Endoscopic system, program, and method for outputting blood flow information

Abstract

This invention provides an endoscopic system, program, and method for outputting blood flow information that can provide blood flow information without administering contrast agents, fluorescent agents, etc. [Solution] An endoscope system capable of acquiring blood concentration image data indicating blood concentration, comprising an output unit that outputs information regarding blood flow based on blood concentration image data acquired at multiple different time points.

Description

[Technical Field]

[0001] The present invention relates to an endoscope system, a program, and a method for outputting blood flow information. [Background technology]

[0002] Conventionally, a technology that captures a predetermined observation area of ​​a subject and displays it as a two-dimensional image has been widely used.

[0003] For example, Patent Document 1 discloses a fluorescence imaging device that captures images using a fluorescent agent administered to a subject, which can suppress the appearance of bright spots caused by reflections from surgical lighting in the images, and has improved accuracy in motion tracking processing by detecting the position of such observation sites from each continuously captured image based on characteristic points in the observation site.

[0004] Furthermore, Patent Document 2 discloses an endoscope system that calculates relative values ​​of hemoglobin concentration and oxygen saturation based on the calculated measured and reference values ​​of hemoglobin concentration and oxygen saturation, and displays relative value images of the relative values ​​of hemoglobin concentration and / or oxygen saturation on a display unit. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2019-136269 [Patent Document 2] Japanese Patent Publication No. 2020-182738 [Overview of the Initiative] [Problems that the invention aims to solve]

[0006] Generally, methods for confirming blood flow in a predetermined observation site of a subject include administering a contrast agent to the subject, and administering a fluorescent agent, as described in Patent Document 1 above.

[0007] However, in this method using contrast agents and fluorescent agents, since the contrast agents and fluorescent agents are administered intravenously, it is necessary to wait for several minutes for them to circulate in the body. Furthermore, the procedure is stopped during this waiting period, and equipment equipped with optical filters is required for the detection of the contrast agents and fluorescent agents. In addition, there are problems such as the physical burden caused by the administration of the contrast agents and fluorescent agents. Moreover, the endoscopic system described in Reference 2 does not address these problems.

[0008] This invention has been made in view of the above circumstances, and its purpose is to provide an endoscopic system, program, and method for outputting blood flow information that can provide blood flow information without administering contrast agents, fluorescent agents, etc. [Means for solving the problem]

[0009] The endoscope system according to the present invention is an endoscope system capable of acquiring time-series blood concentration image data showing blood concentration, and includes an output unit that outputs blood flow information based on blood concentration image data acquired at multiple different points in time.

[0010] In this invention, blood concentration image data showing blood concentration at multiple different points in time is acquired, and based on the acquired blood concentration image data, the output unit outputs blood flow information related to blood flow.

[0011] The program according to the present invention causes a computer to perform a process that acquires time-series blood concentration image data showing blood concentration and outputs blood flow information based on multiple blood concentration image data acquired at multiple different points in time.

[0012] In the present invention, the program described above causes the computer to acquire blood concentration image data showing blood concentration at multiple different points in time, and based on the acquired blood concentration image data, causes the output unit to output blood flow information related to blood flow.

[0013] The blood flow information output method according to the present invention is a blood flow information output method related to blood flow, which acquires blood concentration image data indicating blood concentration at a plurality of different time points, and outputs the blood flow information based on the acquired blood concentration image data.

[0014] In the present invention, blood concentration image data indicating blood concentration is acquired at a plurality of different time points, and blood flow information related to blood flow is output based on the acquired blood concentration image data.

Effect of the Invention

[0015] According to the present invention, blood flow information related to blood flow can be provided without administering a contrast agent, a fluorescent agent, or the like.

Brief Description of the Drawings

[0016] [Figure 1] It is a block diagram showing the main configuration of an endoscope system according to Embodiment 1. [Figure 2] It is a diagram showing the spectral characteristics of a living tissue and the wavelength band of a first optical filter used when acquiring a broadband image (G1 image). [Figure 3] It is a graph plotting the relationship between the amount of transmitted light of blood (vertical axis) and oxygen saturation (horizontal axis) in the wavelength range W2. [Figure 4] It is a graph plotting the relationship between the amount of transmitted light of blood (vertical axis) and oxygen saturation (horizontal axis) in the regions of the wavelength ranges W4, W5, and W6. [Figure 5] It is a functional block diagram showing the main configuration of an analysis processing unit of an endoscope system according to Embodiment 1. [Figure 6] It is a flowchart for explaining a process of generating a blood flow rate image (data) indicating the blood flow rate in an endoscope system according to Embodiment 1. [Figure 7] It is an explanatory diagram for explaining the process of generating corrected RGB values in an endoscope system according to Embodiment 1. [Figure 8]This is a diagram for explaining the principle of obtaining the blood concentration with the influence of scattered light removed in the endoscope system according to Embodiment 1. [Figure 9] This is an explanatory diagram schematically showing the blood concentration image displayed in the endoscope system according to Embodiment 1. [Figure 10] This is an explanatory diagram schematically showing the blood flow volume image based on the blood concentration image data generated at two time points. [Figure 11] This is an explanatory diagram schematically showing the blood flow volume image based on the blood concentration image data generated at three or more time points. [Figure 12] These are the blood concentration image and the blood flow volume image for a predetermined observation site. [Figure 13] This is a flowchart for explaining the process of displaying the blood flow volume image based on the setting change of the accumulation number of the blood concentration image data in the endoscope system according to the modification example of Embodiment 1. [Figure 14] This is a functional block diagram showing the main configuration of the analysis processing unit of the endoscope system according to Embodiment 2. [Figure 15] This is a flowchart for explaining the process of specifying the abnormal region in the endoscope system according to Embodiment 2. [Figure 16] This is an illustrative diagram showing an example of the blood flow volume image subjected to the process of specifying the abnormal region, which is displayed in the endoscope system according to Embodiment 2. [Figure 17] This is a conceptual diagram of a table showing the blood flow volume image data and the time information stored in the internal memory of the endoscope system according to Embodiment 3.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, the endoscope system, program, and blood flow information output method according to the embodiments of the present invention will be described in detail based on the drawings.

[0018] (Embodiment 1)

[0019] Figure 1 is a block diagram showing the main components of the endoscope system 1 according to Embodiment 1. The endoscope system 1 comprises an endoscope device 100, a processor 200, and a monitor 300 (output unit).

[0020] The endoscope device 100 includes an LCB (Light Carrying Bundle) 102, a solid-state image sensor 108, a driver signal processing unit 110, and a memory 112. The tip surface is provided with a light distribution lens 104 that illuminates the target area (subject) with the illumination light propagated through the LCB 102, and an objective lens 106 that collects the reflected light from the target area.

[0021] The solid-state image sensor 108 is, for example, a single-chip color CCD (Charge Coupled Device) image sensor having a Bayer-type pixel arrangement. The solid-state image sensor 108 generates and outputs an image signal (image data) by accumulating the optical image formed by each pixel on the light-receiving surface as an electric charge corresponding to the amount of light. The solid-state image sensor 108 is equipped with a so-called on-chip color filter, in which an R filter that transmits red light, a G filter that transmits green light, and a B filter that transmits blue light are directly formed on each of the photodetectors of the solid-state image sensor 108. The image signal generated by the solid-state image sensor 108 includes an image signal R captured by a photodetector equipped with an R filter, an image signal G captured by a photodetector equipped with a G filter, and an image signal B captured by a photodetector equipped with a B filter. The endoscope device 100 according to Embodiment 1 includes, for example, one or more solid-state image sensors (CMOS image sensors) 108.

[0022] The driver signal processing unit 110 is located at the connection point between the endoscope device 100 and the processor 200. The driver signal processing unit 110 receives an image signal from the solid-state image sensor 108 at a field frequency. After performing predetermined processing on the image signal input from the solid-state image sensor 108, the driver signal processing unit 110 outputs it to the image processing unit 220 of the processor 200, which will be described later.

[0023] Furthermore, a memory 112 is connected to the driver signal processing unit 110, and the memory 112 stores unique information of the endoscope device 100. Such unique information of the endoscope device 100 includes, for example, the number of pixels of the solid-state image sensor 108, sensitivity, operable field rate, model number, etc. The driver signal processing unit 110 reads the unique information of the endoscope device 100 from the memory 112 and outputs the read unique information to the system control unit 202, which will be described later.

[0024] The processor 200 includes a system control unit 202, a timing control unit 204, an image processing unit 220 (reception unit), a lamp 208, a memory 212, and an optical filter device 260.

[0025] The system control unit 202 executes various programs stored in the memory 212 and controls the entire endoscope system 1. The system control unit 202 is also connected to the operation panel 214 and controls each operation of the endoscope system 1 in response to instructions input from the user via the operation panel 214. The timing control unit 204 outputs clock pulses to each processing unit within the endoscope system 1 to adjust the timing of each of the aforementioned operations.

[0026] Lamp 208 is a high-brightness lamp such as a xenon lamp, halogen lamp, mercury lamp, or metal halide lamp, or an LED. The system control unit 202 is connected to the lamp 208 via a lamp igniter 206 depending on the light source, and controls the lamp igniter 206 to turn the lamp 208 on or off. After being turned on, the lamp 208 emits illumination light L, which is incident on the LCB 102 via the focusing lens 210. The illumination light L is light with a spectrum that mainly extends from the visible light region to the invisible infrared light region, or white light that includes the visible light region.

[0027] An optical filter device 260 is positioned between the lamp 208 and the focusing lens 210. The optical filter device 260 comprises a filter drive unit 264 and an optical filter 262 mounted on the filter drive unit 264. The filter drive unit 264 slides the optical filter 262 in a direction perpendicular to the optical axis of the irradiating light L, thereby positioning the optical filter 262 either on the optical path of the irradiating light L or away from the optical path. Details of the optical filter 262 will be described later. Furthermore, the spectral transmittance of the optical filter 262 and the presence or absence of the optical filter 262 depend on the spectral radiance of the light source.

[0028] The endoscope system 1 of Embodiment 1 has three operating modes: a normal observation mode, a special observation mode, and a baseline measurement mode. In the normal observation mode, endoscopic observation is performed using the white light emitted from the lamp 208 as is (or with the infrared and / or ultraviolet components removed) as the illumination light (normal light Ln). In the special observation mode, endoscopic observation is performed using filtered light Lf obtained by passing the white light through the optical filter 262 (or with the infrared and / or ultraviolet components further removed) as the illumination light. The baseline measurement mode is an operating mode for acquiring the correction values ​​used in the special observation mode. The optical filter 262 is positioned away from the optical path in normal observation mode, and on the optical path in special observation mode.

[0029] The illumination light L (filtered light Lf or normal light Ln) that has passed through the optical filter device 260 is focused by the condensing lens 210 onto the incident end face of the LCB 102 and incident into the LCB 102.

[0030] The irradiation light L that enters the LCB102 propagates within the LCB102 and is irradiated onto the subject via the light distribution lens 104 from the exit end face of the LCB102 located at the tip of the endoscope device 100. The reflected light from the subject irradiated by the irradiation light L forms an optical image on the light-receiving surface of the solid-state image sensor 108 via the objective lens 106.

[0031] The system control unit 202 performs various calculations based on the unique information of the endoscope device 100 and generates control signals. Using the generated control signals, the system control unit 202 controls the operation and timing of various processing units within the processor 200 so that processing suitable for the endoscope device 100 connected to the processor 200 is performed.

[0032] The timing control unit 204 supplies clock pulses to the driver signal processing unit 110 in accordance with the timing control by the system control unit 202. The driver signal processing unit 110 drives and controls the solid-state image sensor 108 in accordance with the clock pulses supplied from the timing control unit 204, at a timing synchronized with the field rate of the image processed on the processor 200 side.

[0033] The image processing unit 220 performs predetermined signal processing, such as color interpolation, matrix calculation, and Y / C separation, on the image signal input from the driver signal processing unit 110 in one-field cycles, then generates image data for monitor display, and converts the generated image data for monitor display into a predetermined video format signal. The converted video format signal is output to the monitor 300.

[0034] The monitor 300 displays an image of the subject on its display screen based on the video format signal. The monitor 300 also displays blood concentration and blood flow information, such as blood volume. Specifically, it displays blood flow information estimated based on changes in hemoglobin concentration in the blood.

[0035] The image processing unit 220 also includes a CPU (not shown) and an analysis processing unit 230. The analysis processing unit 230, for example, in a special observation mode, performs spectroscopic analysis based on the acquired image signals R, G, and B, calculates the value of an index that correlates with changes in blood concentration in the biological tissue of the subject, and generates image data for visually displaying the calculation results. The internal configuration example of the analysis processing unit 230 will be described later.

[0036] As described above, the endoscope system 1 of Embodiment 1 has three operating modes: a normal observation mode, a special observation mode, and a baseline measurement mode. Switching between each operating mode is performed by user operation on the control unit of the endoscope device 100 or the control panel 214 of the processor 200.

[0037] In normal observation mode, the optical filter 262 is separated from the optical path by the control of the optical filter device 260 (system control unit 202), and the subject is irradiated with normal light Ln, allowing the solid-state image sensor 108 to take an image. The image signal captured by the solid-state image sensor 108 is then processed as needed, converted into image data for display, and displayed on the monitor 300.

[0038] In the special observation mode and baseline measurement mode, the optical filter 262 is positioned in the optical path under the control of the optical filter device 260 (system control unit 202), and filtered light Lf is irradiated onto the subject so that the solid-state image sensor 108 can take an image. In the special observation mode, based on the image data captured by the solid-state image sensor 108, processes such as the generation of a blood flow image, which will be described later, are performed.

[0039] The baseline measurement mode is a mode used to acquire data for normalization processing in special observation modes by imaging color reference plates such as achromatic diffusers and standard reflectors as subjects under the illumination of filtered light Lf, before performing actual endoscopic observation.

[0040] The three primary color image data R(x,y), G(x,y), and B(x,y) acquired using the filtered light Lf in baseline measurement mode are stored as baseline image data BLR(x,y), BLG(x,y), and BLB(x,y), respectively, in the internal memory 2306 (see Figure 5) of the analysis processing unit 230 (described later). R(x,y), G(x,y), B(x,y), BLR(x,y), BLG(x,y), and BLB(x,y) are the image data and baseline image data values ​​for pixel (x,y), respectively. The pixel (x,y) is identified by the horizontal coordinate x and the vertical coordinate y.

[0041] Figure 2 shows the spectral characteristics of biological tissue and the wavelength band of the first optical filter used to acquire broadband images (G1 images), and Figure 3 is a graph plotting the relationship between the amount of transmitted light (vertical axis) and oxygen saturation (horizontal axis) of blood in the wavelength range W2.

[0042] For example, the first optical filter, as shown in Figure 2, is an optical filter comprising a first region that transmits light with a wavelength of 452±3 to 502±3 nm (blue light), a second region that transmits light with a wavelength of 524±3 to 582±3 nm (green light), and a third region that transmits light with a wavelength of 630±3 to 700±3 nm (red light).

[0043] The first region corresponds to the wavelength band between the isosbestic points E2 (452±3 nm) and E3 (502±3 nm) of the hemoglobin transmission spectrum, and provides blue light data for generating oxygen saturation information. Here, the isosbestic point of the transmission spectrum is the point where the absorption (transmittance) is constant regardless of the concentration ratio (oxygen saturation) of each component, since the hemoglobin transmission spectrum is a two-component spectral spectrum where the sum of the concentrations of oxygenated hemoglobin and reduced hemoglobin is constant.

[0044] The second region corresponds to the wavelength band between the isosbestic point E4 (524±3nm) and the isosbestic point E7 (582±3nm).

[0045] The values ​​for each wavelength range are expressed with a range of "center wavelength ±3" to account for errors that occur during the manufacturing of the optical filter, and this manufacturing error (±3) is just one example. Furthermore, the wavelength values ​​at each isosbestic point have a range of ±3, which is because the intersection of the spectra of oxygenated hemoglobin and deoxygenated hemoglobin is gradual, and "±3" is just one example.

[0046] On the other hand, in the wavelength range W1 adjacent to wavelength range W2, the absorption A of hemoglobin increases linearly with respect to oxygen saturation. Specifically, with respect to light transmittance, the change is precisely according to the Lambert-Beer Law, but in a relatively narrow wavelength range of about 20 nm to 80 nm, it can be considered to be an almost linear change.

[0047] Furthermore, focusing on the wavelength region from the isosbestic points E4 to E7, i.e., the continuous wavelength region W4 to W6, in wavelength regions W4 and W6, hemoglobin absorption increases monotonically with increasing oxygen saturation, while in wavelength region W5, conversely, blood absorption decreases monotonically with increasing oxygen saturation. However, the decrease in blood absorption in wavelength region W5 is approximately equal to the sum of the increases in blood absorption in wavelength regions W4 and W6, and the total transmittance sum information for the wavelength regions W4, W5, and W6, in other words, the transmittance sum information for the wavelength region from the isosbestic points E4 to E7, indicates that blood absorption is approximately constant regardless of oxygen saturation.

[0048] Figure 4 is a graph plotting the relationship between the amount of light transmitted through blood (vertical axis) and oxygen saturation (horizontal axis) in the wavelength ranges W4, W5, and W6. The amount of light transmitted on the vertical axis is the value integrated using the sum of all transmittance information in the wavelength ranges W4, W5, and W6. The average value of the transmitted light is 0.267 (arbitrary unit), and the standard deviation is 1.86 × 10⁻⁶. -5 As shown in Figure 4, the sum of the total transmittance information in the wavelength ranges W4, W5, and W6 confirms that the amount of light transmitted through the blood is approximately constant regardless of oxygen saturation.

[0049] Furthermore, as shown in Figure 2, in the wavelength range of approximately 630±3 nm and above (especially 650 nm and above), hemoglobin absorption is low, and the light transmittance hardly changes even when the oxygen saturation changes. Also, when using a xenon lamp as a white light source, a sufficiently large amount of light from the white light source can be obtained in the wavelength range of 750±3 nm and below (especially 720 nm and below). Therefore, for example, the wavelength range of 650±3 to 720±3 nm can be used as a reference wavelength range for transmitted light quantity, as it is a transparent region where there is no hemoglobin absorption.

[0050] Figure 5 is a functional block diagram showing the main components of the analysis processing unit 230 of the endoscope system 1 according to Embodiment 1. The analysis processing unit 230 includes an image acquisition unit 2301 that acquires images captured by the endoscope device 100, a correction calculation unit 2302 that corrects the RGB values ​​of the images acquired by the image acquisition unit 2301, a blood concentration image generation unit 2303 (acquisition unit) that calculates relative blood concentration and generates data for displaying a blood concentration image described later (hereinafter referred to as blood concentration image data), a blood flow image generation unit 2304 (processing unit) that generates data for displaying a blood flow image described later (hereinafter referred to as blood flow image data) based on the blood concentration image data generated by the blood concentration image generation unit 2303, a display processing unit 2305 that generates display data for displaying each image and related information on the screen of the monitor 300, and an internal memory 2306 that stores parameters, various data, etc., and temporarily stores data received from the endoscope device 100.

[0051] The image acquisition unit 2301 acquires images captured by each solid-state image sensor 108 and transmitted via the driver signal processing unit 110 (see Figure 1), and also acquires a correction image (white image) to be used as a reference when correcting RGB values.

[0052] Specifically, the image acquisition unit 2301 uses a first optical filter to acquire a B1 image with a wavelength range of 452±3nm to 502±3nm, a G1 image with a wavelength range of 524±3nm to 582±3nm, and an R1 image with a wavelength range of 630±3nm to 700±3nm.

[0053] The correction calculation unit 2302 performs a matrix calculation process, for example, rounding the RGB values ​​acquired by the On-Chip filter in the solid-state image sensor 108 to a value that has a high correlation with the filter output, using the correction image. In such a matrix calculation process, for example, a color matrix for color correction is used, which has coefficients that have a high correlation with the wavelength of blood concentration.

[0054] The blood concentration image generation unit 2303 calculates the ratio of the B1 image and the G1 image, and the Hb (hemoglobin) concentration indicating blood concentration. Based on this Hb concentration, i.e., blood concentration, it generates blood concentration image data, which is two-dimensional image data corresponding to the image captured by the solid-state image sensor 108.

[0055] The blood flow image generation unit 2304 generates blood flow image data showing the blood flow rate (index) based on blood concentration image data acquired at multiple different time points. The blood flow image generation unit 2304 generates the blood flow image data by calculating the difference between the blood concentration image data, based on the blood concentration image data generated at multiple different time points by the blood concentration image generation unit 2303.

[0056] Furthermore, the display processing unit 2305 converts the blood flow image data and the like into a format compatible with the monitor 300's format to generate display data, and transmits it to the monitor 300.

[0057] The following describes the process for generating blood flow images. Figure 6 is a flowchart illustrating the process of generating a blood flow image (data) showing the blood flow rate in the endoscope system 1 according to Embodiment 1. In the following description, a CMOS image sensor equipped with an on-chip filter can be used as the solid-state image sensor 108.

[0058] First, the image acquisition unit 2301 acquires the first RGB image, which is an image captured by the endoscope device 100 (step S101). The first RGB image includes a B1 image with a wavelength range of 452±3nm to 502±3nm, a G1 image with a wavelength range of 524±3nm to 582±3nm, and an R1 image with a wavelength range of 630±3nm to 700±3nm.

[0059] The correction calculation unit 2302 performs matrix calculation processing using the first RGB image acquired by the image acquisition unit 2301 to separate the R image, G image, and B image (step S102). Such matrix calculation processing is performed using, for example, a color matrix for color correction, which has coefficients that have a high correlation with the wavelength of blood concentration.

[0060] On-chip filters may not be able to output appropriate RGB values ​​because there are overlapping wavelength bands. Therefore, in the endoscope system 1 according to Embodiment 1, the RGB values ​​acquired by the On-chip filter are corrected with a coefficient that has a high correlation with the wavelength of blood concentration (for example, a 3x3 matrix operation) to achieve appropriate band separation.

[0061] Figure 7 is an explanatory diagram illustrating the process of generating corrected RGB values ​​in the endoscope system 1 according to Embodiment 1. Specifically, as shown in Figure 7, a matrix transformation operation is performed on the RGB values ​​of the on-chip filter (upper row of Figure 7: (Rs, Gs, Bs)) to generate corrected RGB values ​​(RGB_related_values) (see middle row of Figure 7). In subsequent processing, the corrected RGB values ​​are used as the RGB values.

[0062] The blood concentration image generation unit 2303 calculates the relative blood concentration at the observation site (step S103). This blood concentration is obtained by calculating the ratio of each element, which is oxygenated hemoglobin, deoxygenated hemoglobin, and scattered light, based on the spectral information of the mucosa. For example, Japanese Patent No. 7287969 can be used as a method for calculating blood concentration.

[0063] Figure 8 is a diagram illustrating the principle for determining blood concentration after removing the effects of scattered light in the endoscope system 1 according to Embodiment 1. For example, in the absence of scattered light, the baseline becomes nearly horizontal, as shown in Figure 8A. Therefore, the relative blood concentration (also called blood density) can be expressed by the displacement from the baseline to G1 (wide) Hb = G1 / R1 (where R1 represents the baseline). However, in reality, scattered light is involved, so the baseline is not horizontal but tilted, as shown in Figure 8B. In other words, the baseline is blurred.

[0064] The spectral characteristics of scattering can be represented by a combination of the spectral characteristics of the usual RGB values, as shown in Figure 8C. Therefore, by reproducing the spectral characteristics as a linear combination of RGB values ​​and using that as a baseline, it is possible to calculate the relative blood concentration considering scattered light.

[0065] The following equation (2) is used to calculate the relative blood concentration considering scattered light. Hbcnc'={G1(wide)} / (α*B1+β*G1+γ*R1)…(2) In equation (2), we just need to determine the optimal coefficients α, β, and γ that can reproduce the spectral characteristics. Since the sloped baseline in the spectral characteristics of Figure 8B can be reproduced from G1 and R1 alone, in the example of Figure 8B (Figure 8C), we can set α=0 and β=γ=1.

[0066] By performing the calculations described above, the blood concentration image generation unit 2303 can calculate the relative blood concentration at each unit location of the observation area. Furthermore, it is desirable that the generation of blood concentration image data by the blood concentration image generation unit 2303, i.e., imaging by the solid-state image sensor 108, be performed at a period shorter than the pulse period of the subject, and that the changes be added together. Preferably, high efficiency can be obtained by performing the sampling at a period shorter than half the pulse period. However, it is not limited to this.

[0067] The blood concentration image generation unit 2303 generates blood concentration image data, which is two-dimensional image data, based on the calculated blood concentration for each unit location, and transmits it to the display processing unit 2305. The display processing unit 2305 converts the blood concentration image data into a format used when displaying the image on the monitor 300 and transmits it to the monitor 300. The monitor 300 receives and outputs the blood concentration image data from the display processing unit 2305. That is, the monitor 300 displays a blood concentration image on the screen based on the converted blood concentration image data (step S104).

[0068] Figure 9 is a schematic explanatory diagram showing a blood concentration image displayed in the endoscope system 1 according to Embodiment 1. Figure 9A is an image of the observation area captured by the solid-state image sensor 108, and Figure 9B is an illustrative diagram of a blood concentration image, in which the blood concentration at each unit location of the observation area, calculated by the blood concentration image generation unit 2303, is displayed in correspondence with the image of the observation area in Figure 9A.

[0069] The aforementioned blood concentration image displays blood concentration using color information. For example, Figure 9B shows blood concentration using brightness differences. The lower the brightness (darker), the higher the blood concentration. That is, in Figure 9B, the darker areas indicate regions with high blood concentration at that time in the observed area, and the lighter areas indicate regions with low blood concentration at that time in the observed area. In other words, the blood concentration image in Figure 9B shows the blood concentration (index) at the time of observation. However, this is not the only option; blood concentration may also be indicated using hue or saturation.

[0070] In the endoscope system 1 according to Embodiment 1, the solid-state imaging device 108 captures images 30 to 60 times per second (30 frames / second to 60 frames / second), and blood concentration image data corresponding to each captured image is generated in real time. Each blood concentration image corresponding to the captured image is displayed on the monitor 300 each time the solid-state imaging device 108 captures an image.

[0071] When the blood concentration image generation unit 2303 generates a plurality of blood concentration image data at a plurality of different time points, the blood flow rate image generation unit 2304 obtains the difference between the generated plurality of blood concentration image data and integrates the obtained difference (step S105). Hereinafter, such processing will be described in detail.

[0072] When the blood concentration image generation unit 2303 generates blood concentration image data at two time points, for example, t1 and t2, the blood flow rate image generation unit 2304 calculates the absolute value (ΔHbcnc’ t2 ) of the value obtained by subtracting the blood concentration image data (Hbcnc’ t1 ) at t1 from the blood concentration image data (Hbcnc’ t2-t1 ) at t2. Here, cnc is an abbreviation of "concentration".

[0073] When the blood concentration image generation unit 2303 generates three or more blood concentration image data, for example, when the blood concentration image data is generated at three time points, t1, t2, and t3, the blood flow rate image generation unit 2304 obtains the difference between the blood concentration image data at two adjacent time points and integrates the obtained difference.

[0074] That is, the blood flow rate image generation unit 2304 obtains the above-mentioned ΔHbcnc’ t2-t1 and the absolute value (ΔHbcnc’ t3 ) of the value obtained by subtracting the blood concentration image data (Hbcnc’ t2 ) at t2 from the blood concentration image data (Hbcnc’ t3-t2 ) at t3, and then adds (integrates) the obtained ΔHbcnc’ t2-t1 and ΔHbcnc’ t3-t2 .

[0075] Here, changes in blood concentration due to pulsation are captured and used as an indicator of blood flow. For example, when the flow velocity is high, the concentration change due to pulsation is large. Image acquisition using general image sensors allows for imaging at a speed sufficiently faster than the pulsation of living organisms, and high-speed image processing is possible.

[0076] Next, the blood flow image generation unit 2304 generates blood flow image data, which is two-dimensional image data corresponding to the image captured by the solid-state image sensor 108, based on the calculated result of the integration of the differences in blood concentration for each unit location. The blood flow image generation unit 2304 transmits the generated blood flow image data to the display processing unit 2305, which converts the blood flow image data into a format used when displaying the image on the monitor 300 and transmits it to the monitor 300. The monitor 300 receives and outputs the blood flow image data from the display processing unit 2305. That is, the monitor 300 displays a blood flow image on the screen based on the converted blood flow image data (step S106).

[0077] Figure 10 is a schematic diagram illustrating a blood flow image based on blood concentration image data generated at two points in time. Figures 10A and 10B are the blood concentration images at t1 and t2, respectively, generated by the blood concentration image generation unit 2303. Figure 10C is an example of a blood flow image, where the cumulative result of the difference in blood concentration at each unit location of the observation site, obtained by the blood flow image generation unit 2304, is displayed in correspondence with the blood concentration image. For example, t2 is 1 second after t1.

[0078] The aforementioned blood flow image displays the difference in blood concentration using color information. For example, Figure 10C shows the difference in blood concentration using brightness differences. The lower the brightness (darker), the smaller the difference in blood concentration. That is, in Figure 10C, the lightly colored areas indicate regions where the difference in blood concentration is small in the observed area, and the darkly colored areas indicate regions where the difference in blood concentration is large in the observed area.

[0079] Thus, blood flow images (data) represent blood flow information regarding the flow of blood in the observed area. In other words, as described above, blood flow images are generated based on the difference between multiple blood concentration image data generated (acquired) at multiple different time points, so they show changes in blood concentration in the same observed area, and changes in blood concentration indicate blood flow. That is, the larger the change (difference) in blood concentration (the more concentrated the blood), the greater the blood flow, and the smaller the change (difference) in blood concentration (the thinner the blood), the less the blood flow. In other words, based on blood flow images, it is possible to determine whether or not blood is flowing in a given area of ​​the observed site.

[0080] As described above, the blood flow information is based on the difference in blood concentration, and therefore includes not only whether blood is flowing or stagnating in a predetermined area of ​​the observation site, but also whether the flow rate (blood concentration) is always the same. However, since it cannot be assumed that the flow rate (blood concentration) is always the same in a living organism, this aspect will be omitted in the following explanation for convenience.

[0081] In the example in Figure 10C, areas corresponding to large blood vessels are shown darkly, indicating high blood flow, while areas corresponding to capillaries are shown lightly, indicating low blood flow. Furthermore, area P1, which was shown black in Figures 10A and 10B, is shown white in Figure 10C, indicating no blood flow, i.e., no blood is flowing, or blood is present but stagnating. Note that the dashed ellipse in Figure 10C is shown for comparison with area P1 in Figure 10A and is not part of the blood flow image.

[0082] The above explanation used the example of representing the difference in blood concentration using the difference in brightness, but the display method is not limited to this, and blood concentration may also be indicated using hue or saturation.

[0083] Figure 11 is a schematic diagram illustrating blood flow images based on blood concentration image data generated at three or more time points. Figure 11A shows a blood flow image based on blood concentration image data generated at two time points for reference, Figure 11B is a blood flow image based on blood concentration image data generated at the time of integration of 10 frames of images, and Figure 11C is a blood flow image based on blood concentration image data generated at the time of integration of 20 frames of images. Specifically, Figure 11B displays the result of the integration of the difference in blood concentration between 10 blood concentration images, corresponding to the blood concentration images, and Figure 11C displays the result of the integration of the difference in blood concentration between blood concentration images from the integration of 20 frames of images, corresponding to the blood concentration images. In each of the blood flow images from Figures 11A to 11C, the difference (integration) of blood concentration is displayed using color information, as shown in Figure 10C.

[0084] As shown in Figure 11A, blood flow images based on blood concentration image data generated at two time points can also distinguish between areas with high blood flow and areas with low blood flow, allowing for the determination of whether or not blood is flowing in a predetermined area of ​​the observation site.

[0085] In contrast, Figures 11B and 11C, which are blood flow images based on blood concentration image data generated at three or more time points, clearly distinguish between areas with high (concentrated) blood flow and areas with low (dilute) blood flow, improving the accuracy of discrimination and the ability to determine whether or not blood is flowing in a given area of ​​the observation site.

[0086] Furthermore, compared to the blood flow image in Figure 11B, which is based on blood concentration image data generated after 10 scans, the blood flow image in Figure 11C, which is based on blood concentration image data generated after 20 scans, shows even greater accuracy in distinguishing between areas with high and low blood flow, and further improves the accuracy of determining whether or not blood is flowing in a predetermined area of ​​the observation site.

[0087] As described above, in the endoscope system 1 according to Embodiment 1, the solid-state image sensor 108 takes images, for example, 30 to 60 times per second. In other words, blood concentration image data is generated 30 to 60 times per second, and a blood concentration image based on such blood concentration image data is displayed on the monitor 300. For example, if blood concentration image data is generated 60 times per second, the blood flow image generation unit 2304 generates blood flow image data 59 times per second, and the monitor 300 can display the blood flow image in real time.

[0088] As described above, the endoscope system 1 according to Embodiment 1 generates blood flow image data based on the cumulative result of the difference in blood concentration for each unit location in response to the generation of blood concentration image data, and displays the blood flow image on the monitor 300 in real time. The blood flow image (data) is blood flow information relating to the flow of blood in the observed area, and the user can use the blood flow image to determine the relative blood flow in a predetermined observed area, and thereby extract areas where the blood flow state is abnormal, including whether or not blood is flowing in a predetermined area of ​​the observed area.

[0089] Alternatively, the screen of monitor 300 may be split to display the blood concentration image along with the blood flow image. Furthermore, separate monitors 300 may be provided for the blood concentration image and the blood flow image.

[0090] Generally, a known method for confirming blood flow in a designated observation site of a subject involves administering drugs such as contrast agents or fluorescent agents to the subject. However, this method requires medical staff, such as doctors, to wait for several minutes while the contrast agent or fluorescent agent circulates in the body after intravenous administration, and other procedures must be suspended during this waiting period. Furthermore, detection requires irradiation with excitation light of a limited wavelength and specialized equipment equipped with fluorescence detectors, and the administration of contrast agents and fluorescent agents places a burden on the patient's body.

[0091] In contrast, the endoscope system 1 according to Embodiment 1, as described above, can provide blood flow information regarding blood flow in a predetermined observation site, such as determining the blood flow rate in a predetermined observation site and whether or not blood is flowing in a predetermined area of ​​the observation site, based on acquired blood flow images (data) without administering drugs such as contrast agents or fluorescent agents. Therefore, blood flow information can be provided in real time without interfering with medical procedures, and expensive dedicated equipment for fluorescence observation is not required. Furthermore, since there is no need to administer medication, it does not place a burden on the patient's body.

[0092] Furthermore, by using the blood flow images displayed by the endoscope system 1 according to Embodiment 1, it is possible to identify the affected area and understand the pathological condition. This will be explained in detail below.

[0093] Figure 12 shows blood concentration and blood flow images for a predetermined observation site. Figure 12A is a blood concentration image, and Figure 12B is a blood flow image displayed by the endoscope system 1 according to Embodiment 1. In Figures 12A and 12B, the arrows point to neovascularization.

[0094] The blood concentration image in Figure 12A only shows the blood concentration at that time and does not represent blood flow information; therefore, it is not possible to identify the affected area or understand the pathological condition based on the blood concentration image. In contrast, the blood flow image in Figure 12B, as described above, represents the relative blood flow at the observation site and indicates whether or not blood is flowing in a predetermined area of ​​the observation site. Therefore, it is possible to identify the affected area and understand the pathological condition based on the blood flow image.

[0095] Specifically, based on the blood flow images in Figure 12B, areas with high blood flow in existing blood vessels can be identified as potentially inflamed areas, and areas with a high concentration of neovascularization and high blood flow can be identified as potentially tumorous areas.

[0096] Furthermore, as described above, the endoscope system 1 according to Embodiment 1 performs the accumulation of the differences in blood concentration between blood concentration image data, and acquires blood flow image data based on the result of this accumulation of differences in blood concentration. Therefore, as shown in Figure 11, the accuracy of distinguishing between areas with high blood flow and areas with low blood flow is improved, and the accuracy of determining whether or not blood is flowing in a predetermined area of ​​the observation site can be improved.

[0097] In the above description, we have used as an example an endoscope system 1 according to Embodiment 1 in which blood concentration image data is generated 60 times / second and blood flow image data is generated 59 times / second, but we are not limited to this. It is desirable that the blood concentration image generation unit 2303 generates blood concentration image data at a frequency of half the subject's heartbeat cycle. Since the heart contracts and relaxes repeatedly with each heartbeat cycle, the point at half the subject's heartbeat cycle corresponds to a point in time when the difference in blood flow (blood concentration) is large. Therefore, by generating blood concentration image data at a frequency of half the subject's heartbeat cycle, blood flow image data with less blood concentration image data, i.e., with higher efficiency and accuracy, can be obtained.

[0098] Furthermore, while the endoscopic system 1 according to Embodiment 1 has been described above using the example of acquiring blood concentration image data by adjusting the R wavelength, G wavelength, and B wavelength using a first filter, it is not limited to this. Two-dimensional distribution information of blood concentration may be obtained by other methods.

[0099] (modified version) The endoscope system 1 according to Embodiment 1 is not limited to the above description. For example, the interval for displaying (generating) blood flow image data may be changed. Here, the display interval is the interval at which the monitor 300 displays the blood flow image.

[0100] As described above, when the target area is imaged by the solid-state image sensor 108, blood concentration image data is generated, the difference in blood concentration with the immediately preceding blood concentration image data is calculated, and blood flow image data is generated based on the cumulative result of this difference, and the blood flow image is displayed on the monitor 300 based on the generated blood flow image data. In other words, from the second time onward, blood flow image data is generated each time the target area is imaged by the solid-state image sensor 108, and the monitor 300 is able to display the blood flow image.

[0101] In contrast, in the endoscope system 1 according to a modified embodiment of Embodiment 1, instead of displaying a blood flow image each time the solid-state image sensor 108 images the target area, one blood flow image is displayed based on multiple blood concentration image data. That is, multiple blood concentration image data are accumulated over a predetermined period of time, and one blood flow image is displayed based on the cumulative result of the differences between the accumulated multiple blood concentration image data. For example, the number of blood concentration image data to be accumulated, in other words, the accumulation time of the blood concentration image data, is accepted from the user.

[0102] For example, if the user requests "10" as the number of blood concentration image data points to be stored (hereinafter referred to as the "storage number"), then 10 frames of blood concentration image data are acquired. Based on these 10 frames of blood concentration image data, the difference in blood concentration is calculated. Based on the cumulative result of this difference, blood flow image data is generated, and the blood flow image data is displayed on the monitor 300. In other words, a blood flow image is displayed each time 10 frames of blood concentration image data are acquired.

[0103] Figure 13 is a flowchart illustrating the process of displaying blood flow images based on a change in the setting of the number of accumulated blood concentration image data in an endoscope system 1 according to a modified example of Embodiment 1. The process of displaying blood flow images will be described below based on Figures 13 and 6.

[0104] The image processing unit 220 (CPU) of the endoscope system 1 receives a setting from the user via the control panel 214 (see Figure 1) to specify the number of blood concentration image data to be stored (step S201). The received number of blood concentration image data to be stored is stored in the internal memory 2306. For the sake of explanation, the following example will use the case where the user has provided "10" as the number of items to be stored.

[0105] When the user sets the number of blood concentration image data to be stored, the CPU of the image processing unit 220 assigns 1 to "N" and stores it in the internal memory 2306 (step S202).

[0106] Subsequently, the solid-state image sensor 108 images the target area, and as described above, once the blood concentration image data for the first frame corresponding to the target area is generated, the monitor 300 displays the blood concentration image for the first frame based on the blood concentration image data for the first frame on the screen (step S203). This process is the same as steps S101 to S104 in Figure 6, and a detailed explanation is omitted.

[0107] Next, imaging of the target area by the solid-state image sensor 108 continues, and when the blood concentration image data for the second frame is generated, as described above, the difference in blood concentration between the blood concentration image data is calculated based on the blood concentration image data for the first and second frames, and blood flow image data is generated based on this difference in blood concentration (step S204). This process is the same as step S105 in Figure 6, and a detailed explanation is omitted.

[0108] Next, the CPU of the image processing unit 220 determines whether N is less than 10 based on the contents of the internal memory 2306 (step S205).

[0109] If the CPU of the image processing unit 220 determines that N is less than 10 (step S205: YES), it substitutes "N+1" for "N" and stores it in the internal memory 2306 (step S206). At this time, the blood flow image data generated in step S204 is not sent to the display processing unit 2305, and the blood flow image based on the blood concentration image data of the first and second frames is not displayed on the monitor 300. The process then returns to step S202.

[0110] Returning to step S202, the target area is imaged again by the solid-state image sensor 108, blood concentration image data is generated, and the monitor 300 displays a blood concentration image on the screen based on the blood concentration image data. This process, from step S202 to step S206, is repeated until the solid-state image sensor 108 captures the target area for the 10th time, generates blood concentration image data for the 10th frame, and the monitor 300 displays the blood concentration image for the 10th frame based on the blood concentration image data for the 10th frame on the screen.

[0111] When the blood concentration image of the 10th frame is displayed on the screen, the blood flow image generation unit 2304 calculates the difference between the generated blood concentration image data of frames 1 to 10, and integrates the calculated differences. As described above, blood flow image data is generated based on the blood concentration image data for 10 frames (step S204). This process has already been explained in step S105 of Figure 6, so a detailed explanation is omitted here.

[0112] In this case, since "N" is 10, the CPU of the image processing unit 220 determines that N is not less than 10, that is, N is 10 or greater (step S205: NO), and instructs the blood flow image generation unit 2304 to send the blood flow image data based on 10 frames of blood concentration image data to the display processing unit 2305. The display processing unit 2305 converts the blood flow image data based on 10 frames of blood concentration image data into a format and sends it to the monitor 300, and the monitor 300 displays the blood flow image based on 10 frames of blood concentration image data on the screen (step S207).

[0113] Next, the CPU of the image processing unit 220 determines whether or not imaging of the target area by the solid-state image sensor 108 has been completed (step S208). If the CPU of the image processing unit 220 determines that imaging of the target area by the solid-state image sensor 108 has not been completed (step S208: NO), it resets N (step S209). That is, the CPU of the image processing unit 220 assigns null (zero) to "N", stores it in the internal memory 2306 (step S209), and then returns to step S206.

[0114] Furthermore, the CPU of the image processing unit 220 terminates processing when it determines that imaging of the target area by the solid-state image sensor 108 has been completed (step S208: YES). Furthermore, regardless of whether imaging by the solid-state image sensor 108 has finished, the image processing unit 220 may be configured to terminate processing when it receives an interrupt signal instructing termination from its CPU.

[0115] As described above, in the modified endoscope system 1, instead of displaying a blood flow image each time the solid-state image sensor 108 images the target area, the blood flow image is displayed at predetermined intervals according to the number of accumulated blood concentration image data received from the user, thereby reducing the image processing load on the image processing unit 220. Furthermore, since a blood flow image based on blood concentration image data from multiple frames is displayed, it becomes easier to grasp changes in blood flow. In addition, it is possible to select an accumulated number of frames that makes it easy to grasp the blood flow in the area of ​​interest.

[0116] The image acquisition unit 2301, the correction calculation unit 2302, the blood concentration image generation unit 2303, the blood flow rate image generation unit 2304, and the display processing unit 2305 may be configured using hardware logic, or they may be constructed in software by the CPU of the image processing unit 220 executing a predetermined program.

[0117] The light source and optical filter system are not limited to the configuration described above; they can also be implemented using white LEDs, multi-color LEDs, optical filters, or laser light sources.

[0118] (Embodiment 2) Figure 14 is a functional block diagram showing the main components of the analysis processing unit 230 of the endoscope system 1 according to Embodiment 2. The analysis processing unit 230 includes an image acquisition unit 2301, a correction calculation unit 2302, a blood concentration image generation unit 2303 (acquisition unit), a blood flow rate image generation unit 2304 (processing unit), a display processing unit 2305, an internal memory 2306, and a feature region identification unit 2307 (identification unit).

[0119] The image acquisition unit 2301, correction calculation unit 2302, blood concentration image generation unit 2303, blood flow rate image generation unit 2304, display processing unit 2305, and internal memory 2306 have already been described in Embodiment 1, and a detailed explanation will be omitted here.

[0120] The feature region identification unit 2307 identifies regions in the blood flow image where the blood flow rate is very low (below a critical value) or very high (above a critical value) based on thresholds stored in the internal memory 2306 (hereinafter referred to as "abnormal regions"). Specifically, the feature region identification unit 2307 identifies abnormal regions in the observed area by comparing the result of the accumulation of differences in blood concentration obtained by the blood flow image generation unit 2304 with the thresholds stored in the internal memory 2306.

[0121] Figure 15 is a flowchart illustrating the process of identifying abnormal areas in the endoscope system 1 according to Embodiment 2. The processes in steps S301 to S306 in Figure 15 are the same as the processes in steps S101 to S106 in Figure 6 of Embodiment 1, and therefore a detailed explanation is omitted.

[0122] The blood flow image generation unit 2304 calculates the cumulative result of the difference in blood concentration (data) for each unit location of the blood concentration image, generates blood flow image data, and displays the blood flow image on the monitor 300 screen. After that, the feature region identification unit 2307 performs the process of identifying abnormal regions (step S307). For the sake of explanation, below, as an example of identifying abnormal regions, we will describe the case in which regions with blood flow below a specific value and very low are identified.

[0123] The feature region identification unit 2307 reads a threshold value stored in the internal memory 2306 and compares it with the result of the cumulative difference in blood concentration obtained by the blood flow image generation unit 2304 in step S305. This comparison process is performed, for example, for each unit location in the blood flow image. As a result of the comparison by the feature region identification unit 2307, if a unit location that is below the threshold value is identified, the identified unit location is temporarily stored, for example, in the internal memory 2306. Here, the threshold value can refer to information such as blood concentration. For example, if the threshold value is set to a value close to "0 (zero)", the identified unit location (hereinafter referred to as the identified location) is sensitive to blood concentration but has no difference in blood concentration, that is, it indicates a location with very little blood flow.

[0124] Next, the feature region identification unit 2307 performs processing to visually differentiate the identified areas stored in the internal memory 2306. For example, the feature region identification unit 2307 assigns a predetermined color to the identified areas to visually differentiate them from other areas. In this way, blood flow image data is generated in which abnormal areas have been identified, that is, identified areas where the blood flow rate is below a threshold are colored. However, this is not limited to the above, and for example, different colors or different shades may be applied depending on the difference from the threshold.

[0125] The feature region identification unit 2307 transmits the generated blood flow image data, which has undergone processing to identify abnormal regions, to the display processing unit 2305. The display processing unit 2305 converts the blood flow image data, which has undergone processing to identify abnormal regions, into a format used when displaying the image on the monitor 300, and transmits it to the monitor 300. The monitor 300 receives the blood flow image data, which has undergone processing to identify abnormal regions, from the display processing unit 2305 and displays the blood flow image on the screen (step S308).

[0126] Figure 16 is an illustrative diagram showing an example of a blood flow image after abnormal area identification processing has been performed, as displayed in the endoscope system 1 according to Embodiment 2. Figure 16 shows the case when abnormal area identification processing has been performed by the feature area identification unit 2307 on the blood flow image (data) shown in Figure 10C. In the example of Figure 16, for convenience, a predetermined color (shown as hatching in the figure) is applied to the identified area. Below, Figure 16 will be described in comparison with Figure 10C.

[0127] As already explained in Embodiment 1, the blood flow image in Figure 10C shows the magnitude of blood flow using color information. In the example of Figure 10C, the areas corresponding to the thicker, darker blood vessels indicate a high blood flow, while the areas corresponding to the lighter, lighter blood vessels indicate a low blood flow. Furthermore, the area P1 shown in white in Figure 10C indicates no blood flow, that is, no blood is flowing.

[0128] In contrast, in the blood flow image shown in Figure 16, which has been processed to identify abnormal regions, the region corresponding to region P1, which was displayed in white in Figure 10C, is identified as an abnormal region and is marked with a predetermined color (hatching) because, although the presence of blood can be confirmed from the blood concentration image, no blood is flowing.

[0129] As described above, in the endoscope system 1 according to Embodiment 2, the blood flow image (data) is processed by the feature region identification unit 2307 to identify abnormal regions, and the identified abnormal regions are visually differentiated and displayed. Therefore, users such as doctors can objectively and quickly identify regions with very low blood flow or very high blood flow without relying on visual judgment.

[0130] (Embodiment 3) In the endoscope system 1 according to Embodiment 3, the monitor 300 displays the blood flow image as an animated image.

[0131] In the endoscope system 1 according to Embodiment 3, the display processing unit 2305 stores the blood flow image data generated by the blood flow image generation unit 2304 of the analysis processing unit 230 in the internal memory 2306 of the analysis processing unit 230 each time. That is, the internal memory 2306 stores blood flow image data sent to the monitor 300 prior to that point in time, in chronological order, associated with time information representing that point in time.

[0132] Figure 17 is a conceptual diagram of a table showing blood flow image data and time information stored in the internal memory 2306 of the endoscope system 1 according to Embodiment 3. Figure 17 shows that blood flow image data generated by the blood flow image generation unit 2304 at each time point from Time1 to Time10 is stored in chronological order, corresponding to the time information.

[0133] In the endoscope system 1 according to Embodiment 3, when the display processing unit 2305 displays blood flow images (data) on the monitor 300, if there are blood flow image data that have been displayed before that point in time (hereinafter referred to as previously displayed blood flow image data), the blood flow image data to be displayed at that point in time and the previously displayed blood flow image data are sequentially displayed as output images in chronological order. This makes it possible to display blood flow image data as an animated image.

[0134] For example, if the blood flow image data to be displayed is "Blood flow image data 10.xxx", that is, if the current time is Time 10, the display processing unit 2305 reads the previously displayed blood flow image data related to Time 1 to Time 9 ("Blood flow image data 1.xxx" to "Blood flow image data 9.xxx") from the internal memory 2306 and displays "Blood flow image data 1.xxx" to "Blood flow image data 10.xxx" sequentially in chronological order. As a result, the monitor 300 continuously displays "Blood flow image data 1.xxx" to "Blood flow image data 10.xxx".

[0135] As described above, in the endoscope system 1 according to Embodiment 3, when displaying blood flow images (data), the previously displayed blood flow image data is displayed in chronological order along with the blood flow image data to be displayed at that time, as an animation. Therefore, it is possible to grasp the change in blood flow (difference in blood concentration) over time in a predetermined observation area, making it easy to determine the blood flow and whether or not blood is flowing in a predetermined area.

[0136] The endoscope system 1 according to Embodiment 3 is not limited to the above description. In addition to blood flow images, it displays blood flow image data that has undergone specific processing for abnormal regions as described in Embodiment 2 as an animated image. For example, the display processing unit 2305 of the analysis processing unit 230 may make the abnormal region (see hatched area in Figure 16) of the blood flow image data that has undergone specific processing for abnormal regions blink.

[0137] In the above explanation, we have used the example of displaying blood flow information as color information in a blood flow image, but this is not the only example. For example, the blood flow rate may be calculated by associating it with the coordinates of the target area image, and when the user requests the blood flow rate for a specific location, the blood flow rate for that location may be displayed. Alternatively, the calculated blood flow rate may be superimposed on the target area image.

[0138] The technical features (constituent elements) described in Embodiments 1 to 3 are combinable with each other, and by combining them, new technical features can be formed.

[0139] For example, the monitor 300 may display multiple images selected from the images captured using white light in the normal observation mode (hereinafter referred to as white images), oxygen saturation display images, blood concentration images, and blood flow images. Specifically, it can display two screens simultaneously: a white image and a blood flow image, or three screens simultaneously: a white image, an oxygen saturation display screen, and a blood flow image.

[0140] In particular, when displaying both a white image and a blood flow image simultaneously, by increasing the number of accumulated blood flow images by one at a time (each time a blood concentration image is generated) and repeating the display, it is possible to determine the appropriate number of accumulated blood concentration images that result in a blood flow image where the area of ​​interest is easily visible. In this way, once the appropriate number of accumulated blood concentration images is known, it is possible to continue displaying blood flow images with that number of accumulated images. Furthermore, once the number of stored images is determined, the old image is removed and the new image is inserted after each image capture, and the recalculated image is displayed. This means that display delays due to storage time are limited to the initial stage only.

[0141] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of the invention is indicated by the claims, not in the sense described above, and all modifications are intended to be in the sense and scope equivalent to the claims. [Explanation of symbols]

[0142] 1 Endoscopy System 100 Endoscopes 220 Image Processing Unit (Reception Section) 230 Analysis Processing Unit 300 Monitor (Output Section) 2301 Image acquisition unit 2302 Correction Calculation Unit 2303 Blood concentration image generation unit (acquisition unit) 2304 Blood flow image generation unit (processing unit) 2305 Display Processing Unit 2307 Feature Area Identification Unit (Identification Unit)

Claims

1. An endoscope system capable of acquiring time-series blood concentration image data showing blood concentration, An endoscope system equipped with an output unit that outputs blood flow information based on blood concentration image data acquired at multiple different points in time.

2. The endoscope system according to claim 1, wherein the output unit outputs blood flow image data indicating blood flow based on a plurality of blood concentration image data.

3. The system includes a processing unit that calculates the difference between blood concentration image data based on blood concentration image data from at least two time points in time, The endoscope system according to claim 2, wherein the output unit outputs the blood flow image data based on the difference between the blood concentration image data obtained by the processing unit.

4. The processing unit obtains the difference between two adjacent blood concentration image data points from the blood concentration image data at three or more time points in chronological order, and then performs the accumulation of these differences. The endoscope system according to claim 3, wherein the output unit outputs the blood flow image data based on the result of the integration of the difference by the processing unit.

5. The system includes a unit that identifies regions where the blood flow rate is above a threshold or below a threshold, based on the blood flow image data. The endoscope system according to any one of claims 2 to 4, wherein the output unit displays the result of the identification by the identification unit.

6. The endoscope system according to claim 5, wherein the output unit uses color information to represent the blood flow image data.

7. The endoscope system according to any one of claims 2 to 4, wherein the output unit displays a plurality of blood flow image data in chronological order as an output image.

8. The endoscopic system according to claim 1, further comprising an acquisition unit that acquires the blood concentration image data at a period of half the pulse cycle of the subject.

9. The endoscope system according to claim 2, further comprising an output unit that receives a setting for changing the time interval at which the blood flow image data is output.

10. We obtain time-series blood concentration image data that shows blood concentration, Based on multiple blood concentration image data acquired at different time points, it outputs blood flow information. A program that instructs a computer to perform a process.

11. A method for outputting blood flow information related to blood flow, Blood concentration image data showing blood concentration is acquired at multiple different time points. A method for outputting blood flow information, which outputs the blood flow information based on acquired blood concentration image data.

Images