Endoscope device, endoscope image processing method, program product, and storage medium

Abstract

The invention provides an endoscope device, an endoscope image processing method, a program product, and a storage medium. This endoscope device is provided with: an endoscope that outputs an imaging signal; and a processor that generates a subject image by performing image processing on the imaging signal, calculates an index for each pixel by normalizing the sum of a red pixel value and a green pixel value for each of a plurality of pixels of the subject image by using a blue pixel value, and calculates an index for each pixel by normalizing the sum of the red pixel value and the green pixel value for each of the plurality of pixels of the subject image. A threshold value set is selected from a plurality of threshold value sets corresponding to a plurality of combinations of a plurality of pieces of endoscope information and a plurality of pieces of processor information, the symptom level of each pixel is identified as one of a plurality of symptom levels using the threshold value set, and an identification color corresponding to the symptom level of each pixel is acquired. Generating an identification image using the identification colors of each of the plurality of pixels; and a monitor that displays the recognition image.

Description

Technical Field

[0001] The present invention relates to an endoscope device that displays an identification image corresponding to the symptom level of a subject in the body, an endoscope image processing method for photographing a subject in the body and displaying an identification image corresponding to the symptom level, and a program product and a storage medium of an endoscope device that photograph a subject in the body and display an identification image corresponding to the symptom level. Background Art

[0002] An endoscope device disclosed in International Publication No. 2018 / 230130 calculates an index indicating the degree of abnormality of a subject based on the color included in the subject image captured by the endoscope, and performs identification display on the index according to a threshold value. Summary of the Invention

[0003] The endoscope device according to an embodiment of the present invention includes: an endoscope that photographs a subject in the body of a subject and outputs a captured image signal; a processor that performs image processing on the captured image signal to generate a subject image, and the processor normalizes the sum of the red pixel value and the green pixel value of each of a plurality of pixels in at least a part of the subject image using the blue pixel value, thereby calculating an index for each pixel, selects a threshold set corresponding to the combination of the endoscope information and the processor information from a plurality of threshold sets corresponding to a plurality of combinations of the plurality of endoscope information and the plurality of processor information, uses the selected threshold set to identify the symptom level of each pixel as one of a plurality of symptom levels, obtains an identification color corresponding to the symptom level of each pixel, generates an identification image using the identification colors of the plurality of pixels; and a monitor that displays the identification image.

[0004] The working method of the endoscope device according to an embodiment of the present invention performs image processing on a captured image signal obtained by photographing a subject in the body of a subject to generate a subject image, normalizes the sum of the red pixel value and the green pixel value of each of a plurality of pixels in at least a part of the subject image using the blue pixel value, thereby calculating an index for each pixel, selects a threshold set corresponding to the combination of the endoscope information and the processor information from a plurality of threshold sets corresponding to a plurality of combinations of the plurality of endoscope information and the plurality of processor information, uses the selected threshold set to identify the symptom level of each pixel as one of a plurality of symptom levels, obtains an identification color corresponding to the symptom level of each pixel, generates an identification image using the identification colors of the plurality of pixels, and displays the identification image.

[0005] A program product according to an embodiment of the present invention includes a program that causes a computer to perform the following processes: performing image processing on a captured image signal output by an endoscope that captures a subject inside a subject to generate a subject image; normalizing, using a blue pixel value, the sum of a red pixel value and a green pixel value of each of a plurality of pixels in at least a part of the subject image, thereby calculating an index for each pixel; selecting a threshold set corresponding to a combination of endoscope information and processor information from a plurality of threshold sets corresponding to a plurality of combinations of a plurality of endoscope information and a plurality of processor information; using the selected threshold set, identifying a symptom level of each pixel as one level among a plurality of symptom levels; obtaining an identification color corresponding to the symptom level of each pixel; generating an identification image using the identification colors of the plurality of pixels; and displaying the identification image. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1 FIG. is a diagram showing the configuration of an endoscope apparatus according to an embodiment of the present invention.

[0007] Figure 2 FIG. is a diagram for explaining the relationship between the light absorption characteristics of plasma and the light emission characteristics of a light source.

[0008] Figure 3 FIG. is a diagram for explaining the light absorption characteristics of a subject and the like.

[0009] Figure 4 FIG. is a diagram for explaining the calculation formula of an index of an endoscope apparatus according to an embodiment of the present invention.

[0010] Figure 5 FIG. is a diagram for explaining the calculation formula of an index of an endoscope apparatus according to an embodiment of the present invention.

[0011] Figure 6 FIG. is a flowchart of an operation method of an endoscope apparatus according to an embodiment of the present invention.

[0012] Figure 7 FIG. is a table of a plurality of threshold sets in an endoscope apparatus according to an embodiment of the present invention.

[0013] Figure 8 FIG. is a diagram showing the relationship between a symptom level and a threshold in an endoscope apparatus according to an embodiment of the present invention.

[0014] Figure 9 FIG. is a diagram showing the relationship between a symptom level and an identification color in an endoscope apparatus according to an embodiment of the present invention.

[0015] Figure 10 FIG. is an example of a screen of a monitor in an endoscope apparatus according to an embodiment of the present invention.

[0016] Figure 11They are multiple sets of calibration coefficients and standard threshold sets in the endoscope device according to Variant Example 1 of the embodiment of the present invention. Detailed Embodiment

[0017] <Structure of Endoscope Device>

[0018] As Figure 1 shown, the endoscope device 1 of the embodiment includes an endoscope 10, a light source device 20, a processor 30, a monitor 40, and a third memory 50.

[0019] The endoscope 10 has an elongated insertion portion 11 inserted into a subject 90, an operation portion 12 provided at the proximal end of the insertion portion 11, a general cable 13 extending from the operation portion 12, and a connector 14. The operation portion 12 has a plurality of buttons 12A and the like as an endoscope setting portion for operating the endoscope function and the imaging function. The insertion portion 11 of the endoscope 10 sequentially includes a distal end portion 11A, a bending portion 11B provided at the proximal end of the distal end portion 11A, and an elongated flexible tube 11C provided at the proximal end of the bending portion 11B. A imaging unit 15 as an imaging portion and a lighting unit 16 as a lighting portion are provided at the distal end portion 11A.

[0020] The connector 14 of the endoscope 10 is connected to the light source device 20 and the processor 30. The illumination light L generated by the light source device 20 is guided to the illumination unit 16 at the distal end portion 11A of the insertion portion 11 to illuminate the subject 91 in the body of the subject 90. The imaging unit 15 has an imaging element such as a CCD. The imaging unit 15 converts the reflected light R from the subject 91 into an electrical signal and outputs the imaging signal of the subject image to the processor 30.

[0021] The endoscope 10 has a first memory 17 for storing endoscope information. In the present embodiment, the endoscope information is endoscope model data such as the model number of the endoscope 10. The first memory 17 is, for example, a RAM, a ROM, or an RF-ID tag.

[0022] The light source device 20 includes a light source control portion 22, a light source 23, and a multiplexer 24.

[0023] The light source control portion 22 is connected to the light source 23 and is a light source control circuit for controlling the light source 23 according to a control signal from the processor 30.

[0024] The light source 23 has a plurality of light-emitting elements such as LEDs, for example. The light source 23 has an R element 23R, a G element 23G, and a B element 23B. The R element 23R emits red light Br in a normal band. The G element 23G emits green light Bg in a normal band. The B element 23B emits blue light Bb in a normal band. The B element 23B not only outputs blue light Bb in a normal band, but also narrow-band blue light Nb by, for example, a narrow-band optical filter (not shown).

[0025] The multiplexer 24 multiplexes the plurality of light beams input from the light source 23 and outputs illumination light L to the illumination unit 16.

[0026] The processor 30 has an image processing unit 31, a calculation unit 32, an identification unit 33, an identification color acquisition unit 34, an image generation unit 35, a setting unit 36, and a second memory 37. The processor 30 constituted by a CPU controls the entire endoscope apparatus 1, and generates an endoscope image based on the imaging signal input from the endoscope 10. As will be described later, an identification image is generated based on the endoscope image. The second memory 37 is, for example, a RAM or a ROM that stores processor information. In the present embodiment, the processor information is processor model data such as the model number of the processor 30.

[0027] The setting unit 36, which is a setting circuit, is a button or the like for a user to input various instructions. The setting unit 36 may also be a touch panel, a keyboard, a foot switch, a button 12A of the endoscope 10, etc., which are separate from the processor 30. For example, instructions such as a bending instruction for the bending unit, a driving instruction for the light source device 20, the type of illumination light L for illuminating the subject 91, the type of the observation site of the subject 91, and the image displayed on the monitor 40 are input from the setting unit 36.

[0028] In addition, the configurations of the image processing unit 31, the calculation unit 32, the identification unit 33, the identification color acquisition unit 34, and the image generation unit 35 will be described later.

[0029] At least one of the plurality of structures of the processor 30 and the light source control unit 22 may be constituted by an internal circuit (CPU) that operates by software (program), or may be constituted by a dedicated hardware circuit.

[0030] The monitor 40 is, for example, a liquid crystal or a CRT that displays a color image. The monitor 40 displays the image instructed from the processor 30. The monitor 40 having the function of a touch panel may also constitute a part of the setting unit 36.

[0031] The third memory 50 is a RAM, ROM, or hard disk drive device that stores data such as operating conditions for the processor 30, programs, and the like. The third memory 50 may also be a non-transitory computer-readable storage medium such as a CD or DVD. The processor 30 performs predetermined processing based on the programs and data stored in the third memory 50. In addition, past examination data of the subject 90, such as stored in a server separate from the endoscope apparatus 1, may be transferred to the third memory 50 via the Internet or the like.

[0032] The calculation unit 32 is a calculation circuit that calculates an index VI for each of a plurality of pixels of the subject image output by the imaging unit, and calculates the index VI that quantitatively represents the symptom level of the subject 91 using a predetermined calculation formula.

[0033] The following describes the process of selecting the calculation formula.

[0034] Figure 2 Graph illustrating the relationship between the light absorption characteristic W of plasma and the wavelength of light generated by the light source 23. Figure 2 , normal-band red light Br, normal-band green light Bg, normal-band blue light Bb, narrow-band blue light Nb, the absorption characteristic W of plasma, and the peak wavelength Wp of the absorption coefficient of plasma are shown.

[0035] like Figure 2 As shown, the light absorption characteristic W of plasma decreases near a wavelength of 415 nm, reaches a peak near a wavelength of 465 nm, and approaches 0 near a wavelength of 550 nm.

[0036] Therefore, while blue light Bb can be of a normal frequency band, it is particularly preferable to narrowband it to a wavelength that is equal to the peak wavelength Wp of the plasma absorption coefficient in order to significantly detect plasma. For example, blue light Bb can be narrowbanded to a wavelength around 465 nm and used as narrowband blue light Nb. Blue light Bb can also be narrowbanded to a wavelength between 460 nm and 470 nm. Furthermore, blue light Bb can be narrowbanded to a wavelength between 415 nm and 495 nm.

[0037] When irradiated with special light including red light Br, green light Bg and narrow-band blue light Nb, plasma absorbs more blue light than red and green light, and exhibits a stronger yellow hue than when irradiated with normal light including normal blue light Bb.

[0038] then, Figure 3 A cross-section of the mucosa is schematically shown. Figure 3 The diagram shows normal mucosa N, edema M, polyps S, blood vessels Bv, and illumination light L. Here, illumination light L is short-wavelength monochromatic light such as narrow-band blue light Nb. The pigment in the mucosa is plasma.

[0039] As shown in the light propagation region L1, in the normal mucosa N, the propagation degree of the illumination light L is high. Compared with the long wavelength side, on the short wavelength side, due to the mucosal pigments with high absorption coefficients, the reflected light R appears light yellow.

[0040] As shown in the light propagation region L2, in the edema M, the propagation degree of the illumination light L is lower than that in the normal mucosa N. More specifically, in the edema M, due to the thickened epithelium, compared with the long wavelength side, the illumination light L is scattered more on the short wavelength side and is reflected without being absorbed by the pigments in the mucosa. Therefore, in the edema M, the reflected light R clearly appears whiter than the normal mucosa N.

[0041] As shown in the light propagation region L3, in the polyp S, compared with the edema M, the light propagation degree is further reduced, and compared with the edema M, the reflected light R further clearly appears whiter.

[0042] Figure 4 Indicates an index VI obtained by normalizing the green pixel value Vg, red pixel value Vr, blue pixel value Vb of the pixels included in the endoscopic image, or the sum of the green pixel value Vg and the red pixel value Vr, respectively. Regarding the pixel value V, for example, 8-bit data (0 - 255) is acquired.

[0043] Figure 4 Indicates the difference in the index VI caused by the difference in the calculation formula of the index VI among the normal mucosa N, edema M, and polyp S. In Figure 4 it, "Vg / Vb", "Vr / Vb", "Vr / Vg", "(Vr + Vg) / 2Vb" on the X-axis respectively indicate the calculation formula of the index VI, and the Y-axis indicates the index VI obtained by normalizing through each calculation formula.

[0044] The solid line indicates the normal mucosa N, the single-dot dash line indicates the edema M, and the double-dot dash line indicates the polyp S. Hereinafter, the edema M and the polyp S are referred to as abnormal mucosa.

[0045] In the mucosa in the body, such as the mucosa of the paranasal sinuses, in the order of the normal mucosa N, edema M, and polyp S, the symptom grade becomes heavier. Between the normal mucosa N and the abnormal mucosa, the colors are different. As the symptom grade becomes heavier, the mucosal epithelium thickens, and the whiteness in appearance also becomes stronger. Therefore, the calculation formula with the largest index VI for the normal mucosa N and the polyp S is "(Vr + Vg) / 2Vb".

[0046] Figure 5 Indicates the index VIN of the edema M and the polyp S obtained by normalizing the index VI of the same edema M and polyp S as Figure 4 through the normal mucosa N. In Figure 5In this figure, the X-axis shows the formula for calculating the index VIN for calculating the index VIN, which is obtained by normalizing the index VI of the normal mucosa N, and the Y-axis shows the index VIN.

[0047] As Figure 4 and Figure 5 shown, in the normal mucosa N and the polyp S, the indices VI and VIN calculated by the formula "(Vr + Vg) / 2Vb" are greater than the indices VI and VIN calculated by other index formulas.

[0048] That is, the index VIN calculated by the formula "(Vr + Vg) / 2Vb" shows a relatively large difference in color between the normal mucosa N and the abnormal mucosa.

[0049] <Method of Operating an Endoscope Device>

[0050] The method of operating the endoscope device 1 will be described using Figure 6 a flowchart.

[0051] <Step S10> Illumination Light Irradiation

[0052] The insertion portion 11 of the endoscope 10 is inserted into the living body of the subject 90, such as the nasal cavity. The illumination light L from the light source device 20 is irradiated onto the mucosa as the subject 91 via the illumination unit 16 at the distal end portion 11A. The illumination light L is red light Br, green light Bg, and blue light Bb.

[0053] <Step S20> Output of a Video Signal

[0054] The imaging unit 15 at the distal end portion 11A receives the reflected light R from the subject 91, converts it into an electrical signal, and outputs the video signal to the processor 30.

[0055] <Step S30> Image Processing

[0056] The image processing unit 31 is an image processing circuit that performs image processing such as gain adjustment, white balance adjustment, gamma correction, contour enhancement correction, and magnification adjustment based on the video signal, and generates an endoscope image as the subject image.

[0057] <Step S40> Index Calculation

[0058] The calculation unit 32 normalizes the sum of the red pixel value Vr and the green pixel value Vg of each of the plurality of pixels of the subject image by twice the value of the blue pixel value Vb (Nb), thereby calculating the index VI for each pixel. In other words, the calculation unit 32 calculates the index VI for a plurality of regions (pixels) of the subject.

[0059] In Figure 4 , Figure 5In the example shown, "(Vr + Vg) / 2Vb" is used as the calculation formula for normalizing the pixel value and calculating the index VI. However, as long as it is a calculation formula that normalizes the sum of the red pixel value and the green pixel value by the blue pixel value, it can be appropriately changed.

[0060] For example, the index VI can be converted into 8-bit (0 - 255) data, and a value can be further added to the 8-bit data, or the k value of the calculation formula "(Vr + Vg) / kVb" can be changed. Hereinafter, the index VI is calculated using Equation 1.

[0061] <Equation 1>

[0062] VI = 32 × log2[(Vr + Vg) / 2Vb] + 256

[0063] The calculation unit 32 preferably calculates the index VI using any one of a plurality of calculation formulas corresponding to a plurality of subjects 91 (for example, paranasal sinuses, digestive tract).

[0064] In addition, the calculation unit 32 can divide the subject image into regions composed of a plurality of pixels (for example, in units of 25 pixels of 5 × 5), and calculate the index VI for each region. That is, the calculation unit 32 can also calculate the index based on the average value of the pixel values of the plurality of pixels included in each region.

[0065] Some pixels of each region and adjacent regions may overlap with each other (for example, 16 pixels on the outer periphery of a 25-pixel region of 5 × 5).

[0066] <Step S50> Threshold set selection

[0067] The recognition unit 33 is a recognition circuit that selects a threshold set TS for recognition from a plurality of threshold sets TS ( Figure 7 ), and recognizes the symptom level of each pixel using the selected threshold set TS according to the index VI.

[0068] In the endoscope device 1, the symptom levels are five types: "normal / mild / moderate / severe / most severe". If there are three or more symptom levels, it is easier to judge detailed symptoms than in the case of two types: "normal / abnormal".

[0069] To recognize five symptom levels, four thresholds T are required (the first threshold T1 for recognizing normal and mild, the second threshold T2 for recognizing mild and moderate, the third threshold T3 for recognizing moderate and severe, and the fourth threshold T4 for recognizing severe and most severe).

[0070] The recognition unit 33 selects from a table of a plurality of threshold sets TS corresponding to a plurality of combinations of a plurality of endoscopes and a plurality of processors stored in the second memory 37 or the third memory 50 (Figure 7 ) Select a threshold set TS for recognition. The table of the threshold set TS is appropriately set in advance based on the judgments of multiple recognizers, etc.

[0071] The recognition unit 33 obtains the endoscope information of the connected endoscope 10 from the first memory 17 of the endoscope 10 via wire or wirelessly. The endoscope information may also be input by the user using the setting unit 36 of the processor 30. The processor information of the processor 30 is stored in the second memory 37, for example.

[0072] <Step S60> Symptom level recognition

[0073] Figure 8 shows an example of multiple thresholds T when the endoscope 10 is endoscope A and the processor 30 is processor A ( Figure 7 ) The recognition unit 33 recognizes the symptom level of each pixel using the selected threshold set TS based on the index VI calculated by the calculation unit 32.

[0074] <Step S70> Recognition color acquisition

[0075] The recognition color acquisition unit 34 acquires the recognition color corresponding to the symptom level of the pixel acquired by the recognition unit 33.

[0076] Figure 9 shows the recognition color corresponding to the symptom level. The index VI is data in the range of (0 - 511) obtained by adding 256 to 8-bit data, for example. The multiple thresholds T and the recognition color are stored in the second memory 37.

[0077] In addition, in Figure 9 's example, the recognition color acquisition unit 34 acquires multiple colors with different hues, but may also acquire multiple chromas with different vividness, multiple lightness with different brightness, multiple hatching with different intervals, or multiple patterns with different patterns, etc.

[0078] In addition, in the subject image, there may be pixels with incorrect pixel values, which are pixel values of colors that do not occur in normal shooting. In the endoscope device 1, a pixel with a pixel value V in which at least one of the red pixel value, the green pixel value, and the blue pixel value is below a specified lower limit pixel value or above a specified upper limit pixel value is defined as a first incorrect pixel. For example, among the pixels with a pixel value V in the range of (0 - 255), a pixel with a pixel value V of 5 or less or 250 or more is a first incorrect pixel.

[0079] In addition, a pixel of the index VI below a specified lower threshold or above a specified upper threshold is defined as a second incorrect pixel. For example, in Figure 9In the example shown, pixels where the index VI is below the lower threshold of 10 or above the upper threshold of 500 are second error pixels.

[0080] The recognition color acquisition unit 34 acquires the error color for the error pixels (first error pixels and second error pixels). The image generation unit generates a recognition image using the error color for the error pixels. The error color is not limited to Figure 9 the white / black exemplified, and can also be gray or the like, for example. In addition, the color of pixels that are below the lower limit and above the upper limit such as the threshold value can also be the same error color. The numerical values of the determination criteria for the error pixels and the data of the error color are stored in advance in the second memory 37 or the third memory 50.

[0081] <Step S80> Recognition image generation

[0082] The recognition color acquisition unit 34 acquires the recognition color corresponding to the symptom level of each pixel. The image generation unit 35 is a recognition color acquisition circuit that generates a recognition image using the recognition color of each of the plurality of pixels.

[0083] <Step S90> Display

[0084] The monitor 40 displays the recognition image.

[0085] Figure 10 An example of the display image of the monitor 40 is shown. In Figure 10 this, a part of the region of the endoscope image 40A with color display is replaced with the recognition image 40B and displayed. In other words, an overlapping image in which the recognition image 40B overlaps the endoscope image 40A is displayed.

[0086] In addition, on the monitor 40, the average value 40D of the index is displayed together with the recognition color list display 40C. That is, the calculation unit 32 calculates the average value 40D of the indexes of the plurality of pixels, and the monitor 40 displays the average value 40D of the indexes.

[0087] The user can easily grasp the symptoms of the subject based on the average value 40D of the index.

[0088] It is also possible to display only the recognition image 40B on the monitor 40. That is, it is also possible that the calculation unit 32 calculates the index based on the plurality of pixels in the entire region of the endoscope image 40A that is the subject image, and the image generation unit 35 generates a recognition image corresponding to the entire region of the endoscope image 40A.

[0089] In addition, the endoscopic image 40A can be displayed in the main area of the monitor 40, and the recognition image 40B of the area surrounded by the frame in the endoscopic image 40A can be displayed in an area different from the endoscopic image 40A. At least one of the position and range (area) of a part of the area for generating the recognition image 40B in the entire area of the endoscopic image 40A as the subject image can be appropriately selected by the operation of the setting unit 36.

[0090] Inside a narrow pipeline, it is sometimes not easy to orient the center of the endoscopic image 40A (the center of the field of view of the imaging unit 15) towards the area of interest. However, by selecting at least one of the position and range of the area for displaying the recognition image 40B, the user can easily identify the area of interest.

[0091] The endoscopic device 1 of the present embodiment can display an appropriate recognition image according to the combination of the endoscope and the processor. In the present embodiment, the threshold value is determined according to the combination of the endoscope and the processor, but the threshold value can also be determined according to the combination with the light source device or the monitor in the endoscopic system. In this case, a memory for storing the model information is provided in the light source device or the monitor, and the information is read out via the connection line.

[0092] As described above, in the working method of the endoscopic system of the embodiment, the imaging signal obtained by photographing the subject inside the examinee is subjected to image processing to generate a subject image. For the sum of the red pixel value and the green pixel value of each of the plurality of pixels in at least a part of the area of the subject image, it is normalized using the blue pixel value, thereby calculating an index for each pixel. A threshold set corresponding to the combination of the endoscope information and the processor information is selected from a plurality of threshold sets corresponding to a plurality of combinations of the plurality of endoscope information and the plurality of processor information. The symptom level of each pixel is identified as one of the plurality of symptom levels using the selected threshold set, the recognition color corresponding to the symptom level of each pixel is obtained, and the recognition image is generated using the recognition colors of the plurality of pixels, and the recognition image is displayed.

[0093] A program product of another embodiment causes a computer to execute the above processing.

[0094] A storage medium of another embodiment is a non-transitory computer-readable storage medium storing a program for causing a computer to execute the above processing.

[0095] <Modification Example>

[0096] The endoscopic devices 1A - 1C of the modification example are similar to the endoscopic device 1 of the embodiment and have the same effects as the endoscopic device 1. Therefore, in the following description, the constituent elements having the same functions as those of the endoscopic device 1 are denoted by the same reference numerals and the description thereof is omitted.

[0097] <Modified Example 1>

[0098] In the endoscope apparatus 1A of this modified example, a correction data set and a standard threshold set selected from a table of a plurality of correction data sets corresponding to combinations of a plurality of endoscope information and a plurality of processor information are used to obtain a threshold set TS( Figure 11 ). The correction data set and the standard threshold set are stored, for example, in the second memory 37 or the third memory 50.

[0099] For example, when the endoscope 10 is endoscope B and the processor 30 is processor B, the first threshold T1 is 290 (= 296 × 0.98).

[0100] The capacity of the data stored in the second memory 37 or the like of the endoscope apparatus 1A is smaller than that of the endoscope apparatus 1.

[0101] <Modified Example 2>

[0102] Even for the same model manufactured with the same specifications, there are individual differences between the endoscope 10 and the processor 30.

[0103] In the endoscope apparatus 1B of this modified example, the endoscope information is endoscope model data such as the model number of the endoscope 10 and endoscope individual data such as the manufacturing number. The processor information is processor model data such as the model number of the processor 30 and processor individual data such as the manufacturing number.

[0104] Endoscope individual data such as the manufacturing number of the endoscope sometimes includes information on endoscope model data such as the model number. Similarly, processor individual data such as the manufacturing number of the processor sometimes includes information on processor model data such as the model number.

[0105] Therefore, in the endoscope apparatus 1B, the endoscope information can be endoscope individual data, and the processor information can be processor individual data.

[0106] For example, the endoscope individual data is a correction coefficient stored in the first memory 17 during the factory inspection after the manufacture of the endoscope 10. The processor individual data is a correction coefficient stored in the second memory 37 during the factory inspection after the manufacture of the processor 30.

[0107] For example, in the Figure 7 or Figure 11 shown table, when the endoscope 10 is endoscope A, the correction coefficient of the endoscope individual data is 0.99, the processor 30 is processor A, and the correction coefficient of the processor individual data is 1.02, the first threshold T1 is 266 (= 293 × 0.99 × 1.02).

[0108] In the endoscope apparatus 1C, even if there are individual differences between the endoscope and the processor, an appropriate recognition image can be displayed.

[0109] <Modification Example 3>

[0110] The tone or the like of the endoscope image is sometimes changed by the user's adjustment of the setting unit 36. In the endoscope apparatus 1C of this modification example, the threshold set TS is corrected according to a change in the image processing parameter.

[0111] For example, when the red level is adjusted by +5%, the processor 30 multiplies all the thresholds T of the threshold set TS by a correction coefficient of 1.10. On the contrary, when the red level is adjusted by -5%, the processor 30 multiplies all the thresholds T of the threshold set TS by a correction coefficient of 0.92.

[0112] In the endoscope apparatus 1C, even if the endoscope image is adjusted by the user, an appropriate recognition image can be displayed.

[0113] According to an embodiment of the present invention, an endoscope apparatus capable of displaying an appropriate recognition image according to a combination of an endoscope and a processor, a working method of the endoscope apparatus capable of displaying an appropriate recognition image according to a combination of an endoscope and a processor, and a storage medium storing a program of the endoscope apparatus capable of displaying an appropriate recognition image according to a combination of an endoscope and a processor can be provided.

[0114] It should be noted that the range of the values described above, such as the wavelength, is not limited to the range described above and can be appropriately increased or decreased. Also, the insertion portion 11 of the endoscope 10 may be a rigid endoscope. The present invention is not limited to the above-described embodiments and the like, and various changes and modifications can be made without departing from the gist of the present invention.

Claims

1. An endoscope device, wherein, Comprising: An endoscope that captures an object inside a subject and outputs a captured image signal; A processor that performs image processing on the captured image signal to generate a subject image. The processor normalizes the sum of the red pixel value and the green pixel value of each of a plurality of pixels in at least a partial region of the subject image using the blue pixel value to calculate an index for each pixel. The processor selects a threshold set corresponding to the combination of the endoscope information and the processor information from a plurality of threshold sets corresponding to a plurality of combinations of a plurality of endoscope information and a plurality of processor information, and uses the selected threshold set to identify the symptom level of each pixel as one of a plurality of symptom levels. The processor obtains an identification color corresponding to the symptom level of each pixel, and the processor uses the identification colors of the plurality of pixels to generate an identification image; and A monitor that displays the identification image.

2. The endoscope apparatus according to claim 1, wherein The endoscope information is at least one of endoscope model data and endoscope individual data, The processor information is at least one of processor model data and processor individual data.

3. The endoscope apparatus according to claim 2, wherein The plurality of threshold sets include a plurality of correction data sets corresponding to a plurality of combinations of the plurality of endoscope information and the plurality of processor information and a standard threshold set.

4. The endoscope apparatus according to claim 2, wherein The processor corrects the threshold set according to the change in the parameters of the image processing.

5. The endoscope apparatus according to any one of claims 1 to 4, wherein The sum of the red pixel value and the green pixel value is normalized using twice the value of the blue pixel value to calculate the index for each pixel.

6. A method for processing an endoscope image, wherein The sum of the red pixel value and the green pixel value of each of a plurality of pixels in at least a partial region of the subject image is normalized using the blue pixel value, thereby calculating an index for each pixel, A threshold set corresponding to the combination of the endoscope information and the processor information is selected from a plurality of threshold sets corresponding to a plurality of combinations of a plurality of endoscope information and a plurality of processor information, Using the selected threshold set, the symptom level of each pixel is identified as one of a plurality of symptom levels, An identification color corresponding to the symptom level of each pixel is obtained, An identification image is generated using the identification colors of the plurality of pixels, and the identification image is displayed.

7. The method for processing an endoscope image according to claim 6, wherein The endoscope information is at least one of endoscope model data and endoscope individual data, The processor information is at least one of processor model data and processor individual data.

8. The method for processing an endoscope image according to claim 6 or 7, wherein The sum of the red pixel value and the green pixel value is normalized using twice the value of the blue pixel value to calculate the index for each pixel.

9. A program product, wherein, A program that causes a computer to perform the following processing: For the sum of the red pixel values and green pixel values of each of the multiple pixels in at least a part of the subject image, standardize it using the blue pixel value, thereby calculating an index for each pixel. Select a threshold set corresponding to the combination of the endoscope information and the processor information from multiple threshold sets corresponding to multiple combinations of the multiple endoscope information and the multiple processor information. Using the selected threshold set, identify the symptom level of each pixel as one of multiple symptom levels. Obtain an identification color corresponding to the symptom level of each pixel. Generate an identification image using the identification colors of each of the multiple pixels. Display the identification image.

10. The program product according to claim 9, wherein The subject image is generated by performing image processing on a captured image signal output by an endoscope capturing a subject inside a subject.

11. The program product according to claim 9 or 10, wherein The index for each pixel is calculated by standardizing the sum of the red pixel value and the green pixel value using a value that is twice the blue pixel value.

12. A computer-readable storage medium having a program stored thereon, wherein When the program is executed, it implements the endoscopic image processing method according to any one of claims 6 to 8, or the program is the program according to any one of claims 9 to 11.

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