror;
a depth direction scanning unit that performs an A-scan for scanning the light guided to the sample arm in the depth direction of the measurement object;
a lateral scanning unit driven to perform B scanning by shifting the axis of the A scanning in a direction perpendicular to the depth direction;
a photodetector for detecting interference light in which the object light reflected by the measurement target and the reference light reflected by the reference mirror are superimposed;
a processing unit that controls the depth direction scanning unit and the lateral direction scanning unit, processes an optical interference signal input via the photodetector, and calculates a tomographic distribution of the physical quantity in the measurement target;
A display device that displays the calculated tomographic distribution of the physical quantity in a visual form;
with
The processing unit intermittently drives the horizontal scanning unit, acquires the optical interference signal while the horizontal scanning unit is stopped ,
The depth direction scanning unit
a driving circuit for reciprocatingly rotating the reference mirror;
an output circuit that outputs a pulse signal synchronized with the rotation of the reference mirror;
including
The processing unit is
acquiring a trigger signal that rises when the reference mirror starts rotating in one direction and falls when the reference mirror starts rotating in the other direction, based on the pulse signal;
using one of the rising and falling edges of the trigger signal as a trigger to start driving the horizontal scanning unit;
A micro-tomographic visualization apparatus characterized in that acquisition of the optical interference signal is started using the other of the rise and fall of the trigger signal as a trigger . 2. A micro-tomographic visualization apparatus according to claim 1 , wherein said lateral scanning unit is a galvanometer scanner. A micro tomographic visualization device for tomographically visualizing a predetermined physical quantity in a measurement object,
a light source;
a beam splitter that splits the light from the light source into a sample arm that passes through the measurement object and a reference arm that passes through a reference mirror;
a depth direction scanning unit that performs an A-scan for scanning the light guided to the sample arm in the depth direction of the measurement object;
a lateral scanning unit driven to perform B scanning by shifting the axis of the A scanning in a direction perpendicular to the depth direction;
a photodetector for detecting interference light in which the object light reflected by the measurement target and the reference light reflected by the reference mirror are superimposed;
a processing unit that controls the depth direction scanning unit and the lateral direction scanning unit, processes an optical interference signal input via the photodetector, and calculates a tomographic distribution of the physical quantity in the measurement target;
A display device that displays the calculated tomographic distribution of the physical quantity in a visible form;
with
The processing unit intermittently drives the horizontal scanning unit, acquires the optical interference signal while the horizontal scanning unit is stopped,
The depth direction scanning unit is a resonant scanner including the reference mirror,
The micro tomographic visualization apparatus, wherein the processing unit removes system noise caused by driving the resonant scanner in the arithmetic processing of the tomographic distribution of the physical quantity. The processing unit is
calculating the autocorrelation in a predetermined range in the depth direction for the continuously acquired A-scan data, and calculating the phase difference based on the autocorrelation;
4. The micro-tomography visualization apparatus according to claim 3 , wherein the system noise is calculated based on the calculated phase difference. The processing unit is
Sequentially calculating the autocorrelation for the A-scan data of two adjacent lines, calculating the phase difference for each two lines,
In a predetermined line section of three lines or more including the two lines and less than the set line, an area average phase difference is calculated for a predetermined high-rigidity area,
5. The micro-tomographic visualization apparatus according to claim 4 , wherein the system noise for each line is calculated by subtracting the region average phase difference from the phase difference for every two lines. The processing unit is
removing the system noise from the phase difference calculated between each two lines for the lines corresponding to the predetermined line section;
Calculate the Doppler modulation frequency based on the phase difference after removing system noise,
calculating a displacement velocity based on the Doppler modulation frequency;
6. The micro tomographic visualization apparatus according to claim 5 , wherein the tomographic distribution of said physical quantity is calculated based on said displacement velocity. the object to be measured is a biological tissue;
7. The micro-tomography visualization apparatus according to claim 1 , wherein said physical quantity is a blood flow velocity of said living tissue. A micro tomographic visualization method for tomographically visualizing a predetermined physical quantity in a measurement object by using optical coherence tomography,
An A-scan for scanning light in the depth direction of the object to be measured is repeatedly performed while shifting one line at a time in a direction perpendicular to the depth direction to obtain A-scan data of a set number of lines for generating a two-dimensional tomographic image. a scanning process;
A phase difference calculation step of sequentially calculating autocorrelation for A-scan data of two adjacent lines and calculating a phase difference for each two lines;
a noise calculation step of calculating system noise for each line based on the phase difference for every two lines;
a noise removal step of removing the system noise from the phase difference calculated between each two lines;
A Doppler modulation frequency calculation step of calculating a Doppler modulation frequency based on the phase difference after removing system noise;
a displacement velocity calculation step of calculating a displacement velocity based on the Doppler modulation frequency;
a display step of displaying the fault distribution of the physical quantity based on the displacement velocity;
A micro-tomographic visualization method, comprising: Further comprising an area average phase difference calculation step of calculating an area average phase difference for a predetermined high stiffness area in a predetermined line section of three lines or more including the two lines and less than the set number of lines,
The noise calculation step calculates system noise for each line by subtracting the area average phase difference from the phase difference for every two lines,
9. The micro-tomographic visualization method according to claim 8 , wherein the noise removal step removes the system noise from the phase difference calculated between each two lines for the lines corresponding to the predetermined line section.

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