JP2006314557A - Biological observation apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a biological observation apparatus capable of calculating biological function information relating to the blood of a living body on the basis of spectroscopic image signals obtained by signal processing and contributing to the improvement of diagnostic ability. <P>SOLUTION: The output of a matrix operation part 436 is connected to integration parts 438a-438c respectively, an integration operation is performed, then a color adjustment operation is performed in a color adjustment part 440 to the respective stereoscopic image signals ΣF1-ΣF3, and stereoscopic color channel image signals Rch, Gch and Bch are generated from the stereoscopic image signals ΣF1-ΣF3. Also, an IHb value is computed from the stereoscopic image signals ΣF1-ΣF3 in a biological function operation part 450, biological function images are generated from the IHb value, and an observation image by the stereoscopic color channel image signals Rch, Gch and Bch and the biological function image based on the IHb value are displayed on a display monitor 106 through a switching part 439. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a living body observation apparatus that observes a living body.

  2. Description of the Related Art Conventionally, endoscope apparatuses that irradiate illumination light and obtain an endoscopic image in a body cavity have been widely used. In this type of endoscope apparatus, an electronic endoscope having an image pickup unit that guides illumination light from a light source device into a body cavity using a light guide or the like and picks up an image of a subject using the return light is used. An image signal from the imaging means is signal-processed to display an endoscopic image on an observation monitor and observe an observation site such as an affected area.

  When performing normal biological tissue observation in an endoscopic device, the light source device emits white light in the visible light region, and irradiates the subject with surface sequential light through a rotating filter such as RGB, for example. A color image is obtained by synchronizing the return light from the light with a video processor and processing the image, or a color chip is arranged in front of the imaging surface of the imaging means of the endoscope, and the return light from the white light is used for each color component by the color chip. A color image is obtained by taking an image by separating each image and processing the image with a video processor.

  On the other hand, in a living tissue, the light absorption characteristics and the scattering characteristics differ depending on the wavelength of the irradiated light. For example, in Japanese Patent Application Laid-Open No. 2002-95635, illumination light in the visible light region has a narrow spectral bandwidth. A narrow-band optical endoscope apparatus that irradiates a living tissue with RGB sequential light and obtains tissue information of a desired deep portion of the living tissue has been proposed.

Japanese Patent Application Laid-Open No. 2003-93336 discloses a narrowband optical endoscope that generates a discrete spectral image by performing signal processing on an image signal from illumination light in the visible light region and obtains tissue information of a desired deep part of a living tissue. A mirror device has been proposed.
JP 2002-95635 A JP 2003-93336 A

  However, for example, in Japanese Patent Application Laid-Open No. 2003-93336, a spectral image is obtained by signal processing, so that a filter for generating narrow band RGB light is not required, but the obtained spectral image is simply output to a monitor. is doing. For this reason, there is a possibility that the image displayed on the monitor may not be an image having a color tone suitable for observing tissue information in a desired deep part of the biological tissue, and the relationship with biological function information such as hemoglobin concentration in the blood. It becomes difficult to grasp.

  The present invention has been made in view of the above circumstances, and displays biological function information related to tissue information of a desired deep part of a biological tissue based on a spectral image obtained by signal processing to improve diagnostic ability. It aims at providing the biological observation apparatus which can contribute.

  The living body observation apparatus of the present invention controls the operation of the illuminating means for irradiating the subject with light, the observing means for acquiring a biological signal, the illuminating means and / or the observing means, and sends the biological signal to the display output device. In the observation apparatus configured to display and output signal processing means, the signal processing control means calculates a biological function from the spectral signal generating means, a spectral signal generating means for generating a spectral signal from the biological signal, And a biological function calculating means for outputting to the display output device.

  According to the present invention, it is possible to display biological function information related to tissue information of a desired deep part of a biological tissue based on a spectral image obtained by signal processing, and it is possible to contribute to improvement of diagnostic ability. There is.

  Embodiments of the present invention will be described below with reference to the drawings.

  1 to 25 relate to the first embodiment of the present invention, FIG. 1 is a conceptual diagram showing a signal flow when a spectral image signal is created from a color image signal, and FIG. 2 is a conceptual diagram showing an integral operation of the spectral image signal. 3 is an external view showing the external appearance of the electronic endoscope apparatus, FIG. 4 is a block diagram showing the configuration of the electronic endoscope apparatus of FIG. 3, and FIG. 5 is an external view showing the external appearance of the chopper of FIG. 6 is a diagram showing the arrangement of color filters arranged on the imaging surface of the CCD shown in FIG. 3, FIG. 7 is a diagram showing spectral sensitivity characteristics of the color filters shown in FIG. 6, and FIG. 8 is a diagram showing the configuration of the matrix calculation unit shown in FIG. FIG. 9 is a spectrum diagram showing a spectrum of a light source, FIG. 10 is a spectrum diagram showing a reflection spectrum of a living body, FIG. 11 is a diagram showing a layered structure of a living tissue observed by the electronic endoscope apparatus of FIG. 12 is a layer of biological tissue of illumination light from the electronic endoscope apparatus of FIG. FIG. 13 is a diagram illustrating spectral characteristics of each band of white light, FIG. 14 is a first diagram illustrating each band image of white light in FIG. 13, and FIG. 15 is a diagram illustrating FIG. FIG. 16 is a third diagram showing each band image by white light in FIG. 13, and FIG. 17 is a spectral characteristic of the spectral image generated by the matrix calculation unit in FIG. 18 is a first diagram showing each spectral image in FIG. 17, FIG. 19 is a second diagram showing each spectral image in FIG. 17, and FIG. 20 is a third diagram showing each spectral image in FIG. 21 is a block diagram showing the configuration of the color adjustment unit in FIG. 4, FIG. 22 is a diagram for explaining the operation of the color adjustment unit in FIG. 21, and FIG. 23 shows a modification of the color adjustment unit in FIG. FIG. 24 is a block diagram showing the configuration of the biological function calculation unit of FIG. 4, and FIG. A.

  Hereinafter, before describing Example 1 according to the present invention, a matrix calculation method as a basis of the present invention will be described. Here, the matrix is a predetermined coefficient used when generating a spectral image signal from a color image signal acquired to generate a color image (hereinafter referred to as a normal image). Further, following this description, a correction method for obtaining a more accurate spectral image signal and an S / N improvement method for improving the S / N ratio of the generated spectral image signal will be described. Note that this correction method and S / N improvement method may be used as necessary. In the following, vectors and matrices (matrix) are indicated by bold letters or “” (for example, the matrix A is indicated as “A bold letters of A” or “A” ”), and the others are indicated without character modification.

(Matrix calculation method)
FIG. 1 shows a color image signal (here, R, G, and B for simplicity of explanation, but in a complementary color solid-state imaging device as in the embodiments described later, G, Cy, Mg, FIG. 4 is a conceptual diagram showing a signal flow when generating a spectral image signal corresponding to an image corresponding to an image in a narrower optical wavelength band.

  First, the R, G, and B color sensitivity characteristics in the electronic endoscope apparatus are converted into numerical data. Here, the color sensitivity characteristics of R, G, and B are output characteristics with respect to wavelengths obtained when a white object is imaged using a white light source.

  The color sensitivity characteristics of R, G, and B are shown on the right of each image data as a simplified graph. Further, the color sensitivity characteristics of R, G, and B at this time are assumed to be n-dimensional column vectors “R”, “G”, and “B”, respectively.

  Next, spectral band narrow-pass filters F1, F2, F3 (knowing the characteristics of filters that can extract structures efficiently as foresight information. The characteristics of this filter are that the wavelength band is approximately 590 nm to 610 nm, about 530 nm to about 550 nm, and about 400 m to about 430 nm are used as passbands, respectively).

となるマトリックスの要素を求めればよい。 Here, “substantially” is a concept including about 10 nm in wavelength. The filter characteristics at this time are n-dimensional column vectors “F1”, “F2”, and “F3”, respectively. Based on the obtained numerical data, an optimum coefficient set that approximates the following relationship is obtained. That is,
[Equation 1]

What is necessary is just to obtain the elements of the matrix.

となる。従って、（１）式に示した命題は、以下の関係を満足するマトリックス「Ａ」を求めるに等しい。 The solution of the above optimization proposition is given mathematically as follows: If the matrix representing the color sensitivity characteristics of R, G and B is “C”, the matrix representing the spectral characteristics of the narrow-band Pandpass filter to be extracted is “F”, and the coefficient matrix to be obtained is “A”.
[Equation 2]

It becomes. Therefore, the proposition shown in the equation (1) is equivalent to obtaining a matrix “A” that satisfies the following relationship.

ここで、分光特性を表すスペクトルデータとしての点列数nとしては、n＞３であるので、（３）式は１次元連立方程式ではなく、線形最小二乗法の解として与えられる。即ち、（３）式を擬似連立方程式として解けばよい。マトリックス「Ｃ」の転置行列を「^tＣ」とすれば、（３）式は
［数４］

となる。「^tＣＣ」はn×nの正方行列であるので、（４）式はマトリックス「Ａ」についての連立方程式と見ることができ、その解は、
［数５］

で与えられる。 [Equation 3]

Here, since the number of point sequences n as spectral data representing spectral characteristics is n> 3, equation (3) is not a one-dimensional simultaneous equation but is given as a solution of the linear least square method. That is, Equation (3) may be solved as a pseudo simultaneous equation. Assuming that the transposed matrix of the matrix “C” is “ ^t C”, the equation (3) is expressed by [Equation 4].

It becomes. Since “ ^t CC” is an n × n square matrix, equation (4) can be viewed as a simultaneous equation for the matrix “A”, and its solution is
[Equation 5]

Given in.

  By converting the left side of the equation (3) for the matrix “A” obtained by the equation (5), the characteristics of the narrow-band pan-pass filters F1, F2, and F3 to be extracted can be approximated. The above is the description of the matrix calculation method that is the basis of the present invention.

  Using the matrix calculated in this manner, a matrix calculation unit 436 described later generates a spectral image signal from the normal color image signal.

(Correction method)
Next, a correction method for obtaining a more accurate spectral image signal will be described.

  In the above description of the matrix calculation method, the light beam received by a solid-state imaging device such as a CCD is exactly white light (all wavelength intensities are the same in the visible range), and is applied accurately. . That is, the approximation is optimal when the RGB outputs are the same.

  However, under an actual endoscope, the illuminating light beam (light beam from the light source) is not completely white light, and the reflection spectrum of the living body is not uniform, so the light beam received by the solid-state imaging device is not white light (the color is The RGB values are not the same because they have arrived.)

  Therefore, in an actual process, in order to solve the proposition shown in the expression (3) more accurately, it is desirable to consider the spectral characteristics of illumination light and the reflection characteristics of a living body in addition to RGB color sensitivity characteristics.

  Here, the color sensitivity characteristics are respectively R (λ), G (λ), and B (λ), an example of the spectral characteristic of the illumination light is S (λ), and an example of the reflection characteristic of the living body is H (λ). . Note that the spectral characteristics of the illumination light and the reflection characteristics of the living body do not necessarily have to be the characteristics of the inspection apparatus and the subject, and may be general characteristics acquired in advance, for example.

Using these coefficients, the correction coefficients kR, kG, and kB are
[Equation 6]
kR = (∫S (λ) × H (λ) × R (λ) dλ) ⁻¹
kG = (∫S (λ) × H (λ) × G (λ) dλ) ⁻¹
kB = (∫S (λ) × H (λ) × B (λ) dλ) ⁻¹ (6)
Given in. When the sensitivity correction matrix is “K”, it is given as follows.

従って、係数マトリックス「Ａ」については、（５）式に（７）式の補正を加えて、以下のようになる。 [Equation 7]

Accordingly, the coefficient matrix “A” is as follows after adding the correction of the equation (7) to the equation (5).

また、実際に最適化を行う場合は、目標とするフィルタの分光感度特性（図１中のＦ1・Ｆ2・Ｆ3）が負の場合は画像表示上では０となる（つまりフィルタの分光感度特性のうち正の感度を有する部分のみ使用される）ことを利用し、最適化された感度分布の一部が負になることも許容することを付加する。ブロードな分光感度特性より狭帯域な分光感度特性を生成するためには、図１に示すように目標とするＦ1・Ｆ2・Ｆ3の特性に、負の感度特性を付加することで、感度を有する帯域を近似した成分を生成することができる。 [Equation 8]

When the optimization is actually performed, if the spectral sensitivity characteristics of the target filter (F1, F2, and F3 in FIG. 1) are negative, it becomes 0 on the image display (that is, the spectral sensitivity characteristics of the filter). Of these, only a part having a positive sensitivity is used), and it is added that a part of the optimized sensitivity distribution is allowed to be negative. In order to generate a narrower spectral sensitivity characteristic than a broad spectral sensitivity characteristic, it has sensitivity by adding a negative sensitivity characteristic to the target F1, F2, F3 characteristics as shown in FIG. A component approximating the band can be generated.

(S / N improvement method)
Next, a method for improving the S / N and accuracy of the generated spectral image signal will be described. This method for improving the S / N ratio solves the following problems by adding to the processing method described above.

(A) If any of the original signals (R, G, B) in the matrix calculation method described above is saturated, the characteristics of the filters F1 to F3 in the processing method are the characteristics of the filter that can extract the structure efficiently (ideal (In the case of R, G, and B, if two signals are generated only, the two original signals are not saturated).

(B) When a color image signal is converted into a spectral image signal, a narrowband filter is generated from a wideband filter. Therefore, sensitivity degradation occurs, and the component of the generated spectral image signal is also reduced. N ratio is not good.

  As shown in FIG. 2, the method of improving the S / N ratio is that illumination light is irradiated several times (for example, n times, n times) in one field (one frame) of a normal image (general color image). Is divided into two or more integers) (irradiation intensity may be changed each time. In Fig. 2, it is indicated by I0 to In. This is realized only by controlling illumination light. It is possible.)

  Thereby, the intensity of one irradiation can be reduced, and it is possible to suppress the saturation of all of the RGB signals. Further, the image signal divided into several times is added for n sheets in the subsequent stage. Thereby, a signal component can be enlarged and S / N ratio can be improved.

  The above is the matrix calculation method that is the basis of the present invention, the correction method for obtaining an accurate spectral image signal that can be performed together with this, and the method for improving the S / N ratio of the generated spectral image signal. It is an explanation.

  Here, a modified example of the above-described matrix calculation method will be described.

(Modification of matrix calculation method)
Assume that the color image signals are R, G, and B, and the spectral image signals to be estimated are F1, F2, and F3. Strictly speaking, since it is also a function of the position x, y on the image, it should be expressed as, for example, R (x, y), but is omitted here.

  The goal is to estimate a 3 × 3 matrix “A” that calculates F1, F2, F3 from R, G, B. If “A” is estimated, F1, F2, and F3 can be calculated from R, G, and B by the following equation (9).

ここで、以下のデータの表記を定義する。 [Equation 9]

Here, the following data notation is defined.

Spectral characteristics of subject: H (λ), “H” = (H (λ1), H (λ2),..., H (λn)) ^t
λ is a wavelength, and t represents transposition in matrix calculation. Similarly,
Spectral characteristics of illumination light: S (λ), “S” = (S (λ1), S (λ2),..., S (λn)) ^t
Spectral sensitivity characteristics of CCD: J (λ), “J” = (J (λ1), J (λ2),..., J (λn)) ^t
Spectral characteristics of filters for color separation: For primary colors
R (λ), “R” = (R (λ1), R (λ2),..., R (λn)) ^t
G (λ), “G” = (G (λ1), G (λ2),..., G (λn)) ^t
B (λ), “B” = (B (λ1), B (λ2),..., B (λn)) ^t
“R”, “G”, and “B” are combined into a matrix “C” as shown in the equation (10).

画像信号Ｒ，Ｇ，Ｂ、分光信号Ｆ1，Ｆ2，Ｆ3を行列で以下のように表記する。 [Equation 10]

The image signals R, G, B and the spectral signals F1, F2, F3 are expressed in matrix as follows.

画像信号「Ｐ」は次式で計算される。 [Equation 11]

The image signal “P” is calculated by the following equation.

いま、「Ｑ」を得るための色分解フィルタを「Ｆ」とすると、（１２）式同様に
［数１３］

ここで、重要な第１の仮定として、いま、被検体の分光反射率が基本的な３つの分光特性の線形和で表現できると仮定すると、「Ｈ」は以下のように表記できる。 [Equation 12]

Assuming that the color separation filter for obtaining “Q” is “F”, [Formula 13] as in the equation (12).

Here, as an important first assumption, assuming that the spectral reflectance of the subject can be expressed by a linear sum of three basic spectral characteristics, “H” can be expressed as follows.

ここで、「Ｄ」は３つの基本スペクトルＤ1（λ）、Ｄ2（λ）、Ｄ3（λ）を列ベクトルに持つ行列で、「Ｗ」は「Ｈ」に対するＤ1（λ）、Ｄ2（λ）、Ｄ3（λ）の寄与をあらわす重み係数である。被検体の色調がそれほど大きく変動しない場合には、この近似が成立することが知られている。 [Formula 14]

Here, “D” is a matrix having three basic spectra D1 (λ), D2 (λ), and D3 (λ) as column vectors, and “W” is D1 (λ) and D2 (λ) for “H”. , D3 (λ) is a weighting coefficient representing the contribution. It is known that this approximation is established when the color tone of the subject does not vary so much.

  Substituting equation (14) into equation (12) yields:

ここで、３×３の行列「Ｍ」は、行列「ＣＳＪＤ」の計算結果を１つにまとめた行列を示す。 [Equation 15]

Here, the 3 × 3 matrix “M” indicates a matrix in which the calculation results of the matrix “CSJD” are combined into one.

  Similarly, the following equation is obtained by substituting the equation (14) into the equation (13).

同じく、「Ｍ’」は、行列「ＦＳＪＤ」の計算結果を１つにまとめた行列を示す。 [Equation 16]

Similarly, “M ′” indicates a matrix in which the calculation results of the matrix “FSJD” are combined into one.

  Eventually, “W” is eliminated from the equations (15) and (16), and the following equation is obtained.

「Ｍ^-1」は行列「Ｍ」の逆行列を示す。結局、「Ｍ’Ｍ^-1」は３×３の行列となり、推定目標の行列「Ａ」となる。 [Equation 17]

“M ⁻¹ ” indicates an inverse matrix of the matrix “M”. Eventually, “M′M ⁻¹ ” is a 3 × 3 matrix, which is the estimation target matrix “A”.

色分解用のバンドパスが完全なバンドパスでなく、他の帯域にも感度を持つ場合も考慮して、この仮定が成立する場合、（１５）式、（１６）式における「Ｗ」を上記「Ｈ」と考えれば、結局（１７）式と同様な行列が推定できる。 Here, as an important second assumption, when color separation is performed using a bandpass filter, it is assumed that the spectral characteristic of the subject in the band can be approximated by one numerical value. That is,
[Equation 18]

In consideration of the case where the bandpass for color separation is not a complete bandpass and has sensitivity in other bands as well, if this assumption is satisfied, “W” in Expressions (15) and (16) is Considering “H”, a matrix similar to the equation (17) can be estimated after all.

  Next, a specific configuration of the electronic endoscope apparatus according to the first embodiment of the present invention will be described with reference to FIG. In addition, it is the same external appearance also in the other Example shown below.

  As shown in FIG. 3, the electronic endoscope apparatus 100 includes a scope 101, an endoscope apparatus main body 105, and a display monitor 106. The scope 101 is provided on the insertion portion 102 to be inserted into the body of the subject, the distal end portion 103 provided at the distal end of the insertion portion 102, and the distal end side of the insertion portion 102. It is mainly composed of an angle operation unit 104 for instructing a bending operation or the like.

  The subject image acquired by the scope 101 is subjected to predetermined signal processing in the endoscope apparatus main body 105, and the processed image is displayed on the display monitor 106.

  Next, the endoscope apparatus main body 105 will be described in detail with reference to FIG. FIG. 4 is a block diagram of the electronic endoscope apparatus 100.

  As shown in FIG. 4, the endoscope apparatus main body 105 mainly includes a light source section 41, a control section 42, and a main body processing apparatus 43.

  In this embodiment, the endoscope apparatus main body 105, which is one unit, will be described as having a light source unit 41 and a main body processing apparatus 43 that performs image processing and the like. You may be comprised so that removal is possible.

  The light source unit 41 is connected to the control unit 42 and the scope 101, and emits white light (including a case where the light is not perfect white light) with a predetermined light amount based on a signal from the control unit 42. The light source unit 41 includes a lamp 15 as a white light source, a chopper 16 for adjusting the light amount, and a chopper driving unit 17 for driving the chopper 16.

  As shown in FIG. 5, the chopper 16 has a configuration in which a notch having a predetermined length in the circumferential direction is provided in a disk-like structure having a predetermined radius r0 with the point 17a as the center. The center point 17a is connected to a rotating shaft provided in the chopper driving unit 17. That is, the chopper 16 performs rotational movement around the center point 17a. In addition, a plurality of notches are provided for each predetermined radius. In this figure, the notch has a maximum length = 2πr0 × 2θ0 degrees / 360 degrees and a width = r0−ra between the radius r0 and the radius ra. Similarly, the maximum length = 2πra × 2θ1 degrees / 360 degrees between the radius ra and the radius rb, the width = ra−rb, and the maximum length = 2πrb × 2θ2 between the radius rb and the radius rc. Degree / 360 degrees and width = rb−rc (respective radii are r0> ra> rb> rc).

  In addition, the length and width of the notch in the chopper 16 are examples, and are not limited to the present embodiment.

  Further, the chopper 16 has a protrusion 160a extending in the radial direction substantially at the center of the notch. In addition, by switching the frame when the light is blocked by the projection 160a, the interval between the light irradiated one frame before and after one frame is minimized, and the blur due to the movement of the subject is minimized. It is.

  Further, the chopper driving unit 17 is configured to be movable in the direction with respect to the lamp 15 as indicated by an arrow in FIG.

  That is, the distance R between the rotation center 17a of the chopper 16 shown in FIG. 5 and the luminous flux from the lamp (shown by a dotted circle) can be changed. For example, in the state shown in FIG. 5, since the distance R is quite small, the amount of illumination light is small. By increasing the distance R (the chopper driving unit 17 is moved away from the lamp 15), the cutout portion through which the light beam can pass becomes longer, so that the irradiation time becomes longer and the amount of illumination light can be increased.

  As described above, the newly generated spectral image may not be sufficient as S / N, and the correct calculation was performed when any signal required for generation was saturated. Therefore, it is necessary to control the amount of illumination light. The light amount adjustment is performed by the chopper 16 and the chopper driving unit 17.

  The light source unit 41 may adjust the light amount not by the light amount control by the chopper but by the current control of the lamp 15. That is, a current control device is provided in the lamp 15, and the current flowing through the lamp 15 is controlled based on a command from the control unit 42 so that none of the RGB color image signals are saturated. Thereby, since the current used for light emission in the lamp 15 is controlled, the amount of light changes according to the magnitude of the current.

  A spectral image in which a blood vessel pattern or the like is clearly displayed can be obtained even by current control of the lamp 15, but the current control of the lamp 15 has an advantage that the control method is simpler than the light amount control using a chopper. There is.

  The scope 101 connected to the light source unit 41 via the connector 11 includes an objective lens 19 and a solid-state imaging device 21 such as a CCD (hereinafter simply referred to as a CCD) at the distal end portion 103. The CCD in this embodiment is a single plate type (CCD used for a simultaneous electronic endoscope) and is a primary color type. The arrangement of the color filters is shown in FIG. FIG. 7 shows the spectral sensitivity characteristics of RGB.

  As shown in FIG. 4, the light guide 14 that guides the light emitted from the light source unit 41 to the distal end 103 is transmitted to the insertion unit 102, and the image of the subject obtained by the CCD is transmitted to the main body processing device 43. A signal line for performing treatment, a forceps channel 28 for performing treatment, and the like are provided. A forceps port 29 for inserting forceps into the forceps channel 28 is provided in the vicinity of the operation unit 104.

  Further, the main body processing device 43 is connected to the scope 101 via the connector 11, similarly to the light source unit 41. The main body processing device 43 is provided with a CCD drive 431 for driving the CCD 21. In addition, a luminance signal processing system and a color signal processing system are provided as signal circuit systems for obtaining a normal image.

  The luminance signal processing system includes a contour correction unit 432 that is connected to the CCD 21 and performs contour correction, and a luminance signal processing unit 434 that generates a luminance signal from data corrected by the contour correction unit 432. The color signal processing system is connected to the CCD 21, and samples and hold circuits (S / H circuits) 433a to 433c and S / H circuits 433a to 433c that sample the signals obtained by the CCD 21 and generate RGB signals. A color signal processing unit 435 is connected to the output and generates a color signal.

  In addition, a normal image generation unit 437 that generates one normal image from the outputs of the luminance signal processing system and the color signal processing system is provided, and a Y signal is output from the normal image generation unit 437 to the display monitor 106 via the switching unit 439. RY signal and BY signal are sent.

  On the other hand, as a signal circuit system for obtaining a spectral image, a matrix calculation unit 436 is provided at the output of the S / H circuits 433a to 433c, and a predetermined matrix calculation is performed on the RGB signals. Matrix calculation refers to a process of performing addition processing or the like between color image signals and multiplying the matrix obtained by the above-described matrix calculation method (or a modification thereof).

  In this embodiment, a method using electronic circuit processing (processing by hardware using an electronic circuit) will be described as the matrix calculation method. However, as in the embodiments described later, numerical data processing (program It is also possible to be based on processing by software using. Moreover, when implementing, it is also possible to combine these.

  FIG. 8 shows a circuit diagram of the matrix calculation unit 436. The RGB signals are input to the amplifiers 32a to 32c through the resistor groups 31a to 31c, respectively. Each resistor group has a plurality of resistors to which RGB signals are respectively connected, and the resistance value of each resistor is a value corresponding to the matrix coefficient. In other words, the gain of the RGB signal is changed by each resistor, and the amplifiers add (or subtract). The outputs of the amplifiers 32a to 32c are the outputs of the matrix operation unit 436. That is, the matrix calculation unit 436 performs so-called weighted addition processing. Note that the resistance value of each resistor used here may be variable.

  The outputs of the matrix calculation unit 436 are connected to the integration units 438a to 438c, respectively, and after integration is performed, the respective spectral image signals ΣF1 to ΣF3 are sent to the color adjustment unit 440 and the biological function calculation unit 450. The color adjustment unit 440 performs a color adjustment calculation described later on the spectral image signals ΣF1 to ΣF3, generates color channels Rch, Gch, and Bch and sends them to the switching unit 439. In addition, the biological function calculation unit 450 calculates a value (hemoglobin index; IHb) correlated with the hemoglobin concentration in blood as an index representing the biological function based on the spectral image signals ΣF1 to ΣF3, and from the calculated IHb value Biological function information such as a pseudo image (pseudo color image or gray scale image) is generated and sent to the switching unit 439. The configuration of the color adjustment unit 440 and the biological function calculation unit 450 will be described later.

  The switching unit 439 performs display switching between a normal image, a spectral image, and a biological function image (biological function information), and can also switch and display spectral images. That is, the operator can selectively display from a normal image, a spectral channel image by Rch, a spectral channel image by Gch, a spectral channel image by Bch, and a biological function image. Further, any two or more images may be displayed on the display monitor 106 at the same time.

  In particular, when the normal image, the spectral channel image, and the biological function image can be displayed simultaneously, the spectral channel image and the biological functional image can be easily compared with the normal image that is generally observed. Each characteristic of the normal image and the spectral channel image (the characteristic of the normal image is easy to observe because the color degree is close to that of the normal naked eye. The characteristic of the spectral channel image is to observe a predetermined blood vessel or the like that cannot be observed in the normal image. Can be observed in consideration of the above, and is very useful in diagnosis.

  Next, the operation of the electronic endoscope apparatus 100 according to the present embodiment will be described in detail with reference to FIG.

  In the following, the operation when observing a normal image will be described first, and the operation when observing a spectral image will be described later.

  First, the operation of the light source unit 41 will be described. Based on a control signal from the control unit 42, the chopper driving unit 17 is set to a predetermined position and rotates the chopper 16. The light flux from the lamp 15 passes through the notch portion of the chopper 16 and is incident on the light guide 14 that is an optical fiber bundle provided in the connector 11 at the connection portion of the scope 101 and the light source portion 41 by the condenser lens. At the end, it is condensed.

  The condensed light flux passes through the light guide 14 and is irradiated into the body of the subject from the illumination optical system provided at the distal end portion 103. The irradiated light beam is reflected in the subject, and signals are collected for each color filter shown in FIG.

  The collected signals are input in parallel to the luminance signal processing system and the color signal processing system. The luminance signal-based contour correction unit 432 adds the signals collected for each color filter for each pixel and inputs them. After contour correction, the signals are input to the luminance signal processing unit 434. In the luminance signal processing unit 434, a luminance signal is generated and input to the normal image generating unit 437.

  On the other hand, signals collected by the CCD 21 are input to the S / H circuits 433a to 433c for each filter, and R, G, and B signals are respectively generated. Further, R, G, and B signals are generated by a color signal processing unit 435, and a normal image generation unit 437 generates a Y signal, an RY signal, and a BY signal from the luminance signal and the color signal. Then, the normal image of the subject is displayed on the display monitor 106 via the switching unit 439.

  Next, the operation when observing a spectral image will be described. In addition, what performs the same operation | movement as observation of a normal image is abbreviate | omitted here.

  The operator gives an instruction to observe the spectral image from the normal image by operating a keyboard or the like provided on the main body 105 or a switch or the like provided on the operation unit 104 of the scope 101. At this time, the control unit 42 changes the control state of the light source unit 41 and the main body processing device 43.

  Specifically, the amount of light emitted from the light source unit 41 is changed as necessary. As described above, since it is not desirable that the output from the CCD 21 is saturated, the amount of illumination light is reduced as compared with a normal image. Further, it is possible to control the output signal from the CCD not to be saturated, and to change the amount of illumination light within a range where the output signal is not saturated.

  Further, as a control change to the main body processing device 43, the signal output from the switching unit 439 is switched to the signal output from the normal image generation unit 437 to the integration units 438a to 438c. The outputs of the S / H circuits 433a to 433c are amplified and added by the matrix calculation unit 436, and output to the integration units 438a to 438c according to the respective bands. Even when the amount of illumination light is reduced by the chopper 16, the signal intensity can be increased and the S / N can be improved as shown in FIG. 2 by storing and integrating in the integrating units 438 a to 438 c. Spectral images can be obtained.

  Hereinafter, specific matrix processing of the matrix calculation unit 436 in the present embodiment will be described. In this embodiment, from the spectral sensitivity characteristics of RGB indicated by the solid line in FIG. 7, ideal narrow bandpass filters F1 to F3 (here, each transmission wavelength region is expressed as F1: 590 nm). ~ 620nm, F2: 520nm to 560nm, F3: 400nm to 440nm) when trying to create a bandpass filter (hereinafter referred to as a pseudo bandpass filter), from the above formula (1) to (5) Depending on what is shown, the following matrix is optimal.

更に、（６）式及び（７）式に示した内容により補正を行うと、以下の補正係数を得る。 [Equation 19]

Further, when correction is performed according to the contents shown in the equations (6) and (7), the following correction coefficients are obtained.

尚、（６）式に示す光源のスペクトルＳ（λ）は図９に、（７）式に示す注目する生体の反射スペクトルＨ（λ）は図１０に示すものとの先見情報を使用している。 [Equation 20]

Note that the spectrum S (λ) of the light source shown in the equation (6) is shown in FIG. 9, and the reflection spectrum H (λ) of the target organism shown in the equation (7) is used in the foresight information shown in FIG. Yes.

  Therefore, the processing performed by the matrix calculation unit 436 is mathematically equivalent to the following matrix calculation.

このマトリックス演算を行うことにより擬似フィルタ特性（図７にはフィルタ擬似Ｆ1乃至Ｆ3の特性として示されている）が得られる。即ち、上述のマトリックス処理は、カラー画像信号に、上述のようにして予め生成された擬似バンドパスフィルタ（マトリックス）を用いて、分光画像信号を作成するものである。 [Equation 21]

By performing this matrix operation, pseudo filter characteristics (shown as characteristics of filter pseudo F1 to F3 in FIG. 7) are obtained. That is, the matrix processing described above creates a spectral image signal using a pseudo bandpass filter (matrix) generated in advance as described above for a color image signal.

  An example of an endoscopic image generated using this pseudo filter characteristic is shown below.

  As shown in FIG. 11, the body cavity tissue 51 often has an absorber distribution structure such as blood vessels that differ in the depth direction. A large number of capillaries 52 are mainly distributed near the surface of the mucosa, and blood vessels 53 that are thicker than capillaries are distributed in the middle layer deeper than this layer, and thicker blood vessels 54 are further distributed in the deep layers. become.

  On the other hand, the depth of light in the depth direction with respect to the body cavity tissue 51 depends on the wavelength of the light, and the illumination light including the visible range is blue (B) as shown in FIG. In the case of light with such a short wavelength, the light reaches the surface layer only due to the absorption and scattering characteristics in the living tissue, and the light emitted from the surface is observed by being absorbed and scattered in the depth range up to that. Is done. In the case of green (G) light, which has a wavelength longer than that of blue (B) light, it reaches deeper than the range where blue (B) light deepens, absorbs and scatters within that range, and exits from the surface. Light is observed. Still further, red (R) light having a wavelength longer than that of green (G) light reaches a deeper range.

Since the RGB light during normal observation of the tissue 51 in the body cavity is overlapped with each other as shown in FIG.
(1) Band images having shallow layer and middle layer tissue information including a lot of tissue information in the shallow layer as shown in FIG.
(2) In addition, the image signal picked up by the CCD 21 with the G-band light is picked up with a shallow layer image including a lot of tissue information in the middle layer and a band image having the middle layer tissue information as shown in FIG.
(3) Further, a band image having middle layer and deep layer tissue information including a lot of tissue information in the deep layer as shown in FIG.

  Then, the endoscope apparatus body 105 performs signal processing on these RGB imaging signals, so that it is possible to obtain an endoscopic image having a desired or natural color reproduction as an endoscopic image.

The matrix processing in the matrix calculation unit 436 is to create a spectral image signal by using the pseudo bandpass filter (matrix) generated in advance as described above for the color image signal. For example, spectral image signals F1 to F3 are obtained using pseudo bandpass filters F1 to F3 having discrete and narrow-band spectral characteristics capable of extracting desired deep tissue information as shown in FIG. As shown in FIG. 17, the pseudo bandpass filters F1 to F3 are not overlapped with each other.
(4) A band image having tissue information in a shallow layer as shown in FIG. 18 is captured in the spectral image signal F3 by the pseudo bandpass filter F3,
(5) A band image having tissue information in the middle layer as shown in FIG. 19 is captured in the spectral image signal F2 by the pseudo bandpass filter F2, and (6) the spectral image signal F1 by the pseudo bandpass filter F1 A band image having tissue information in the deep layer as shown in FIG. 20 is captured.

  Next, for the spectral image signals F1 to F3 obtained in this way, the color adjustment unit 440, as an example of the simplest color conversion, uses the spectral image signal F1 as a color channel Rch and the spectral image signal F2 as a color. The spectral image signal F3 is allocated to the channel Gch to the color channel Bch, and is output to the display monitor 106 via the switching unit 439.

  As shown in FIG. 21, the color adjustment unit 440 has three sets of LUTs 62a, 62b, 62c, 63a, 63b, and 63c and LUTs 62a, 62b, 62c, and 63a on both sides of the 3 × 3 matrix circuit 61. , 63b, 63c and a coefficient changing circuit 64 for converting the coefficients of the 3 × 3 matrix circuit 61 to constitute a color conversion processing circuit 440a.

  The spectral image signals F1 to F3 input to the color conversion processing circuit 440a are converted by the LUTs 62a, 62b, and 62c for each band data. Here, inverse γ correction, nonlinear contrast conversion, and the like are performed.

  Next, after color conversion is performed in the 3 × 3 matrix circuit 61, γ correction and appropriate gradation conversion processing are performed in the subsequent LUTs 63a, 63b, and 63c.

  The LUTs 62a, 62b, 62c, 63a, 63b, and 63c can be changed by the coefficient changing circuit 64 that converts the table data and the coefficients of the 3 × 3 matrix circuit 61.

  The change by the coefficient changing circuit 64 is based on a control signal from a processing conversion switch (not shown) provided in the operation unit or the like of the scope 101.

  Upon receiving these control signals, the coefficient changing circuit 63 calls appropriate data from the coefficient data previously written in the color adjustment unit 440, and rewrites the current circuit coefficient with this data.

  Next, specific color conversion processing contents will be described. An example of the color conversion formula is shown in Formula (22).

この式（２２）による処理は、分光チャンネル画像Ｒch、Ｇch、Ｂchに分光画像信号Ｆ1乃至Ｆ3を波長の短い順に割り当てる色変換である。 [Equation 22]

The processing according to the equation (22) is color conversion in which the spectral image signals F1 to F3 are assigned to the spectral channel images Rch, Gch, and Bch in order of decreasing wavelength.

  When observed with color images of these color channels Rch, Gch, and Bch, for example, an image as shown in FIG. 22 is obtained. A thick blood vessel is in a deep position, the spectral image signal F3 is reflected, and the color is shown as a blue pattern. Since the spectral image signal F2 is strongly reflected in the vascular network near the middle layer, the color image is shown as a red pattern. Those existing in the vicinity of the mucosal surface in the vascular network are expressed as a yellowish pattern.

  The color conversion processing circuit 440a performs color conversion using a matrix calculator composed of a 3 × 3 matrix circuit 61. However, the present invention is not limited to this, and a color conversion processing means may be configured by a numerical operation processor (CPU) or LUT. .

  For example, in the above embodiment, the color conversion processing circuit 440a is shown with a configuration centered on the 3 × 3 matrix circuit 61. However, as shown in FIG. 23, the color conversion processing circuit 440a is replaced with a three-dimensional LUT 71 corresponding to each band. The same effect can be obtained by replacing with. In this case, the coefficient changing circuit 64 performs an operation of changing the contents of the table based on a control signal from a processing conversion switch (not shown) provided in the operation unit or the like of the scope 101.

  On the other hand, an operator operates a biological function calculation by operating a keyboard provided on the main body 105 or a switch provided on the operation unit 104 of the scope 101 with respect to an observation image using the color channels Rch, Gch, and Bch. When the calculation instruction is given to the unit 450, the IHb value is calculated by the IHb value calculation circuit 450a shown in FIG. 24 using the two band image information of the spectral image signals F1 to F3.

  In the conventional IHb value calculation, equation (23) is used, and this equation utilizes the fact that the G band image strongly reflects blood information. On the other hand, when the band of the filter is narrowed, capillaries on the surface are strongly reflected in the B image. Therefore, the images of B and G have different depths at which blood exists, and B reflects information on the surface layer and G has a deeper layer position.

[Equation 23]
IHb = 32 × Log ₂ (R / G) (23)
Therefore, the biological function calculation unit 450 treats the spectral image signal F1 corresponding to the R band as the R signal, the spectral image signal F2 corresponding to the G band as the G signal, and the spectral image signal F3 corresponding to the B band as the B signal, By switching the operation of the selector 451 provided in the IHb calculation circuit 450a by an instruction from an operation switch or the like, the IHb value of the mucosal middle layer based on the G information according to the equation (23) and the B information according to the equation (24) are used. Calculation is performed by switching the mucosal surface IHb value. Thereby, it is possible to separate and confirm tissue information of a desired deep portion near the tissue surface of the living tissue.

[Equation 24]
IHb = 32 × Log ₂ (R / B) (24)
Specifically, as shown in FIG. 24, the IHb calculation circuit 450a includes a selector 451, a divider 452, a logarithmic converter 453, and a multiplier 454, and a spectral image signal F1 as an R signal, The spectral image signal F2 as the G signal selected by the selector 451 or the spectral image signal F3 as the B signal is input to the divider 452, and R / G or R / B is calculated. The output of the divider 452 is input to the Log conversion unit 453, and logarithmic conversion is performed using a conversion table on the ROM. The logarithmically converted signal is multiplied by a predetermined coefficient in a multiplier 454, and an IHb value for each pixel is calculated.

  Then, a pseudo color image or the like is generated based on the calculated IHb value for each pixel, and is output to the display monitor 106 via the switching unit 439. For example, as shown in FIG. 25, the display monitor 106 displays a normal color image 106A on the left side of the screen, an observation image 106C based on a spectral channel image on the right side, and an IHb value below the observation image 106B. By displaying the biological function image based on 106C, a normal image, an observation image that has been color-converted into a color suitable for observing tissue information at a desired depth, and a biological function based on the IHb value of the tissue corresponding to the observation image Information can be displayed at the same time, and the diagnostic ability can be improved.

  For example, the spectral image signal F2 is assigned to the color channel Gch by the color conversion processing according to the equation (22), and the blood vessel network near the middle layer is displayed in the observation image of the red pattern, and at the same time, the G based on the spectral image signals F1, F2 is displayed. By calculating the IHb value of the mucosal middle layer based on the information and displaying the biological function image, it is possible to easily grasp the change in hemodynamics due to the hemoglobin distribution.

  At this time, the vascular network existing in the vicinity of the mucosal surface is expressed as a yellow pattern in the observation image, but the yellow pattern tends to have low contrast with the background mucosa and low visibility. Changes in the pattern near the mucosal surface are particularly important for early differential detection and diagnosis.

  Therefore, in order to more clearly reproduce the pattern near the mucosal surface in the observed image, the conversion shown in the following equation (25) is performed, while the IHb value of the mucosal surface layer based on the B information by the spectral image signals F1 and F3. It is effective to calculate and display a biological function image.

この式（２５）による処理は、分光画像信号Ｆ1をある一定の比率で分光画像信号Ｆ2に混合し生成されたデータを新たに分光Ｇチャンネル画像Ｇchとする変換例であり、血管網などの吸収散乱体が深さ位置で異なることをより明確化することが可能となる。 [Equation 25]

The processing according to the equation (25) is a conversion example in which the spectral image signal F1 is mixed with the spectral image signal F2 at a certain ratio and the generated data is newly used as the spectral G channel image Gch. It becomes possible to further clarify that the scatterers are different in depth positions.

  Accordingly, by adjusting the matrix coefficient through the coefficient changing circuit 64, the user can adjust the display effect. As the operation, the matrix coefficient is set to the default value from the through operation in the image processing means in conjunction with a mode change switch (not shown) provided in the operation unit of the scope 101.

The through operation here refers to a state in which the 3 × 3 matrix circuit 61 is mounted with a unit matrix, and the LUTs 62a, 62b, 62c, 63a, 63b, and 63c are mounted with non-conversion tables. For the default value, for example, set values of ω _G = 0.2 and ω _B = 0.8 are given to the matrix coefficients.

Then, the user operates the operation unit or the like of the scope 101 to adjust the coefficient so that ω _G = 0.4, ω _B = 0.6, and the like. A reverse γ correction table and a γ correction table are applied to the LUTs 62a, 62b, 62c, 63a, 63b, and 63c as necessary.

  In addition to the IHb calculation circuit 450a, the biological function calculation unit 450 is provided with a calculation unit that calculates feature values such as the average value of IHb, the standard deviation of IHb, and the kurtosis of IHb in the entire image. You may make it display on the screen of the display monitor 106 with the biofunction image based on an IHb value.

  As described above, according to the present embodiment, a pseudo narrowband filter is generated by using a color image signal for generating a normal electronic endoscopic image (normal image). A spectral image having tissue information of a desired deep portion such as a blood vessel pattern can be obtained without using an optical wavelength narrow-band bandpass filter, and the parameters of the color conversion processing circuit 440a of the color adjustment unit 440 are converted into spectral images. By setting it accordingly, it becomes possible to realize an expression method that makes use of the feature of depth-of-depth information when observing a narrow-band spectral image, and it is possible to effectively obtain tissue information of a desired deep part near the tissue surface of a living tissue. It can be visually recognized separately.

  Moreover, on the same display monitor, in addition to a normal color image, an observation image having a color tone suitable for observation and biological function information such as a pseudo image based on the IHb value are displayed at the same time. Can be easily grasped, and it is not necessary to frequently switch various images as in the prior art, and each image can be easily compared and contrasted, thereby improving the diagnostic ability.

  FIG. 26 is a block diagram illustrating a configuration of a matrix calculation unit according to the second embodiment of the present invention. Since the second embodiment is almost the same as the first embodiment, only different points will be described.

  In the present embodiment, the matrix calculation unit 436 is mainly different from the first embodiment. In the first embodiment, the matrix operation is performed by so-called hardware processing using an electronic circuit. In this embodiment, this operation is performed by numerical data processing (processing by software using a program).

  A specific configuration of the matrix calculation unit 436 in this embodiment is shown in FIG. The matrix calculation unit 436 includes an image memory 50 that stores RGB color image signals. Further, it has a counting register 51 in which each value of the matrix “A ′” shown in Expression (21) is stored as numerical data.

  The counting register 51 and the image memory 50 are connected to the multipliers 53a to 53i, the multipliers 53a, 53d, and 53g are connected to the multiplier 54a, and the output of the multiplier 54a is connected to the integrating unit 438a in FIG. Is done. The multipliers 53b, 53e, and 53h are connected to the multiplier 54b, and the output thereof is connected to the integrating unit 438b. The multipliers 53c, 53f, and 53i are connected to the multiplier 54c, and the output thereof is connected to the integrating unit 438c.

  As an operation of this embodiment, the input RGB image data is once stored in the image memory 50. Next, each count of the matrix “A ′” from the count register 51 is multiplied by the multiplier and the RGB image data stored in the image memory 50 by a calculation program stored in a predetermined storage device (not shown). The

  FIG. 26 shows an example in which the R signal and each matrix count are multiplied by multipliers 53a to 53c. Also, as shown in the figure, the G signal and each matrix count are multiplied by multipliers 53d to 53f, and the B signal and each matrix count are multiplied by multipliers 53g to 53i. The data multiplied by the matrix count is obtained by multiplying the outputs of the multipliers 53a, 53d and 53g by the multiplier 54a, the outputs of the multipliers 53b, 53e and 53h by the multiplier 54b, and the multipliers 53c, 53f, The outputs of 53i are respectively multiplied by the multiplier 54c. The output of the multiplier 54a is sent to the integrating unit 438a. The outputs of the multiplier 54b and the multiplier 54c are sent to the integrating units 438b and 438c, respectively.

  According to the present embodiment, as in the first embodiment, it is possible to obtain a spectral observation image in which a blood vessel pattern is clearly displayed and to display biological function information related to the spectral observation image.

  Further, in the present embodiment, the matrix processing is not performed by hardware as in the first embodiment, but is performed by using software, and therefore, for example, it is possible to quickly cope with a change in each matrix count.

  In addition, the matrix count is stored not only as a result value, that is, as a matrix “A ′”, but separately as S (λ), H (λ), R (λ), G (λ), and B (λ). When the matrix “A ′” is obtained and used by performing calculations as necessary, only one of the elements can be changed, and convenience is improved. For example, it is possible to change only the spectral characteristic S (λ) of the illumination light.

  27 and 28 relate to the third embodiment of the present invention, FIG. 27 is a block diagram showing the configuration of the electronic endoscope apparatus, and FIG. 28 is a diagram showing the charge accumulation time of the CCD of FIG.

  Since the third embodiment is almost the same as the first embodiment, only different points will be described, and the same components are denoted by the same reference numerals and description thereof will be omitted.

  In the present embodiment, the light source unit 41 and the CCD 21 are mainly different from the first embodiment. In the first embodiment, the color filter shown in FIG. 6 is provided in the CCD 21 and a color signal is generated by this color filter. In contrast, in this embodiment, the illumination light is illuminated in the order of RGB. Thus, a so-called frame sequential method for generating a color signal is used.

  As shown in FIG. 27, in the light source unit 41 in this embodiment, a diaphragm 25 is provided in front of the lamp 15, and an RGB filter 23 is provided in front of the diaphragm 25. In addition, the diaphragm 25 is connected to the diaphragm control unit 24, and restricts the light beam to be transmitted among the light beams emitted from the lamp 15 in accordance with a control signal from the diaphragm control unit 24, thereby changing the light amount. The RGB rotation filter 23 is connected to the RGB rotation filter control unit 26 and rotates at a predetermined rotation speed.

  As the operation of the light source unit in this embodiment, the luminous flux output from the lamp 15 is limited to a predetermined light amount by the diaphragm 25, and the luminous flux transmitted through the diaphragm 25 passes through the RGB filter every predetermined time. It is output from the light source unit as illumination lights of R, G, and B. Each illumination light is reflected in the subject and received by the CCD 21. Signals obtained by the CCD 21 are distributed by a switching unit (not shown) provided in the endoscope apparatus main body 105 according to the irradiation time, and input to the S / H circuits 433a to 433c, respectively. That is, when the illumination light is irradiated from the light source unit 41 through the R filter, the signal obtained by the CCD 21 is input to the S / H circuit 433a. Since other operations are the same as those in the first embodiment, they are omitted here.

  According to the present embodiment, as in the first embodiment, it is possible to obtain a spectral observation image in which a blood vessel pattern is clearly displayed and to display biological function information related to the spectral observation image. Further, in this embodiment, unlike the first embodiment, it is possible to enjoy the merits of the so-called frame sequential method. This merit includes, for example, the same as in Example 4 described later.

  In the above-described embodiment, the illumination light amount (light amount from the light source unit) is controlled and adjusted in order to avoid saturation of the RGB color signal. On the other hand, there is a method of adjusting the electronic shutter of the CCD. In the CCD, a charge proportional to the intensity of light incident within a predetermined time is accumulated, and the amount of the charge is used as a signal. The accumulation time corresponds to what is called an electronic shutter. By adjusting this electronic shutter, it is possible to adjust the charge accumulation amount, that is, the signal amount, so as shown in FIG. 28, by obtaining an RGB color image with the charge accumulation time sequentially changed, Similar spectral images can be obtained. That is, in each of the above-described embodiments, the illumination light amount control is used to obtain a normal image, and when obtaining a spectral image, it is possible to avoid saturation of RGB color signals by changing the electronic shutter. is there.

  FIG. 29 is a diagram showing the charge accumulation time of the CCD according to Example 4 of the present invention.

  Since the fourth embodiment is almost the same as the third embodiment, only different points will be described, and the same components are denoted by the same reference numerals and description thereof will be omitted.

  This embodiment mainly uses the frame sequential method as in the third embodiment, and takes advantage of this advantage. By adding a weight to the charge accumulation time by electronic shutter control in the third embodiment, the generation of spectral image data can be simplified. That is, in this embodiment, the CCD drive 431 that can change the charge accumulation time of the CCD 21 is provided. Other configurations are the same as those in the third embodiment, and are omitted here.

As an operation of this embodiment, as shown in FIG. 29, when each illumination light is irradiated through the RGB rotation filter 23, the charge accumulation time by the electronic shutter in the CCD 21 is changed. Here, tdr, tdg, and tdb are the charge accumulation times of the CCD 21 when the illumination light is R, G, and B (in this figure, since the B color image signal has no accumulation time, tdb is omitted. And). For example, the F3 pseudo filter image in the case of performing the matrix processing represented by the equation (21) is obtained from an RGB image obtained by a normal endoscope,
[Equation 26]
F3 = −0.050R−1.777G + 0.829B (26)
Therefore, the charge accumulation time by RGB electronic shutter control in FIG.
tdr: tdg: tdb = 0.050: 1.777: 0.829 (27)
It should be set so that. In the matrix portion, the signal obtained by simply inverting only the R and G components and the B component are added. Thereby, the same spectral image as Example 1 thru | or Example 3 can be obtained.

  According to the present embodiment, as in the third embodiment, it is possible to obtain a spectral observation image in which a blood vessel pattern is clearly displayed and to display biological function information related to the spectral observation image. Further, in the present embodiment, as in the third embodiment, a frame sequential method is used to create a color signal, and further, an electronic shutter can be used to change the charge accumulation time for each color signal. Thus, in the matrix portion, it is only necessary to perform addition and difference processing, and the processing can be simplified.

  30 and 31 relate to the fifth embodiment of the present invention, FIG. 30 is a diagram showing an arrangement of color filters, and FIG. 31 is a diagram showing spectral sensitivity characteristics of the color filters in FIG.

  Since the fifth embodiment is almost the same as the first embodiment, only different points will be described, and the same components are denoted by the same reference numerals and description thereof will be omitted.

  In the present embodiment, the color filter provided in the CCD 21 is mainly different from that in the first embodiment. In the first embodiment, an RGB primary color filter is used as shown in FIG. 6, whereas in the present embodiment, a complementary color filter is used.

  As shown in FIG. 30, this complementary color filter array is composed of G, Mg, Ye, and Cy elements. The relationship between each element of the primary color filter and each element of the complementary color filter is Mg = R + B, Cy = G + B, Ye = R + G.

  In this case, all the pixels of the CCD 21 are read out, and the image from each color filter is subjected to signal processing or image processing. Further, when the equations (1) to (8) and (19) to (21) for the primary color filter are modified in the case of a complementary color filter, the following equation (34) is obtained from the following equation (28): become that way. However, the characteristics of the target narrow-band bandpass filter are the same.

［数２９］

［数３０］
ｋG＝（∫Ｓ（λ）×Ｈ（λ）×Ｇ（λ）ｄλ）^-1
ｋMg＝（∫Ｓ（λ）×Ｈ（λ）×Ｍｇ（λ）ｄλ）^-1
ｋCy＝（∫Ｓ（λ）×Ｈ（λ）×Ｃｙ（λ）ｄλ）^-1
ｋYe＝（∫Ｓ（λ）×Ｈ（λ）×Ｙｅ（λ）ｄλ）^-1 …（３０）
［数３１］

［数３２］

［数３３］

［数３４］

また、図３１に、補色型カラーフィルタを用いた場合の分光感度特性、目標とするバンドパスフィルタ及び上記（２８）式乃至（３４）式により求められ擬似バンドパスフィルタの特性を示す。 [Equation 28]

[Equation 29]

[Equation 30]
kG = (∫S (λ) × H (λ) × G (λ) dλ) ⁻¹
kmg = (∫S (λ) × H (λ) × Mg (λ) dλ) ⁻¹
kCy = (∫S (λ) × H (λ) × Cy (λ) dλ) ⁻¹
kYe = (∫S (λ) × H (λ) × Ye (λ) dλ) ⁻¹ (30)
[Equation 31]

[Formula 32]

[Equation 33]

[Formula 34]

FIG. 31 shows the spectral sensitivity characteristics when the complementary color filter is used, the target bandpass filter, and the characteristics of the pseudo bandpass filter obtained by the above equations (28) to (34).

  When the complementary color filter is used, it goes without saying that the S / H circuit shown in FIG. 4 is performed for G, Mg, Cy, and Ye instead of R, G, and B, respectively.

  Further, even when a complementary color filter is used, the matrix estimation method shown in the equations (9) to (18) can be applied. In this case, when the number of the complementary color filters is four, the biological spectral reflectance assumed in the equation (14) can be approximated by three basic spectral characteristics, or four or less. Become. Accordingly, in accordance with this, the dimension for calculating the estimation matrix is changed from 3 to 4.

  According to the present embodiment, as in the first embodiment, it is possible to obtain a spectral observation image in which a blood vessel pattern is clearly displayed and to display biological function information related to the spectral observation image. Further, in this embodiment, it is possible to enjoy the advantages of using a complementary color filter.

  The embodiments of the present invention have been described above. However, the present invention may be used by combining various embodiments described above, and modifications may be made without departing from the spirit of the present invention.

  For example, for all the embodiments described above, a new pseudo band-pass filter can be created by the operator himself / herself at other timings in the clinic and applied to the clinic. That is, in the first embodiment, a design unit (not shown) capable of calculating and calculating matrix coefficients is provided in the control unit 42 in FIG.

  Thereby, by inputting conditions via the keyboard provided in the endoscope main body shown in FIG. 3, a pseudo bandpass filter suitable for obtaining a spectral image that the operator wants to know is newly designed, Correction coefficient (corresponding to each element of the matrix “K” in the expressions (20) and (33)) to the calculated matrix coefficient (corresponding to each element of the matrix “A” in the expressions (19) and (32)) By setting the final matrix coefficient (corresponding to each element of the matrix “A ′” in the equations (21) and (34)) in the matrix calculation unit 436 in FIG. it can.

  FIG. 32 shows a flow until application. This flow will be described in detail. First, the operator inputs information about a target bandpass filter (for example, a wavelength band) via a keyboard or the like. As a result, the matrix “A ′” is calculated together with the characteristics of the light source / color filter already stored in a predetermined storage device or the like, and as shown in FIG. 30, along with the characteristics of the target bandpass filter, The calculation result (pseudo bandpass filter) by the matrix “A ′” is displayed on the monitor as a spectrum diagram.

  After confirming the calculation result, the operator performs setting when using the newly created matrix “A ′”, and generates an actual endoscopic image using this matrix “A ′”. Is done. In addition, the newly created matrix “A ′” is stored in a predetermined storage device and can be used again according to a predetermined operation by the operator.

  As a result, the operator can generate a new band-pass filter based on his / her own experience etc. without being bound by the existing matrix “A ′”, and is particularly effective when used for research purposes. .

  The present invention is not limited to the above-described embodiments, and various changes and modifications can be made without departing from the scope of the present invention.

FIG. 3 is a conceptual diagram showing a signal flow when creating a spectral image signal from a color image signal according to Embodiment 1 of the present invention. FIG. 3 is a conceptual diagram showing integration calculation of spectral image signals according to Embodiment 1 of the present invention. 1 is an external view showing an external appearance of an electronic endoscope apparatus according to Embodiment 1 of the present invention. The block diagram which shows the structure of the electronic endoscope apparatus of FIG. External view showing the external appearance of the chopper of FIG. The figure which shows the arrangement | sequence of the color filter arrange | positioned at the imaging surface of CCD of FIG. The figure which shows the spectral sensitivity characteristic of the color filter of FIG. The block diagram which shows the structure of the matrix calculating part of FIG. The spectrum figure which shows the spectrum of the light source which concerns on Example 1 of this invention The spectrum figure which shows the reflection spectrum of the living body concerning Example 1 of the present invention, FIG. 11 is a diagram showing a layer direction structure of a biological tissue observed by the electronic endoscope apparatus of FIG. The figure explaining the arrival state to the layer direction of the biological tissue of the illumination light from the electronic endoscope apparatus of FIG. Diagram showing spectral characteristics of each band of white light The 1st figure which shows each band image by the white light of FIG. 2nd figure which shows each band image by the white light of FIG. 3rd figure which shows each band image by the white light of FIG. The figure which shows the spectral characteristic of the spectral image produced | generated by the matrix calculating part of FIG. The 1st figure which shows each spectral image of FIG. The 2nd figure which shows each spectral image of FIG. The 3rd figure which shows each spectral image of FIG. FIG. 21 is a block diagram showing the configuration of the color adjustment unit in FIG. The figure explaining the effect | action of the color adjustment part of FIG. FIG. 4 is a block diagram showing a modification of the color adjustment unit in FIG. The block diagram which shows the structure of the biological function calculating part of FIG. Figure showing a display example on the monitor FIG. 5 is a block diagram showing a configuration of a matrix calculation unit according to the second embodiment of the present invention. Block diagram showing the configuration of an electronic endoscope apparatus according to Embodiment 3 of the present invention The figure which shows the charge accumulation time of CCD of FIG. The figure which shows the charge accumulation time of CCD which concerns on Example 4 of this invention. The figure which shows the arrangement | sequence of the color filter which concerns on Example 5 of this invention. The figure which shows the spectral sensitivity characteristic of the color filter of FIG. Flowchart at the time of matrix calculation in a modification according to the present invention

Explanation of symbols

DESCRIPTION OF SYMBOLS 41 ... Light source part 42 ... Control part 43 ... Main body processing apparatus 100 ... Electronic endoscope apparatus 101 ... Scope 102 ... Insertion part 103 ... Tip part 104 ... Angle operation part 105 ... Endoscope apparatus main body 106 ... Display monitor 436 ... Matrix Calculation unit 440 ... Color adjustment unit 440a ... Color conversion processing circuit 450 ... Biological function calculation unit 450a ... IHb calculation circuit

Claims (5)

Illumination means for irradiating the subject with light;
An observation means for acquiring a biological signal;
In an observation apparatus comprising: signal processing control means for controlling the operation of the illumination means and / or the observation means, and displaying and outputting the biological signal to a display output device,
The signal processing control means includes
Spectral signal generating means for generating a spectral signal from the biological signal;
A biological function calculating means for calculating a biological function from the spectral signal and outputting the biological function to the display output device. The living body observation apparatus according to claim 1, further comprising color adjustment means for adjusting a color tone when the spectral signal is displayed and output to the display output apparatus. The living body observation apparatus according to claim 1, wherein the living body function is a hemoglobin index. The living body observation apparatus according to claim 3, wherein the calculation of the hemoglobin index includes a logarithm of a ratio of a spectral signal in a red band and a spectral signal in a green band. The living body observation apparatus according to claim 3, wherein the calculation of the hemoglobin index includes a logarithm of a ratio between a red band spectral signal and a blue band spectral signal.

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