Staining intensity acquisition method, program, and staining intensity acquisition device

Abstract

To acquire a staining intensity appropriate to a target region corresponding to at least a portion of each cell from a cell image indicating a plurality of dyed cells.SOLUTION: In a target region 42 corresponding to at least a portion of a cell, first, a plurality of high-intensity pixels 422 having a relatively high pixel staining intensity, which is a staining intensity derived from a pixel value, are identified. Next, a region staining intensity, which is the staining intensity of the target region 42, is acquired as an average value of the pixel staining intensities of the plurality of high-intensity pixels 422. As a result, the present invention can acquire an appropriate region staining intensity enabling suppression of false negatives and false positives in dyeing determination.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to a technique for acquiring the staining intensity of at least a partial region of each cell from a cell image showing a plurality of stained cells. [Background technology]

[0002] In recent years, in medical and biological research, single-cell analysis of biological specimens such as tissue specimens and cell specimens has been carried out for the purpose of elucidating disease mechanisms, biological mechanisms, drug action mechanisms, etc. For example, in multiplex immunostaining analysis, biological substances such as proteins are stained by various methods and quantitative and qualitative analysis is performed by measuring the staining state.

[0003] In Patent Document 1, a cell region corresponding to a cell, or a region at the center or periphery of a cell, is extracted from an image of stained tissue, and the average density of the entire extracted region or the maximum density within the region is obtained as the "staining density." If the staining density is equal to or greater than a predetermined threshold, the cell is determined to be "positive" for that stain, and if the staining density is equal to or less than the threshold, the cell is determined to be "negative" for that stain. Being "positive" means, for example, that the cell has a significant amount of a specific protein or that intracellular organelles are present. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2022-123488 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, when determining whether a stain is positive or negative from the average staining intensity (staining concentration in Patent Document 1) in a region extracted from a cell image as in Patent Document 1, there is a risk that a false positive will be determined if the staining intensity is relatively high overall, or a false negative will be determined because the region with high staining intensity is small. In addition, if the determination is made only based on the maximum concentration in the extracted region, the pixel values ​​will be strongly influenced by pixels with abnormalities, and sufficient determination accuracy cannot be obtained.

[0006] The present invention has been made in consideration of the above-mentioned problems, and aims to obtain an appropriate staining intensity of a target region corresponding to at least a portion of each cell from a cell image showing a plurality of stained cells. [Means for solving the problem]

[0007] A first aspect of the present invention is a staining intensity acquisition method for acquiring a regional staining intensity, which is the staining intensity of a target region corresponding to at least a portion of each cell, from a cell image showing a plurality of stained cells, comprising the steps of: a) identifying a plurality of high-intensity pixels in the target region, each having a relatively high pixel staining intensity, which is a staining intensity derived from pixel values; and b) acquiring the regional staining intensity of the target region based on the pixel values ​​of the plurality of high-intensity pixels.

[0008] A second aspect of the present invention is the staining intensity acquisition method of the first aspect, wherein the plurality of high intensity pixels is a predetermined number of pixels in the target region having the highest pixel staining intensity.

[0009] A third aspect of the present invention is the staining intensity acquisition method of the second aspect, wherein the predetermined number is proportional to the number of pixels included in the target region.

[0010] A fourth aspect of the present invention is the staining intensity acquisition method of the first aspect (which may be any one of the first to third aspects), wherein the plurality of high intensity pixels are spaced apart from each other by a predetermined distance or more.

[0011] A fifth aspect of the present invention is a staining intensity acquisition method according to the first aspect, wherein the step a) comprises the steps of: identifying at least one peak pixel in the target region, the pixel staining intensity of which is higher than the pixel staining intensity of surrounding pixels; and identifying pixels within a circular region of a predetermined size centered on the at least one peak pixel as the plurality of high intensity pixels.

[0012] A sixth aspect of the present invention is the staining intensity acquisition method of the first aspect (which may be any one of the first to fifth aspects), wherein the cell image represents a tissue specimen.

[0013] A seventh aspect of the present invention is the staining intensity acquisition method according to any one of the first to sixth aspects, wherein the target region is extracted from the cell image as a region showing one entire cell.

[0014] Aspect 8 of the present invention is a staining intensity acquisition method of any one of aspects 1 to 6, further comprising, prior to step a), the steps of c) extracting a provisional target area from the cell image corresponding to at least a portion of each of the cells, and d) dividing the provisional target area into an internal area and an outer peripheral area, wherein the target area is either the internal area or the outer peripheral area.

[0015] A ninth aspect of the present invention is a program that causes a computer to obtain a regional staining intensity, which is the staining intensity of a target region corresponding to at least a portion of each cell, from a cell image showing a plurality of stained cells, and execution of the program by the computer causes the computer to perform the steps of: a) identifying a plurality of high-intensity pixels in the target region, the pixel staining intensity being a staining intensity derived from pixel values, which is relatively high; and b) obtaining the regional staining intensity of the target region based on the pixel values ​​of the plurality of high-intensity pixels.

[0016] A tenth aspect of the present invention is a staining intensity acquisition device that acquires a regional staining intensity, which is the staining intensity of a target region corresponding to at least a portion of each cell, from a cell image showing a plurality of stained cells, and includes a pixel identification unit that identifies a plurality of high-intensity pixels in the target region having relatively high pixel staining intensity, which is a staining intensity derived from pixel values, and an intensity acquisition unit that acquires the regional staining intensity of the target region based on the pixel values ​​of the plurality of high-intensity pixels. Effect of the Invention

[0017] According to the present invention, it is possible to obtain an appropriate staining intensity for a target region. [Brief description of the drawings]

[0018] [Figure 1] FIG. 13 is a diagram showing the configuration of a computer that functions as a staining intensity acquisition device. [Diagram 2] FIG. 2 is a block diagram showing the functional configuration of a staining intensity acquisition device. [Diagram 3] FIG. 2 is a diagram showing the flow of operations of a computer. [Figure 4] FIG. 1 shows cell images. [Diagram 5] FIG. [Figure 6] FIG. 13 illustrates locations of high intensity pixels identified in a region of interest. [Figure 7] FIG. 13 is a diagram showing a cell image indicating the determination result. [Figure 8] FIG. 13 shows a state in which the entire target region is non-specifically stained. [Figure 9] 13 is a diagram for explaining another example of the operation of the staining intensity acquisition unit. FIG. [Figure 10] 13 is a diagram for explaining another example of the operation of the staining intensity acquisition unit. FIG. [Figure 11] FIG. 13 is a diagram showing the flow of still another example of the operation of the staining intensity acquisition unit. [Figure 12] FIG. 13 is a diagram for explaining yet another example of the operation of the staining intensity acquisition unit. [Figure 13]13 is a diagram illustrating a flow of another example of the operation of the target region acquisition unit. [Figure 14] 13 is a diagram for explaining another example of the operation of the target region acquisition unit; FIG. [Figure 15] 13 is a diagram for explaining another example of the operation of the target region acquisition unit; FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0019] FIG. 1 is a diagram showing the configuration of a computer 5 functioning as a staining intensity acquisition device according to one embodiment of the present invention. The staining intensity acquisition device is a device that acquires staining intensity (hereinafter referred to as "regional staining intensity" to distinguish it from the staining intensity for each pixel described later) of a target region corresponding to at least a part of each cell from a cell image. A cell image is a digital image showing multiple cells stained with a biological substance such as a specific protein or RNA (ribonucleic acid), and is, for example, an image obtained by imaging a biological specimen obtained by an immunostaining method. The cell image may be one of multiple images obtained for each staining in a multiple immunostaining method in which staining and destaining are repeated.

[0020] The computer 5 has a typical computer system configuration including a CPU 51, a GPU 52, a ROM 53, a RAM 54, a fixed disk 55, a display 56, an input unit 57, a reading device 58, a communication unit 59, and a bus 50. The CPU 51 performs various types of arithmetic processing. The GPU 52 performs various types of arithmetic processing related to image processing at high speed. The ROM 53 stores basic programs. The RAM 54 stores various types of information. The fixed disk 55 stores information. The display 56 is a display unit that displays various types of information such as images.

[0021] The input unit 57 includes a keyboard 57a and a mouse 57b for receiving input from an operator. The reader 58 reads information from a computer-readable recording medium 9 such as an optical disk, a magnetic disk, a magneto-optical disk, or a memory card. The display 56, the keyboard 57a, the mouse 57b, and the reader 58 are connected to the bus 50 via an interface (I / F). The communication unit 59 transmits and receives signals to and from devices external to the computer 5.

[0022] The bus 50 is a signal circuit that connects the CPU 51, GPU 52, ROM 53, RAM 54, fixed disk 55, display 56, input unit 57, reading device 58, and communication unit 59. An imaging device 8 external to the computer 5 is connected to the bus 50 via an I / F. The imaging device 8 obtains an image of a specimen as a cell image, and the data is stored in the fixed disk 55.

[0023] In the computer 5, the program 91 is read in advance from the recording medium 9 via the reading device 58 and stored in the fixed disk 55. The program 91 may be stored in the fixed disk 55 via a network. The CPU 51 and the GPU 52 execute arithmetic processing while using the RAM 54 and the fixed disk 55 in accordance with the program 91. The CPU 51 and the GPU 52 function as a calculation unit in the staining intensity acquisition device 1. Other configurations functioning as a calculation unit other than the CPU 51 and the GPU 52 may be employed.

[0024] Fig. 2 is a block diagram showing the functional configuration of the staining intensity acquisition device 1 realized by the above-mentioned computer 5 executing arithmetic processing and the like according to the program 91. Fig. 2 also shows configurations other than the function of the staining intensity acquisition device 1. In Fig. 2, a staining intensity acquisition unit 13 shows the main functional configuration of the staining intensity acquisition device 1. The memory unit 11 and the target area acquisition unit 12 may be included in the functional configuration of the staining intensity acquisition device 1. The computer 5 further realizes the functional configuration of a staining determination unit 14, whereby the computer 5 becomes a device that determines whether the staining of each cell in a cell image is positive or negative.

[0025] All or part of each functional configuration may be realized by a dedicated electric circuit. Furthermore, these functional configurations may be realized by a plurality of computers. Of the functional configurations shown in Fig. 2, storage unit 11 is realized mainly by RAM 54 and fixed disk 55. Target area acquisition unit 12, staining intensity acquisition unit 13, staining determination unit 14, and display control unit 15 are realized by CPU 51, GPU 52, ROM 53, RAM 54, fixed disk 55, and their peripheral configurations.

[0026] The storage unit 11 stores cell images, which are images of a biological specimen (hereinafter also simply referred to as a "specimen") acquired by the imaging device 8. The stored images are, to be precise, "image data 81" as shown in FIG. 2, and in the following description, processing of an image is, to be precise, processing of the image data 81.

[0027] FIG. 3 is a diagram showing the flow of operation of the computer 5, illustrating the operation of obtaining regional staining intensity (which may be considered as the staining intensity of each cell), which is the staining intensity of each target region in a cell image, and determining whether the staining of the target region is positive or negative.

[0028] First, a specimen is imaged and a cell image is prepared in the storage unit 11 (step S11) by the control of the imaging device 8 by the computer 5 or by the operation of the imaging device 8. As illustrated in Fig. 4, the cell image 4 stored in the storage unit 11 shows a plurality of cells 41. In Fig. 4, each cell 41 is simply represented by a circle.

[0029] Next, the target area acquisition unit 12 acquires an area corresponding to at least a part of each cell 41 as a target area from the cell image 4 (step S12). When the cell image 4 to be processed is one of a plurality of images obtained for each staining in a multiple immunostaining method in which staining and destaining are repeated, an area corresponding to the target area may be acquired from a cell image stained by a different staining from the cell image 4 (i.e., a differently stained image of the same specimen), and this area may be used as the target area of ​​the cell image 4. The function of the area division unit 121 in the target area acquisition unit 12 will be described later. Hereinafter, the plurality of target areas acquired by the target area acquisition unit 12 will be referred to as a "group of target areas."

[0030] One target region may be a so-called "cell region" corresponding to one whole cell 41, or may be a part of the cell region, such as a region corresponding to the nucleus of a cell. Acquisition of the target region can be performed using various known methods. For example, various known methods for acquiring a cell region, various known methods for acquiring a nucleus region, and various known methods for acquiring at least a part of a region of a cell that is not captured by the tissue of the cell can be used. When single cell analysis is performed, the target region and the cell preferably correspond one-to-one. That is, the target region is at least a part of the cell region, and the cell region and the target region correspond one-to-one. In this way, the target region is a region corresponding to at least a part of each cell. If the computer 5 has a function of extracting the target region, it does not necessarily have a function of extracting the cell region.

[0031] Next, the staining intensity acquisition unit 13 selects a target region to be the first processing target (step S13). Fig. 5 is a diagram illustrating a target region 42 when the target region 42 is a cellular region. A stained region 421 exists in the target region 42. In Fig. 5, the region 421 is shown as a circle with parallel hatching for ease of understanding, but in reality, the region 421 has light and dark shades, various shapes, and some regions have unclear contours.

[0032] The staining intensity acquisition unit 13 includes a pixel identification unit 131 and an intensity acquisition unit 132. The pixel identification unit 131 identifies a plurality of pixels (hereinafter referred to as "high intensity pixels") having a relatively high staining intensity (hereinafter referred to as "pixel staining intensity") derived from a pixel value among the pixels in the target region 42 (step S14). The "staining intensity" in "region staining intensity" and "pixel staining intensity" refers to the intensity at which staining appears in a cell image. For example, in an image in which color development due to staining is captured by a bright-field imaging system, if a strongly stained region appears dark, the darker the intensity, the higher the staining intensity, and in an image in which emission due to fluorescent dye staining is captured, if a strongly stained region appears bright, the brighter the intensity, the higher the staining intensity.

[0033] Therefore, when the cell image is a monochrome image, the pixel staining intensity may be higher or lower as the pixel value is larger. When the cell image is a color image, the pixel staining intensity may be higher or lower as the value of a specific color element of the pixel or a value calculated from multiple color elements is larger. When the cell image is a color image, an image that has been previously processed, such as color separation or color extraction, to extract only the expected color components of the staining may be treated as a new cell image to be processed. When the cell image is a monochrome image, an image that has been processed may also be treated as a new cell image. As described later, the same applies to the relationship between the level of the region staining intensity derived from the pixel values ​​of multiple high-intensity pixels and the brightness and color of the target region 42 in the image.

[0034] Generally speaking, "stain intensity" is a value derived from the pixel values ​​of a single pixel or multiple pixels contained in a region (pixel stain intensity may be the pixel value itself) and indicates the intensity of staining. More precisely, "pixel stain intensity" is a value based on the pixel value of a single pixel, and "region stain intensity" is a value based on the pixel values ​​of multiple high intensity pixels contained in the region of interest 42.

[0035] As described above, if the pixel staining intensity increases, the pixel value (including the case where the pixel value corresponds to the value of one color component of the color pixel value or a value derived from multiple color components) simply increases or decreases. Therefore, the pixel identifying unit 131 of the staining intensity acquisition unit 13 can identify multiple high intensity pixels having relatively high pixel staining intensities in the target region 42 without actually calculating the pixel staining intensity. For example, the pixel identifying unit 131 identifies a predetermined number of pixels having the largest pixel value or a predetermined number of pixels having the smallest pixel value as high intensity pixels. This allows a predetermined number of pixels having the highest pixel staining intensities in the target region 42 to be easily identified as multiple high intensity pixels. Note that the "predetermined number of pixels having the highest pixel staining intensity" refers to a predetermined number of pixels that are at the top when the pixels are arranged in descending order of pixel staining intensity.

[0036] FIG. 6 is a diagram illustrating the positions of four high intensity pixels 422 identified in the target region 42 with "+" marks. The number of high intensity pixels 422 identified in each target region 42 is not particularly limited, but in a preferred example, the number of high intensity pixels 422 is proportional to the number of pixels included in each target region 42 in one image. In another preferred example, the number of high intensity pixels 422 is constant regardless of the size of the target region 42. The ratio of the number of high intensity pixels 422 to the number of pixels in the target region 42 and the number of high intensity pixels 422 are appropriately set depending on the size of the actual target region 42, the resolution of the cell image, and the characteristics of the staining (for example, the amount of the target protein or intracellular organelle present, the size of the target, and the ease of staining).

[0037] The ratio of the number of high intensity pixels 422 to the number of pixels in the target region 42 may be automatically determined by learning. For example, for cell images with various stains, a computer learning device may be made to learn the positive or negative status of multiple target regions 42 and the combination of the optimal number of high intensity pixels 422, and when an input image is input to the learning device, the ratio of the number of high intensity pixels 422 to the number of pixels in the target region 42 may be output.

[0038] Next, the intensity acquisition unit 132 acquires the average value of the pixel dye intensities of the identified multiple high intensity pixels 422 as the regional dye intensity of the target region 42 (step S15). As described above, since pixel values ​​can be used instead of pixel dye intensities, the average value of the pixel values ​​of the high intensity pixels 422 may be acquired as the regional dye intensity in step S15. Of course, the pixel dye intensity of each high intensity pixel 422 may be calculated, and the average value of the pixel dye intensities may be acquired as the regional dye intensity of the target region 42. In this way, the intensity acquisition unit 132 acquires the regional dye intensity of the target region 42 based on the pixel values ​​of the multiple high intensity pixels 422. When the number of high intensity pixels 422 is proportional to the number of pixels included in the target region 42, the regional dye intensity can be acquired while suppressing the influence of the size of the target region 42.

[0039] When the regional staining intensity for one target region 42 is acquired, the staining intensity acquisition unit 13 checks whether the next target region 42 for which the regional staining intensity has not been obtained exists in the target region group (step S16), and if so, selects the next target region 42 and acquires the regional staining intensity (steps S13 to S15). When the regional staining intensities for all target regions 42 are acquired (step S16), the process proceeds to the staining determination unit 14.

[0040] In the staining determination unit 14, a threshold is set in advance by the operator via the input unit 57, and the regional staining intensity of each target region 42 of the target region group is compared with the threshold. If the regional staining intensity of the target region 42 is higher than the threshold, the target region 42 is determined to be positive for staining (step S17). Note that the smaller the average pixel value of the high intensity pixels included in the target region 42, the higher the regional staining intensity. In addition, when the average pixel value is directly compared with the threshold in the staining determination unit 14, the target region 42 is determined to be positive for staining if the average pixel value is smaller than the threshold. The determination result 82 of each target region 42 is stored in the memory unit 11.

[0041] The determination result 82 is displayed on the display 56 under the control of the display control unit 15. For example, as shown in Fig. 7, among the target areas 42 of the cell image 4, the positive target areas 42a are colored and the cell image 4 is displayed on the display 56.

[0042] In the staining intensity acquisition device 1, by using the pixel staining intensity of the high intensity pixel 422, staining judgment, that is, judgment of whether or not the staining is positive can be appropriately performed. For example, as shown in FIG. 8, the entire target region 42 may be non-specifically stained, and the entire target region 42 may have about 60% of the maximum staining intensity. Even if such a staining state should not be judged as positive, if the average value of the pixel staining intensity of the entire target region 42 is acquired as the regional staining intensity of the target region 42 as in the conventional method, the target region 42 will be erroneously judged as positive if the threshold value is 50%. On the other hand, in the case of FIG. 6, although it should be judged as positive, since there are few regions with high staining intensity, if the average of the pixel staining intensity of the entire target region 42 is obtained as the regional staining intensity, and if this value is 40%, the target region 42 will be erroneously judged as negative.

[0043] In contrast, when the pixel staining intensity of the high intensity pixels 422 is used, and the average of the pixel staining intensities of the high intensity pixels 422 is obtained as the regional staining intensity, the regional staining intensity is obtained as, for example, 80%, and the target region 42 is determined to be positive. In this way, by using the pixel staining intensity of the high intensity pixels 422 (i.e., by using the pixel values), it is possible to appropriately determine a region as positive when it has a strongly stained region, and to prevent false positive and false negative determinations.

[0044] The staining judgment using the high intensity pixel 422 is particularly suitable for staining judgment of a cell image stained with nuclear staining or cytoplasmic staining, in which only a part of the target region 42 is stained darkly. Also, even if there is noise called background, in which a part or the whole of the cell tissue is colored lightly and non-specifically, appropriate staining judgment can be performed. Since background is more likely to occur when staining a tissue specimen than cultured cells, the staining judgment using the high intensity pixel 422 is suitable for staining judgment of a tissue specimen.

[0045] In addition, the staining judgment using the high intensity pixel 422 is suitable for staining judgment of a protein that is highly localized or unevenly distributed within a cell in the presence of a background, and is more suitable for staining judgment of fibrillarin localized in the nucleolus than for actin that forms the cytoskeleton.Furthermore, it is also suitable for staining judgment of an image with a low S / N ratio, and is more suitable for staining judgment using an enzyme antibody method using a coloring agent and a bright field optical system than for staining judgment using a fluorescent dye and a fluorescent optical system.

[0046] It should be noted that all of the effects of determining regional staining intensity using high intensity pixel 422 described above are also applicable to determining regional staining intensity by identifying high intensity pixels using peak pixels, as described below.

[0047] 9 and 10 are diagrams for explaining another example of the operation of the staining intensity acquisition unit 13. FIG. 9 is a diagram illustrating a target region 42 that should be determined to be negative. In the target region 42 in FIG. 9, one strongly stained region 421a exists, and multiple small weakly stained regions 421b that should not be recognized as stained exist. When a predetermined number of pixels with high pixel staining intensity are extracted from the region 421a when the high intensity pixel 422 is identified in the example of FIG. 9, the average pixel staining intensity of the high intensity pixel 422 becomes high, and the target region 42 is erroneously determined to be positive.

[0048] Therefore, in the improved staining intensity acquisition unit 13, a plurality of high intensity pixels 422 are acquired as pixels that are separated from each other by a predetermined distance or more. Specifically, as shown in FIG. 10, first, a pixel 422a having the highest staining intensity is identified as the high intensity pixel 422. Next, a pixel 422b having the highest staining intensity among pixels that are separated from the pixel 422a by the distance of the radius of the circle of the broken line 43 or more is identified as the next high intensity pixel 422. Next, a pixel 422c having the highest staining intensity among pixels that are separated from both of the already identified high intensity pixels 422a and 422b by the distance of the radius of the circle of the broken line 43 or more is identified as the next high intensity pixel 422. The above process is repeated to identify a predetermined number of high intensity pixels 422 (pixels 422a to 422d shown in FIG. 10).

[0049] Because the pixel staining intensities of pixels 422b, 422c, and 422d are not high, the regional staining intensity, which is the average value of the pixel staining intensities of the high intensity pixels 422, is low. As a result, the target region 42 is correctly determined to be negative. By spacing the multiple high intensity pixels 422 apart from each other, the regional staining intensity can be determined while suppressing the strong influence of a particular region with high staining intensity.

[0050] The distance by which the high intensity pixels 422 should be separated, i.e., the radius of the circle indicated by the dashed line 43 in Fig. 10, may be automatically determined. For example, the distance may be determined as a value proportional to the average radius of a circle that includes the multiple cellular regions, and inversely proportional to the square root of the number of high intensity pixels 422 to be identified. In this manner, the "predetermined distance" by which the multiple high intensity pixels 422 should be separated may be different for each target region 42.

[0051] Next, still another operation example of the dyeing intensity acquisition unit 13 in Fig. 2 will be described with reference to Fig. 11 and Fig. 12. In this operation example, the operation shown in Fig. 11 is executed by the pixel specifying unit 131 in step S14 in Fig. 3.

[0052] First, the pixel identifying unit 131 identifies at least one peak pixel 423 in the target region 42 as shown in FIG. 12 (step S141). The peak pixel 423 is a pixel in the target region 42 that has a higher pixel staining intensity than the surrounding pixels, i.e., a pixel at a position where the pixel staining intensity is a peak when viewed two-dimensionally. However, in order to exclude peak pixels in areas with low staining intensity, a lower limit is set for the pixel staining intensity for identifying the peak pixel 423. Also, even if a pixel exists at a peak position, if the number of surrounding pixels that form the peak is small, the pixel may be excluded from the peak pixels. A peak pixel is a pixel that has a pixel staining intensity equal to or greater than a predetermined intensity and is located at the apex of a peak (of staining intensity) equal to or greater than a predetermined size.

[0053] Next, the pixel identifying unit 131 identifies pixels within a circular region 424 of a predetermined size centered on at least one peak pixel 423 as a plurality of high intensity pixels (step S142). The radii of the circular regions 424 may all be the same, or may be larger as the pixel dyeing intensity of the peak pixel 423 increases. In other words, the "predetermined size" of the circular regions 424 may all be the same, or may be different for each circular region 424.

[0054] Thereafter, the intensity acquisition section 132 acquires an average value of the pixel dye intensities of all pixels in at least one circular region 424 as the regional dye intensity of the target region 42. If the number of circular regions 424 is two or more, the average value of the pixel dye intensities in each circular region 424 may be calculated, and then the average value of the multiple average values ​​may be used as the regional dye intensity of the target region 42. In this manner, the intensity acquisition section 132 acquires the regional dye intensity of the target region 42 based on the pixel dye intensities of high intensity pixels in a circular region 424 of a predetermined size centered on at least one peak pixel 423.

[0055] The peak pixel 423 can be easily specified using, for example, the open source computer vision library "Open CV". By acquiring the regional staining intensity of the target region 42 using the peak pixel 423, it becomes possible to perform a more accurate staining judgment when staining occurs such that multiple positive spots are scattered within the target region 42. Therefore, acquisition of the regional staining intensity using the peak pixel 423 is suitable for the case where multiple peak pixels 423 are identified for one target region 42 by the pixel identification unit 131. Staining judgment using the peak pixel 423 is particularly suitable for staining judgment on a cell image stained with nuclear staining or cytoplasmic staining, in which only a part of the target region 42 is stained darkly.

[0056] Next, another operation example of the target region acquisition unit 12 of FIG. 2 will be described with reference to FIG. 13 to FIG. 15. In the other operation example, steps S21 and S22 of FIG. 13 are executed by the target region acquisition unit 12 instead of step S12 of FIG. 3. The target region acquisition unit 12 first extracts a provisional target region group from the cell image 4 (step S21). One provisional target region may be a so-called "cell region" corresponding to one whole cell, or may be a part of a cell region, such as a region corresponding to the nucleus of a cell. When single cell analysis is performed, preferably, the provisional target region and the cell correspond one-to-one. That is, the provisional target region is at least a part of the cell region, and the cell region and the provisional target region correspond one-to-one. In this way, the provisional target region is a region corresponding to at least a part of each cell. The computer 5 does not necessarily have a function of extracting a cell region as long as it has a function of extracting a provisional target region.

[0057] FIG. 14 is a diagram illustrating a provisional target region 44. The region 421 shown by a circle with parallel diagonal lines indicates a dyed region, but in reality, the region 421 has various sizes and shapes, and has a variety of shadings. In addition, some of the regions 421 have unclear contours. The target region acquisition unit 12 has the function of the region division unit 121 shown in FIG. 2, and the region division unit 121 divides each provisional target region 44 into an inner region 441 on the inside and an outer periphery region 442 on the outer periphery (step S22). The outer periphery region 442 is a region of a certain width along the outer periphery edge of the provisional target region 44. The inner region 441 is a region inside the outer periphery region 442. Then, the target region acquisition unit 12 acquires either the inner region 441 or the outer periphery region 442 as the target region. That is, the inner regions 441 of all the provisional target regions 44 are acquired as the target regions, or the outer circumferential regions 442 of all the provisional target regions 44 are acquired as the target regions. After that, steps S13 to S17 shown in FIG.

[0058] That is, when the internal region 441 is treated as the target region, pixels in the internal region 441 having relatively high pixel dyeing intensity are identified as high intensity pixels 422 in step S14 in FIG. 3. In FIG. 14, the high intensity pixels 422 are illustrated by a "+" mark. On the other hand, when the peripheral region 442 is treated as the target region, pixels in the peripheral region 442 having high pixel dyeing intensity are identified as high intensity pixels 422 in step S14, as illustrated in FIG. 15. Then, the regional dyeing intensity of the target region is obtained (step S15). After the regional dyeing intensities of all the target regions are obtained (step S16), dyeing determination is performed for all the target regions (step S17).

[0059] By setting the target region as the inner region 441, even if the staining occurs non-specifically with respect to the outer peripheral region 442, it is possible to appropriately determine the staining of the inner region 441. For example, when it is desired to stain and detect a specific protein in the nucleus of a cell or in its vicinity, it is possible to eliminate the influence of staining of the cell membrane. It is also possible to eliminate the influence of staining of adjacent cells. When the target region is the outer peripheral region 442, it is possible to appropriately determine the staining of the outer peripheral region 442, even if the staining occurs non-specifically with respect to the inner region 441. For example, when it is desired to stain and detect a specific protein in the cell membrane, it is possible to eliminate the influence of staining of other than the cell membrane.

[0060] Of course, the provisional target region 44 is not limited to a cell region (a region showing the entire cell), and for example, the provisional target region 44 may be extracted as a nucleus and its neighboring region, and the region inside the nucleus may be acquired as an inner region 441, and the region on the periphery of the nucleus may be acquired as an outer region 442. By dividing the provisional target region 44 into the inner region 441 and the outer region 442 and using only one of them as the target region, artifacts in the analysis can be effectively suppressed, and more robust regional staining intensity can be acquired.

[0061] The above embodiment can be modified in various ways.

[0062] In the example shown in FIG. 6, a predetermined number of pixels in the target region 42 having the highest pixel staining intensity are identified as the plurality of high intensity pixels 422. In the example shown in FIG. 12, at least one peak pixel 423 and its surrounding pixels are identified as the plurality of high intensity pixels. In this manner, the high intensity pixels may be identified by various methods as long as they are pixels having relatively high pixel staining intensity. The high intensity pixels are preferably included in the top 50% (more preferably, the top 30%) of the pixels having high pixel staining intensity among all pixels in the target region 42. That is, the high intensity pixels may be selected from the top 50% of the pixels having high pixel staining intensity by various methods. Then, the regional staining intensity of the target region 42 is obtained by performing various calculations on the pixel values ​​of the plurality of high intensity pixels.

[0063] The flow of operations shown in Fig. 3 may be modified in various ways within the scope of similar effects. For example, each time the regional staining intensity of one target region 42 is acquired, the regional staining intensity may be compared with a threshold value, and the operation may proceed to acquisition of the regional staining intensity of the next target region 42.

[0064] The method of using either the inner region 441 or the outer peripheral region 442 in FIGS. 13 to 15 can also be applied to the method of obtaining regional staining intensity using the peak pixel 423 shown in FIGS.

[0065] The staining in this embodiment is not limited to multiple staining, nor is it limited to staining using antibodies. This embodiment can be used to judge the staining in various stainings as long as they stain substances derived from living organisms. This embodiment is preferably suitable for cases in which cells appear in shading due to staining. It is also suitable for staining specific proteins.

[0066] The configurations in the above-described embodiment and each of the modified examples may be combined as appropriate as long as they are not mutually inconsistent. [Explanation of symbols]

[0067] 1 Staining intensity acquisition device 4. Cell Images 5. Computers 13 Staining intensity acquisition unit 41 cells 42 Target Area 44 Provisional Target Area 91 Programs 131 Pixel Identification Unit 132 Strength acquisition section 422 high intensity pixels 423 peak pixels 424 Circular area (centered on peak pixel) 441 Internal area 442 Outer area S14, S15, S21, S22, S141, S142 steps

Claims

1. A staining intensity acquisition method for acquiring a region staining intensity, which is a staining intensity of a target region corresponding to at least a part of each cell from a cell image showing a plurality of stained cells, comprising: a) identifying a plurality of high intensity pixels in the region of interest, the high intensity pixels having a pixel stain intensity derived from pixel values; b) obtaining the regional staining intensity of the region of interest based on pixel values ​​of the plurality of high intensity pixels; A staining intensity acquisition method comprising:

2. The staining intensity acquisition method according to claim 1, A staining intensity acquisition method, wherein the plurality of high intensity pixels is a predetermined number of pixels in the target region that have the highest pixel staining intensity.

3. The staining intensity acquisition method according to claim 2, A staining intensity acquisition method, wherein the predetermined number is proportional to the number of pixels contained in the target region.

4. The staining intensity acquisition method according to claim 1, A staining intensity acquisition method, wherein the plurality of high intensity pixels are spaced apart from each other by a predetermined distance or more.

5. The staining intensity acquisition method according to claim 1, The step a) comprises: identifying at least one peak pixel in the region of interest, the peak pixel having a pixel staining intensity greater than the pixel staining intensity of surrounding pixels; identifying pixels within a circular region of a predetermined size centered on the at least one peak pixel as the plurality of high intensity pixels; A staining intensity acquisition method comprising:

6. The staining intensity acquisition method according to claim 1, The staining intensity acquisition method, wherein the cell image represents a tissue specimen.

7. A staining intensity acquisition method according to any one of claims 1 to 6, A staining intensity acquisition method in which the target area is extracted from the cell image as an area showing an entire cell.

8. A staining intensity acquisition method according to any one of claims 1 to 6, Prior to the step a), c) extracting a provisional region of interest from the cell image corresponding to at least a portion of each of the cells; d) dividing the temporary target region into an inner region and a perimeter region; Further equipped with A staining intensity acquisition method in which the target region is either the internal region or the peripheral region.

9. A program for causing a computer to obtain a region staining intensity, which is a staining intensity of a target region corresponding to at least a part of each cell from a cell image showing a plurality of stained cells, wherein the execution of the program by the computer includes the steps of: a) identifying a plurality of high intensity pixels in the region of interest, the high intensity pixels having a pixel stain intensity derived from pixel values; b) obtaining the regional staining intensity of the region of interest based on pixel values ​​of the plurality of high intensity pixels; A program that executes the following.

10. A staining intensity acquisition device for acquiring a region staining intensity, which is a staining intensity of a target region corresponding to at least a part of each cell from a cell image showing a plurality of stained cells, comprising: a pixel identification unit that identifies a plurality of high intensity pixels in the target region, the high intensity pixels having a pixel staining intensity that is a staining intensity derived from a pixel value; an intensity acquisition unit that acquires the regional staining intensity of the target region based on pixel values ​​of the plurality of high intensity pixels; A staining intensity acquisition device comprising:

Images