JP2012168085A - Method for detecting specific microbial components - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method for detecting specific microbial components capable of stably detecting specific microorganisms or viruses in a sample with high detection accuracy.SOLUTION: A digital image at a first excitation time and a digital image at a second excitation time are obtained by irradiating a sample with a first excitation light and a second excitation light respectively and photographing a surface of the sample at the respective times (S1-S4). Color space data obtained for each pixel unit in the digital image at the first excitation time and the digital image at the second excitation time is respectively and separately collated with a predetermined specified range to obtain binarized data for each pixel unit in the digital image at the first excitation time and the digital image at the second excitation time (S5-S8). The presence of a specific fluorescent reaction in the sample is detected based on calculation processing data for each pixel unit obtained by collation calculation between the respective pixels that are at the same location in the binarized data for each pixel unit in a plurality of kinds of digital images D1, D2 at excitation times (S9-S13).

Description

  The present invention relates to a method for detecting a specific biological component for detecting a specific microorganism or virus in a sample.

  In the test for insects (eggs) carried out at schools and the like, for example, a test sample obtained by a subject applying cellophane to the anus is inspected at an inspection institution or medical institution. In this inspection, it is necessary to visually check with a microscope whether or not there is a caterpillar egg adhering to the cellophane. Therefore, the inspector requires skill, and it cannot be said that the inspection accuracy and the inspection efficiency are so excellent. For example, Patent Document 1 discloses an insect egg automatic inspection facility for observing an insect test paper with a microscope.

  On the other hand, for example, in the foreign substance detection method of Patent Document 2, it is shown that when a parasite is excited by irradiation with visible light, the parasite fluoresces. And the presence or absence of the parasite which parasitizes meat is detected using this property. Patent Document 2 shows that a fluorescent image emitted from a subject is obtained by a digital camera, a CCD camera, or the like, image processing such as binarization is performed, and the presence / absence of a foreign object is determined by a computer. Yes.

Japanese Patent No. 3090492 JP 2007-286041 A

  However, in the conventional examination of caterpillar eggs, such as Patent Document 2, there is only one kind of excitation light, such as UV excitation, B excitation, and G excitation, used when exciting the insect eggs. Therefore, when trying to detect the presence or absence of a beetle egg using image processing by a computer, the detection accuracy is low, and a stable detection result cannot be obtained.

  The present invention has been made in view of such a problem, and an object of the present invention is to provide a specific biological component detection method capable of stably detecting a specific microorganism or virus in a sample with high detection accuracy. is there.

The present invention is a specific biological component detection method for detecting the specific microorganism or virus by detecting a specific fluorescence reaction generated when a specific microorganism or virus in a sample is excited,
A first excitation light irradiation step of irradiating the sample with the first excitation light at a specific wavelength, intensity, and irradiation time;
A first digital image obtaining step of photographing the surface of the sample irradiated with the first excitation light and obtaining a first excitation digital image;
A second excitation light irradiation step of irradiating the sample with a second excitation light that is different from the first excitation light in at least one of wavelength, intensity, and irradiation time;
A second digital image acquisition step of photographing the surface of the sample irradiated with the second excitation light and acquiring a second excitation digital image;
Color space data for each pixel unit is obtained for at least the first excitation digital image and the second excitation digital image, and the color for each pixel unit in the first excitation digital image and the second excitation digital image. Each of the spatial data is separately checked against a predetermined specified range, and when the color space data is within the predetermined specified range, 1 is set, and when the color space data is not within the predetermined specified range, 0 is set. An image processing step for obtaining binarized data for each pixel unit in the digital image and the second excitation digital image,
The identification in the sample based on the calculation processing data for each pixel unit obtained by collating the pixel units at the same position of the binary data of each pixel unit in the plurality of types of excitation digital images And a detection step of detecting a microorganism or virus in the sample by detecting a fluorescent reaction. (Claim 1)

In the specific biological component detection method of the present invention, the first irradiation step, the first digital image acquisition step, the second excitation light irradiation step, the second digital image acquisition step, and the image processing step, And at least the detection step.
In the first irradiation step, the sample is irradiated with the first excitation light at a specific wavelength, intensity, and irradiation time. At this time, when a component that is excited by the first excitation light and emits fluorescence exists in the sample, these exhibit a fluorescence reaction.

  Next, in the first digital image acquisition step, the surface of the sample irradiated with the first excitation light is photographed to acquire a first excitation digital image. That is, by photographing the surface of the sample with a digital camera or the like, for example, the fluorescence state emitted by the component contained in the sample can be acquired as a digital image. As a component that emits fluorescence, foreign substances such as dust (foreign substances that are not to be detected) are assumed in addition to microorganisms or viruses.

  On the other hand, in the second irradiation step, the sample is irradiated with second excitation light composed of excitation light that differs from the first excitation light in at least one of wavelength, intensity, and irradiation time. At this time, when a component that is excited by the second excitation light and emits fluorescence exists in the sample, these exhibit a fluorescence reaction. Since the second excitation light is different from the first excitation light in at least one of wavelength, intensity, and irradiation time, the sample generates fluorescence in a pattern different from that in the case of the first excitation light.

Next, in the second digital image acquisition step, the surface of the sample irradiated with the second excitation light is photographed to acquire a second excitation digital image. Similarly to the first digital image acquisition step, the fluorescence state emitted by the component contained in the sample can be acquired as a digital image. As a component that emits fluorescence, foreign substances such as dust (foreign substances that are not to be detected) are assumed in addition to microorganisms or viruses.
The first excitation-time digital image and the second excitation-time digital image show different fluorescence states because the excitation light is different.

Next, in the image processing step, color space data for each pixel unit is obtained for at least the first excitation digital image and the second excitation digital image. Then, the color space data for each pixel unit in the digital image at the time of the first excitation is separately checked against a predetermined specified range.
That is, for example, the color space data for each pixel unit in either the first excitation digital image or the second excitation digital image is checked against a predetermined specified range, and the other pixel unit in the other excitation digital image Each color space data can be collated with a predetermined specified range.
Here, the predetermined specified range is set by analyzing the color space data of a pixel showing a specific fluorescence reaction in a plurality of types of excitation digital images obtained for microorganisms or viruses.

The conditions of the excitation light (first excitation light and second excitation light) used at the time of detecting the specific fluorescence reaction are the same as the conditions of the excitation light used at the time of setting the reference for setting the specified range. For example, when a digital image at the time of excitation is taken with different wavelengths and intensities, the plurality of types of excitation light used at the time of detecting the specific fluorescence reaction are the plurality of types used at the time of setting the standard for setting the specified range. Same as the excitation light. Then, the color space data at the time of detection and the specified range of the color space data at the time of setting the reference are compared when the conditions of the excitation light are the same.
In the image processing step, for both the first excitation time digital image and the second excitation time digital image, the color space data is 1 within a predetermined specified range, and is not within the predetermined specified range. And binarized data for each pixel unit is obtained.

  Next, in the detection step, a collation operation is performed between pixel units at the same position in the binarized data of each pixel unit in the first excitation digital image and the second excitation digital image, and each pixel unit Find the operation data. And based on this arithmetic processing data, presence of the specific fluorescence reaction by the specific microorganism or virus in a sample can be detected, and a specific microorganism or virus can be detected.

By the way, in general, a sample contains foreign matters other than detection targets such as dust in addition to microorganisms or viruses, and the foreign matters also generate fluorescence by excitation light. However, the fluorescence properties of the specific fluorescence reaction that occurs when a microorganism or virus is excited and the fluorescence reaction that generates foreign matter such as dust differ depending on the wavelength, intensity, and irradiation time (imaging time) of the excitation light. .
Therefore, as in the present invention, at least two types of excitation light, i.e., the first excitation light and the second excitation light, are irradiated, and at least two types of excitation, the first excitation digital image and the second excitation digital image. When a digital image is taken, for example, a specific fluorescence reaction is photographed in any excitation digital image, while in any excitation digital image and another excitation digital image, it is photographed by the intensity of fluorescence. It is assumed that the way of doing is different. In this case, by performing the above collation operation, the fluorescence reaction caused by microorganisms or viruses can be clearly distinguished from the fluorescence reaction caused by foreign matters such as dust.
Further, at least two types of excitation light, the first excitation light and the second excitation light, were irradiated, and at least two types of excitation digital images, the first excitation digital image and the second excitation digital image, were taken. In this case, for example, it is assumed that fluorescence due to a foreign substance is photographed in all the digital images at the time of excitation, while the specific fluorescence reaction is clearly photographed in any one of the digital images at the time of excitation. In this case, by performing the above collation operation, it is possible to remove the influence of the fluorescent reaction due to the foreign matter, and to make the specific fluorescent reaction due to the microorganism or virus stand out and be detected. The fluorescence reaction caused by microorganisms or viruses can be clearly distinguished from the fluorescence reaction caused by foreign matters such as dust.

  Therefore, according to the specific biological component detection method of the present invention, microorganisms or viruses in the sample can be stably detected with high detection accuracy.

Explanatory drawing which shows the structure of the fluorescence reaction detection apparatus concerning an Example. Explanatory drawing which shows the digital image at the time of the 1st excitation concerning an Example schematically. Explanatory drawing which shows the digital image at the time of the 2nd excitation concerning an Example schematically. Explanatory drawing which visualizes the result of having performed collation calculation with respect to the digital image at the time of 1st excitation, and the digital image at the time of 2nd excitation concerning an Example, and shows schematically as a collation image. Explanatory drawing which visualizes the state which collates 1st color space data and 2nd color space data concerning the Example in the pixel unit for every dot. FIG. 3 is an explanatory diagram schematically illustrating a state in which a logical operation is performed on binarized data for each pixel unit of two types of excitation-time digital images according to the embodiment. Explanatory drawing which shows the hit area | region surrounding a hit pixel concerning an Example. Explanatory drawing which shows schematically the state which expanded and displayed on the monitor the pixel area | region corresponded to a hit area | region about the elementary digital image concerning an Example. The flowchart which shows the procedure which detects specific fluorescence reactions, such as microorganisms, concerning an Example.

Next, a preferred embodiment of the specific biological component detection method of the first and second inventions will be described.
In the specific biological component detection method, a specific microorganism or virus in the sample can be detected.
Examples of the microorganism include a parasite, a parasitic egg, and a bacterium. Examples of parasites include worms, roundworms, whipworms, flukes, worms, contracted tapeworms, broad-lined headworms, oriental hairy nematodes, and striped worms. Parasite eggs are those eggs.
Examples of bacteria include cocci, bacilli, and spiral bacteria.
In addition, as viruses, there are various viruses composed of nucleic acids and proteins.

  The sample can be stool, blood, or the like. The microorganism or virus may be present in stool, blood and the like. Parasites lurking in blood insects include, for example, Westermann lung fluke, Miyazaki lung fluke, schistospores, malaria pathogens, Japanese schistosomiasis, filamentous insects, filariae, and Guangdong schistosomes.

  Further, the first excitation light and the second excitation light are further irradiated to the sample by changing at least one of wavelength, intensity, and irradiation time, and the sample irradiated with the excitation light is irradiated. At least one excitation light irradiation-digital image acquisition process for capturing a surface and acquiring an excitation digital image is performed at least once. In the image processing process, the first excitation digital image and the second excitation digital image are used together. Preferably, the binarized data is obtained for at least one or more excitation digital images acquired in the excitation light irradiation-digital image acquisition step.

  As described above, by performing the excitation light irradiation-digital image acquisition step and performing the collation operation, the fluorescence reaction caused by microorganisms or viruses can be more clearly distinguished from the fluorescence reaction caused by foreign matters such as dust. That is, in this case, in order to obtain binarized data by individually collating a predetermined prescribed range with respect to three or more types of excitation digital images respectively obtained by irradiating three or more types of excitation light. The specific fluorescence reaction caused by the microorganisms or viruses can be detected more clearly.

Further, in the detection step, a case where the arithmetic processing data for each pixel unit is 1 is a hit pixel, and a shape and an area where the hit pixels are formed side by side are obtained in advance for the specific fluorescence reaction It is preferable to detect the presence of the specific microorganism or virus in the sample when the area is within the specified range (Claim 3).
In this case, in the above detection step, the microorganism or virus may be detected by confirming the shape and size of the specific fluorescence reaction for the sample in which the specific fluorescence reaction generated when the microorganism or virus is excited is detected. it can. Therefore, the detection accuracy of microorganisms or viruses can be improved.

In addition, a pixel region having a size surrounding the shape formed by the hit pixels detected side by side in the detection step is specified as a hit region, and the element when the excitation light is not irradiated is specified. It is preferable to perform a display step of acquiring a digital image and enlarging and displaying a pixel area corresponding to the hit area in the elementary digital image on a monitor.
In this case, by enlarging and displaying on the monitor the pixel area where the presence of the specific fluorescence reaction is detected, it is possible to visually confirm the area where the microorganism or virus is detected in the elementary digital image.

The color space data is at least one of red, green, and blue hues and luminance, and the collation operation in the detection step is the binary value for at least one of the hue and luminance. It is preferable that the logical operation is performed on the digitized data.
In this case, the arithmetic processing data for each image unit can be appropriately obtained in the image processing step.

Moreover, it is preferable that the wavelength of said 1st excitation light and said 2nd excitation light is a wavelength applicable to either of UV excitation, B excitation, or G excitation (Claim 6).
In this case, microorganisms or viruses can be excited appropriately.
Here, UV excitation (near ultraviolet rays) can be excitation light having a wavelength of 320 to 380 nm. The B excitation (blue light) can be excitation light having a wavelength of 380 to 495 nm. The G excitation (green light) can be excitation light having a wavelength of 495 to 570 nm.
In addition, also when performing the said excitation light irradiation-digital image acquisition process, it is preferable that the wavelength of excitation light is a wavelength corresponded in any one of UV excitation, B excitation, or G excitation, respectively.

In addition, it is preferable that at least one of the first excitation light and the second excitation light is composed of a plurality of types of excitation light in which at least one of wavelength and intensity is different.
That is, it is preferable to simultaneously irradiate a plurality of types of excitation light having different wavelengths and / or intensities as at least one of the first excitation light and the second excitation light.
In this case, as at least one of the first excitation time digital image and the second excitation time digital image, a digital image when a plurality of types of excitation light having different wavelengths and intensities are simultaneously irradiated. Can be obtained. In this case, there may be a case where it is possible to obtain a specific fluorescence reaction that cannot be obtained simply by irradiating a microorganism or virus with excitation light having one wavelength and intensity. In some cases, the detection accuracy of microorganisms or viruses can be significantly improved. For example, in the case of a caterpillar (egg), the detection accuracy can be particularly improved.

Example 1
Next, examples according to the specific biological component detection method of the present invention will be described.
In the specific biological component detection method of this example, the first excitation light irradiation step, the first excitation digital image acquisition step, the second excitation light irradiation step, the second excitation digital image acquisition step, the image processing step, and the detection step, To detect specific microorganisms or viruses in the sample.

  In the first excitation light irradiation step, the sample is irradiated with the first excitation light at a specific wavelength, intensity, and irradiation time. In the first excitation digital image acquisition step, the surface of the sample irradiated with the first excitation light is photographed to acquire a first excitation digital image.

  In the second excitation light irradiation step, the sample is irradiated with second excitation light that differs from the first excitation light in at least one of wavelength, intensity, and irradiation time. In the second excitation digital image acquisition step, the surface of the sample irradiated with the second excitation light is photographed to acquire a second excitation digital image.

  In the image processing step, color space data for each pixel unit is obtained for at least the first excitation digital image and the second excitation digital image, and the first excitation digital image and the second excitation digital image are obtained. The color space data for each pixel unit in the digital image is separately checked against a predetermined specified range, and the case where the color space data is within the predetermined specified range is 1, and the case where the color space data is not within the predetermined specified range. As 0, binary data for each pixel unit in the first excitation digital image and the second excitation digital image is obtained.

  Further, in the detection step, for each pixel unit obtained by collating the pixel units at the same position in the binarized data of each pixel unit in the first excitation digital image and the second excitation digital image. A microorganism or virus in the sample is detected by detecting the specific fluorescence reaction in the sample based on the arithmetic processing data.

  In this example, as shown in FIG. 1, using the fluorescence detection apparatus 1 including the light source 2, the camera 4, the control unit 51, the image processing unit 52, and the determination unit 53, A first excitation digital image acquisition step, a second excitation light irradiation step, a second excitation digital image acquisition step, an image processing step, and a detection step are performed.

In the fluorescence detection device 1, the light source 2 can irradiate the sample 8 with excitation light X having a specific wavelength through the filter 3. The camera 4 is configured to capture the surface of the sample 8 as a digital image.
The control unit 51, the image processing unit 52, and the determination unit 53 are constructed in the computer 5, and the light source 2 and the camera 4 are connected to the computer 5.

The control unit 51 changes at least one of the wavelength and intensity of the excitation light X transmitted through the filter 3 or changes the time from when the irradiation of the excitation light X from the light source 2 is started to when the camera 4 takes an image. Any one of them is performed, and a plurality of types of excitation-time digital images D1 and D2 are captured by the camera 4.
The image processing unit 52 obtains color space data for each pixel unit for each of the plurality of types of excitation digital images D1 and D2, and determines the color space data for each pixel unit in the plurality of types of excitation digital images D1 and D2, respectively. Pixels in a plurality of types of excitation-time digital images D1 and D2 are separately checked against a predetermined specified range, and the color space data is 1 when the color space data is within the predetermined specified range and 0 when the color space data is not within the predetermined specified range. The binarized data for each unit is obtained.
The determination unit 53 is based on the calculation processing data for each pixel unit obtained by collating the pixel units at the same position in the binarized data for each pixel unit in the plurality of types of excitation digital images D1 and D2. The presence or absence of the specific fluorescence reaction 81 in the sample 8 is detected.

  The light source 2 and the control unit 51 perform the first excitation light irradiation process and the second excitation light irradiation process, and the camera 4 and the control unit 51 perform the first digital image acquisition process and the second digital image acquisition process. It can be carried out. Further, the image processing unit 52 and the determination unit 53 can perform the above-described image processing step and detection step.

Hereinafter, the fluorescence reaction detection device 1 of this example and the specific biological component detection method using the same will be described in detail with reference to FIGS.
FIG. 1 is a diagram schematically showing the configuration of the fluorescence reaction detection apparatus 1. As shown in the figure, the light source 2 of this example is constituted by an ultraviolet lamp 2 that emits light having wavelengths of ultraviolet light and visible light. A filter 3 that transmits light of a specific wavelength is disposed at the light passage position of the ultraviolet lamp 2, and the sample 8 is irradiated with excitation light X having a desired wavelength and intensity by appropriately replacing the filter 3. be able to.

The wavelength of the excitation light X that passes through the filter 3 and irradiates the sample 8 corresponds to one of UV excitation (320 to 380 nm), B excitation (380 to 495 nm), or G excitation (495 to 570 nm). It is. The filter 3 includes a UV excitation filter 3 that transmits light having a wavelength of UV excitation from light emitted from the ultraviolet lamp 2, and a B excitation filter 3 that transmits light having a wavelength of B excitation from light emitted from the ultraviolet lamp 2. And a G excitation filter 3 that transmits light having a wavelength of G excitation from the light emitted from the ultraviolet lamp 2.
Further, the light source 2 is configured to change the intensity of the excitation light X by passing through the neutral density filter 30. The neutral density filter 30 is disposed at a position facing the filter 3. And the wavelength and intensity | strength of the excitation light X can be changed by changing the filter 3 and the neutral density filter 30 to be used.
Further, the excitation light X can be irradiated from the light source 2 to the sample 8 by being reflected by the mirror 43.

The camera 4 of this example is configured by combining an optical lens 42 having a predetermined magnification with a CMOS camera (digital camera) 41 that can be digitally processed by the computer 5. The camera 4 selects an appropriate number of pixels according to each detection target of microorganisms or viruses, and enlarges the digital image to 1000 to 10000 times by the magnification of the optical lens 42 and the magnification by the digital zoom of the CMOS camera 41. be able to. In this example, a filter 44 for blocking the ultraviolet rays and protecting the camera 4 is disposed in front of the optical lens 42 of the camera 4.
The control unit 51 of this example transmits a control signal to the light source 2, emits light from the light source 2, transmits a control signal to the camera 4, and images the surface of the sample 8 by the camera 4. Is configured to do.

In the fluorescence reaction detection apparatus 1 of the present example, the wavelengths of the excitation light X emitted from the light source 2 and the filter 3 are made different from each other, and two types of excitation light (first excitation light and second excitation light) are respectively applied to the sample 8. Irradiate (first excitation light irradiation step and second excitation light irradiation step). Then, two types of excitation digital images (first excitation digital image and second excitation digital image) D1 and D2 are photographed by the camera 4 (first digital image acquisition step and second digital image acquisition step).
These two types of digital images D1 and D2 at the time of excitation vary the wavelength of the excitation light X in the first excitation light irradiation process and the second excitation light irradiation process, and also the intensity or irradiation time (imaging time) of the excitation light X. You can shoot differently. The two types of excitation digital images D1 and D2 can also be photographed with different intensities or irradiation times (imaging time) of the excitation light X in the first excitation light irradiation step and the second excitation light irradiation step. .

In addition, at least one of the two types of excitation digital images D1 and D2 may be a digital image when the sample 8 is simultaneously irradiated with excitation light X having different wavelengths from the light source 2 and the filter 3. it can. Further, the excitation light X irradiated at the same time can be irradiated with different wavelengths and different intensities. Further, the excitation light X irradiated at the same time can be irradiated with only different intensities.
Each of the excitation-time digital pixels D1 and D2 can be photographed while the sample 8 is irradiated with the excitation light X, or can be photographed immediately after the sample 8 is irradiated with the excitation light X.

  FIG. 2 schematically shows the first excitation digital image D1, and FIG. 3 schematically shows the second excitation digital image D2. In FIG. 4, the result of the collation operation performed on the first excitation digital image D1 and the second excitation digital image D2 is visualized and schematically shown as a collation image D3.

  The wavelength of the excitation light X can be made different from each other in the two types of excitation-time digital images D1 and D2 as the wavelength of UV excitation, B excitation, or G excitation. In this case, for example, as shown in FIGS. 2 and 3, a fluorescence reaction 82 caused by foreign matter not detected such as dust and a specific fluorescence reaction 81 caused by microorganisms are photographed in both of the two types of excitation digital images D1 and D2. However, at least for the specific fluorescence reaction 81, it is assumed that the one of the excitation digital image D1 and the other excitation digital image D2 are photographed differently depending on the intensity of fluorescence. At this time, as shown in FIG. 4, when the pixel unit binarized data for the two types of digital images D1 and D2 at the time of excitation is obtained and the collation operation is performed, the specific fluorescence reaction 81 caused by microorganisms or viruses is changed to dust or the like. It can be clearly distinguished from the fluorescence reaction 82 caused by foreign matter. In addition, the specific fluorescence reaction 81 shown with the dotted line in FIG. 2 means that the specific fluorescence reaction 81 shown with the continuous line shown in FIG. 3 is weaker.

  Further, when the excitation light X having any wavelength of UV excitation, B excitation, or G excitation is used, the intensity of the excitation light X or the imaging time (from the time when the irradiation of the excitation light X from the light source 2 is started) It is also possible to use two types of digital images D1 and D2 at the time of excitation, which are photographed with different times). In this case, for example, as shown in FIG. 2 and FIG. 3, the foreign substance exhibits a fluorescence reaction 82 even when irradiated with the excitation light X having a weak intensity or the excitation light X for a short period of time. Are assumed to show a clear specific fluorescent reaction 81 only after irradiation with excitation light X with high intensity or irradiation with excitation light X for a long time. At this time, as shown in FIG. 4, when the binary calculation data of each pixel unit for the two types of digital images D1 and D2 at the time of excitation is obtained and the collation operation is performed, the influence of the fluorescence reaction 82 due to the foreign matter is canceled out. The specific fluorescence reaction 81 caused by microorganisms or the like can be clearly detected. In this case, it is effective when the time when a microorganism or the like exhibits a fluorescent reaction is later than that of a foreign substance.

The color space data obtained in the image processing unit 52 of this example indicates hue data of red (R), green (G), and blue (B), which are the three primary colors, by numerical values in a predetermined number of gradations. . The color space data in this example is obtained by decomposing light of a specific wavelength detected by the camera 4 into red, green, and blue data. Each of the red, green, and blue data is assigned 256 gradations, and each data (each primary color) is indicated by a numerical value of 0-255.
Further, the color space data can include luminance (brightness) expressed using the three primary colors. The luminance Y can be obtained from Y = a1 * R + a2 * G + a3 * B, where a1 to a3 are coefficients, R is red, G is green, and B is blue. The coefficients a1 to a3 are the values of red, green, and blue for a plurality of digital images when light of a plurality of wavelengths is captured by the camera 4, and X1 to Y = (a1 × X1 + a2 × X2 + a3 × X3) / 3 It can be obtained by substituting for X3.
Note that depending on the detection target of the microorganism or virus, the color space data may be only luminance data.

  In the image processing unit 52, the color space data d1 for each pixel unit in the first excitation-time digital image D1 when the first excitation light X is irradiated is irradiated with the first excitation light X to a specific fluorescence reaction. It is determined whether or not it is within the specified range of the color space data of the pixel showing 81. Further, the pixel in which the color space data d2 for each pixel unit in the second excitation digital image D2 when the second excitation light X is irradiated reflects the specific fluorescence reaction 81 by irradiating the second excitation light X to a microorganism or the like. It is determined whether it is within the specified range of the color space data.

  In FIG. 5, the first color space data d1 and the second color space data d2 in a pixel unit for each dot are visualized and shown. As shown in the figure, the numerical values represented by 0 to 255 of red, green, and blue in the first color space data d1 for the first excitation digital image D1 are R1, G1, and B1, and the second excitation digital image. The numerical values represented by 0 to 255 of red, green, and blue in the second color space data d2 for D2 are R2, G2, and B2. Also, the numerical value indicated by 0 to 255 of the luminance in the first color space data d1 for the first excitation digital image D1 is Y1, and the luminance of the second color space data d2 for the second excitation digital image D2 is 0. The numerical value indicated by ~ 255 is Y2.

When the value of the red data R1 in the first color space data d1 is within the specified range of the red data in the specific pixel in which the first excitation light X is irradiated to the microorganisms and the specific fluorescence reaction 81 is reflected, or Data that has been binarized is represented by binarized data R1 ′, with 1 being larger or smaller than a predetermined specified value and 0 being otherwise.
Further, when the value of the red data R2 in the second color space data d2 is within the specified range of the red data in the specific pixel in which the specific excitation reaction X is projected by irradiating the second excitation light X to the microorganism or the like, or this red color Data that has been binarized is represented by binarized data R2 ′, where 1 is the case where the data is larger or smaller than a predetermined specified value and 0 is the other case.
G1 ′, G2 ′, B1 ′, B2 ′, Y1 ′, and Y2 ′ are the same as R1 ′ and R2 ′.

In the determination unit 53, the collation operation performed between the pixel units at the same position in the digital image indicated by a large number of pixels can be the following logical operation.
In FIG. 6, the state which performs a logical operation with respect to the binarized data for every pixel unit of two types of digital images D1 and D2 at the time of excitation is visualized and shown roughly.
As the logical operation, at least one of R1 ′ (and) R2 ′, G1 ′ (and) G2 ′, B1 ′ (and) B2 ′, R1 ′ (or) R2 ′, G1 ′ (or) G2 ′, As at least one of B1 ′ (or) B2 ′, it can be performed as at least one of R1 ′ (xor) R2 ′, G1 ′ (xor) G2 ′, B1 ′ (xor) B2 ′.
Further, the logical operation is Y1 ′, where Y1 is the luminance value in the binarized data for the first excitation digital image D1, and Y2 is the luminance value in the binarized data for the second excitation digital image D2. (And) Y2 ′, Y1 ′ (or) Y2 ′, Y1 ′ (xor) Y2 ′ can also be performed.

R1 ′ (and) R2 ′ means calculation processing data obtained by setting 1 when both R1 ′ and R2 ′ are 1, and 0 otherwise.
R1 ′ (or) R2 ′ means arithmetic processing data obtained by setting 1 when at least one of R1 ′ and R2 ′ is 1, and 0 when both are 0. .
R1 ′ (xor) R2 ′ is operation processing data obtained by setting 1 when only one of R1 ′ and R2 ′ is 1, and setting 0 when both are 1 or 0. Means that.
The case of G1 ′, G2 ′, B1 ′, B2 ′, Y1 ′, Y2 ′ is the same as the case of R1 ′, R2 ′.
In this way, the arithmetic processing data obtained by performing the logical operation in the determination unit 53 is indicated as binary data of 1 or 0.

The specified range of the color space data, which is the determination criterion in the image processing unit 52, is a plurality (2) when the specific microorganisms or the like to be detected are irradiated with excitation light X having at least one of wavelength and intensity different from each other. Is obtained as a result of performing a collation operation on a pixel in which the specific fluorescence reaction 81 is reflected in the excitation digital image.
In addition, the prescribed range of the arithmetic processing data which is a determination criterion in the determination unit 53 is different in time from the time when the irradiation of the excitation light X is started to a specific microorganism or the like to be detected to the time when the camera 4 takes an image. In a plurality of (two) excitation-time digital images when the images are taken, it is also possible to obtain as a result of performing a collation operation on pixels in which the specific fluorescence reaction 81 is reflected in the excitation-time digital image.

The specified range of the color space data can be set with an appropriate margin with respect to the color space data of hue and luminance when the specific fluorescence reaction 81 is actually photographed for a specific microorganism or the like. At this time, the specific fluorescent reaction 81 can be photographed a plurality of times to determine the width of the specified range.
When the specific fluorescent reaction 81 is actually inspected for the sample 8, the excitation light X under the same conditions as the excitation light X used when determining the specified range of the color space data as a determination criterion is used. 8 is irradiated. In addition, when the wavelength or intensity of the excitation light X is different, the type of excitation light X used at the time of setting reference and at the time of detection is made the same.

The determination unit 53 of this example sets a hit pixel H when the arithmetic processing data for each pixel unit is 1. Then, when the shape and area in which the hit pixels H are formed side by side are within the specified range of the shape and area obtained in advance for the specific fluorescence reaction 81, it is detected that microorganisms or viruses are present in the sample 8.
The specified range of the shape and area for the specific fluorescence reaction 81 can be set with a moderate margin to the value obtained by actually measuring the shape and area of a specific microorganism or the like to be detected.

  In addition, each pixel in the determination unit 53 performs all of these values when R1 ′ (and) R2 ′, G1 ′ (and) G2 ′, and B1 ′ (and) B2 ′ are performed as logical operations, for example. When the value becomes 1, it can be determined as a hit pixel H. In addition, when one or two of these values are within the specified range, the hit pixel H can be determined. The same applies to the case where the determination unit 53 performs other logical operations.

The determination unit 53 specifies a pixel region having a size surrounding a shape in which the hit pixels H detected as having the specific fluorescence reaction 81 are formed side by side as the hit region A.
4 and 7 show a hit area A surrounding the hit pixel H. FIG.
In the determination unit 53 of this example, the X-axis and the Y-axis of the digital image are matched with the maximum contour of the hit pixel shape formed by arranging the hit pixels H with respect to the binarized data from which the hit pixels H are extracted. Surrounded by a rectangle with sides parallel to. Then, the pixel region surrounded by the rectangular shape is specified as the hit region A, and it is determined whether or not the hit pixel shape approximates the shape of the specific fluorescence reaction 81 such as a microorganism to be detected. .

  The determination unit 53 can detect the area (number of hit pixels H) of the hit pixel shape surrounded by the rectangular shape, the center of gravity position, and the like. When the hit pixel shape is within the specified range of the shape and area of the specific fluorescence reaction 81 for microorganisms or the like, the position, number, etc., of the hit pixel shape in the entire digital image at the time of excitation are specified. The specified range of the area of the specific fluorescence reaction 81 has a predetermined size range that is not less than a predetermined area and not more than a predetermined area. If the hit pixel shape is too large or too small, it does not fall within the specified range of the area of the specific fluorescence reaction 81.

In addition to detecting the hit pixel shape, the determination unit 53 has a predetermined ratio of the area (number of pixels) occupied by the hit pixel H in the total area (number of pixels) constituting the excitation digital image. When the ratio is equal to or greater than the ratio, it can be determined that the specific fluorescent reaction 81 is present in the sample 8.
The control unit 51 of this example captures the elementary digital image D4 when the excitation light X is not irradiated by the camera 4, and a monitor in which the pixel region corresponding to the hit region A in the elementary digital image D4 is connected to the computer 5. 6 is configured to perform a display process of enlarging display.
FIG. 8 schematically shows a state in which the pixel area B corresponding to the hit area A is enlarged and displayed on the monitor 6 for the elementary digital image D4. In this example, it is possible to actually confirm visually the region detected in the elementary digital image D4 that microorganisms or the like are present.

Moreover, in the determination part 53, the prescription | regulation range of the shape and area about the specific fluorescence reaction 81 can be preset about several types of microorganisms. Then, the determination unit 53 determines whether the shape and area formed by arranging the hit pixel shapes are included in a predetermined range of the shape and area obtained in advance for each of a plurality of types of microorganisms, etc. 8 can be used to estimate the types of microorganisms and the like present in 8. In this case, not only the presence or absence of microorganisms but also the type can be detected.
The determination unit 53 determines the type of microorganism or the like according to the ratio of the area (number of pixels) of the hit pixel H having a predetermined shape in the hit area A to the area (number of pixels) of the rectangular hit area A. It can also be estimated.

Next, a procedure for detecting a specific fluorescence reaction 81 such as a microorganism using the fluorescence reaction detection apparatus 1, that is, a method for detecting a specific biological component will be described with reference to the flowchart of FIG.
First, the sample 8 is irradiated with the first excitation light X having a predetermined wavelength and intensity from the light source 2 (first excitation light irradiation step; step S1 in the figure). And after predetermined time passes, the surface of the sample 8 is image | photographed with the camera 4 (1st digital image acquisition process; S2). At this time, the sample 8 is excited by the first excitation light X to cause various fluorescence reactions, and the camera 4 captures fluorescence of predetermined visible light. In addition, the first digital image D1 at the time of excitation that has been taken is captured and stored in the image processing unit 52 (see FIG. 1) of the computer 5.

  Next, the sample 8 is irradiated with the second excitation light X having at least one of the wavelength and intensity different from the first excitation light X from the light source 2 (second excitation light irradiation step; S3). And after predetermined time passes, the surface of the sample 8 is image | photographed with the camera 4 (2nd digital image acquisition process; S4). At this time, the sample 8 is excited by the second excitation light X to cause various fluorescent reactions, and the camera 4 captures fluorescence of predetermined visible light. The second excitation digital image D <b> 2 that has been shot is captured and stored in the image processing unit 52 of the computer 5.

Next, the image processing steps (S5 to S8) are performed as follows.
Specifically, first, first color space data d1 for each pixel unit in the first excitation digital image D1 and second color space data d2 for each pixel unit in the second excitation digital image D2 are obtained (S5). ).
Next, it is determined whether or not the first color space data d1 is within a predetermined range determined in advance for the specific fluorescence reaction 81 when the first excitation light X is irradiated, and the second color space data d2 Is in the predetermined prescribed range obtained for the specific fluorescence reaction 81 when the second excitation light X is irradiated in advance (S6).
Then, for the first color space data d1 and the second color space data d2, the case of being in the specified range is set to 1 of the binarized data (S7), and the case of not being in the specified range is set to 0 of the binarized data. (S8).

Next, a detection process (S9-S13) is performed as follows.
Specifically, first, a collation operation of a logical operation is performed on the binarized data of the first color space data d1 for each pixel unit and the binarized data of the second color space data d2 for each pixel unit. Then, calculation processing data for each pixel unit is obtained (S9).
Next, the pixel whose arithmetic processing data is 1 is extracted as a hit pixel H (S10). Next, it is determined whether or not the hit pixel shape formed by collecting the hit pixels H is within the prescribed range of the shape and area obtained in advance for the specific fluorescence reaction 81 (S11). When the hit pixel shape is within the specified range, it is detected that there is a specific fluorescence reaction 81 caused by microorganisms or the like (S12). On the other hand, if the hit pixel shape is not within the specified range, the process is terminated assuming that the specific fluorescence reaction 81 has not been detected in the sample 8 (S13).

In the specific biological component detection method 1 of this example, as described above, the first irradiation step (S1), the first digital image acquisition step (S2), the second excitation light irradiation step (S3), and the second At least a digital image acquisition step (S4), an image processing step (S5 to S8), and a detection step (S9 to S13) are performed (see FIG. 9).
In the first irradiation step, the sample 8 is irradiated with the first excitation light X at a specific wavelength, intensity, and irradiation time (see FIG. 1). Next, in the first digital image acquisition step, the surface of the sample 8 irradiated with the first excitation light X is photographed by the camera 4 to obtain a first excitation digital image D1 (see FIG. 2).

On the other hand, in the second irradiation step, the sample 8 is irradiated with the second excitation light X composed of excitation light different from the first excitation light in at least one of wavelength, intensity, and irradiation time. Next, in the second digital image acquisition step, the surface of the sample 8 irradiated with the second excitation light X is photographed by the camera 4, and a second excitation digital image D2 is acquired. Similar to the first digital image acquisition step, the fluorescence state of the sample 8 can be acquired as a digital image by photographing the surface of the sample 8. Since at least one of the wavelength, intensity, and irradiation time of the second excitation light X is different from that of the first excitation light, the sample 8 emits fluorescence in a pattern different from that of the first excitation light.
In the first irradiation process and / or the second irradiation process, when microorganisms or the like are present in the sample 8, the microorganisms and the like are excited by the excitation light X and emit predetermined fluorescence. In addition, the excitation digital image D1 and the second excitation digital image D2 exhibit different fluorescence states because the excitation light is different (see FIGS. 2 and 3).

In the image processing step, color space data d1 and d2 for each pixel unit are obtained for the first excitation digital image D1 and the second excitation digital image D2. Next, the image processing unit 52 collates the color space data d1 and d2 for each pixel unit in the two types of excitation-time digital images D1 and D2 separately with a predetermined specified range.
Then, the image processing unit 52 determines that the color space data d1 and d2 for each pixel unit is within a predetermined specified range for both the first excitation digital image D1 and the second excitation digital image D2. The binarized data is obtained for each pixel unit, with 0 being not within the prescribed range.

  Next, in the detection step, the binarized data of each pixel unit in the first excitation digital image D1 and the binarized data of each pixel unit in the second excitation digital image D2 are respectively in the same position. Logical operation is performed between certain pixel units, and calculation processing data for each pixel unit is obtained. Then, based on the arithmetic processing data, it can be determined whether or not the sample 8 has a specific fluorescent reaction 81 emitted by a microorganism or virus, and the microorganism or virus in the sample 8 can be detected.

  Incidentally, in general, the sample 8 contains foreign matters such as dust in addition to microorganisms or viruses, and the foreign matter also generates a fluorescent reaction 82 by the excitation light X (see FIGS. 2 and 3). However, the fluorescence property of the specific fluorescence reaction 81 and the fluorescence reaction 82 caused by dust differ depending on conditions such as the wavelength and intensity of the excitation light X. Therefore, when two types of excitation digital images D1 and D2 of the first excitation digital image and the second excitation digital image are captured, for example, the specific fluorescence reaction 81 is captured in two types of excitation digital images D1 and D2. On the other hand, it is assumed that the first excitation-time digital image D1 and the second excitation-time digital image D2 have different shooting methods depending on the intensity of fluorescence. In this case, by performing the above logical operation, the specific fluorescence reaction 81 caused by microorganisms or the like can be clearly distinguished from the fluorescence reaction 82 caused by other dust (foreign matter not detected).

  Therefore, according to the specific biological component detection method of this example, the presence or absence of microorganisms or viruses in the sample can be stably detected with high detection accuracy.

DESCRIPTION OF SYMBOLS 1 Fluorescence reaction detection apparatus 2 Light source 3 Filter 4 Camera 5 Computer 51 Control part 52 Image processing part 53 Judgment part 6 Monitor 8 Sample 81 Specific fluorescence reaction X Excitation light D1, D2 Excitation digital image D4 Elementary digital image d1, d2 Color space Data H Hit pixel A Hit area

Claims (7)

A specific biological component detection method for detecting the specific microorganism or virus by detecting a specific fluorescence reaction generated when a specific microorganism or virus in a sample is excited,
A first excitation light irradiation step of irradiating the sample with the first excitation light at a specific wavelength, intensity, and irradiation time;
A first digital image obtaining step of photographing the surface of the sample irradiated with the first excitation light and obtaining a first excitation digital image;
A second excitation light irradiation step of irradiating the sample with a second excitation light that is different from the first excitation light in at least one of wavelength, intensity, and irradiation time;
A second digital image acquisition step of photographing the surface of the sample irradiated with the second excitation light and acquiring a second excitation digital image;
Color space data for each pixel unit is obtained for at least the first excitation digital image and the second excitation digital image, and the color for each pixel unit in the first excitation digital image and the second excitation digital image. Each of the spatial data is separately checked against a predetermined specified range, and when the color space data is within the predetermined specified range, 1 is set, and when the color space data is not within the predetermined specified range, 0 is set. An image processing step for obtaining binarized data for each pixel unit in the digital image and the second excitation digital image,
Based on the calculation processing data for each pixel unit obtained by collating the pixel units at the same position in the binarized data for each pixel unit in the first excitation digital image and the second excitation digital image. And a detection step of detecting microorganisms or viruses in the sample by detecting the specific fluorescence reaction in the sample.   2. The specific biological component detection method according to claim 1, wherein the first excitation light and the second excitation light are further subjected to excitation light by changing at least one of a wavelength, intensity, and irradiation time with respect to the sample. Irradiation, imaging of the surface of the sample irradiated with the excitation light, and at least one excitation light irradiation-digital image acquisition step of acquiring a digital image at the time of excitation are performed. In the image processing step, at the time of the first excitation A specific biological component for obtaining the binarized data for at least one or more excitation digital images acquired in the excitation light irradiation-digital image acquisition step together with the digital image and the second excitation digital image Detection method.   3. The specific biological component detection method according to claim 1, wherein in the detection step, a hit pixel is formed when the arithmetic processing data for each pixel unit is 1, and the hit pixels are formed side by side. And a specific organism detection method, wherein the presence of the specific microorganism or virus is detected in the sample when the area and the area are within the prescribed range of the shape and area determined in advance for the specific fluorescence reaction. The specific biological component detection method according to claim 3, wherein a pixel region having a size surrounding a shape formed side by side with the hit pixels detected when the specific fluorescent reaction is present in the detection step is specified as a hit region,
A specific biological component detection method comprising: performing a display step of acquiring an elementary digital image when the excitation light is not irradiated and enlarging and displaying a pixel region corresponding to the hit region in the elementary digital image on a monitor . The specific biological component detection method according to any one of claims 1 to 4, wherein the color space data is at least one of red, green, blue hue, and luminance,
The specific biological component detection method according to claim 1, wherein the collation operation in the detection step is a logical operation performed on the binarized data for at least one of the hue and luminance.   The specific biological component detection method according to any one of claims 1 to 5, wherein the wavelengths of the first excitation light and the second excitation light are any of UV excitation, B excitation, and G excitation. A specific biological component detection method characterized by having a corresponding wavelength.   The specific biological component detection method according to any one of claims 1 to 7, wherein at least one of the first excitation light and the second excitation light is a plurality in which at least one of wavelength and intensity is different. A method for detecting a specific biological component, comprising a kind of excitation light.

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