JPS5830049B2 - Automatic reticulocyte measurement device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to an apparatus that identifies red blood cells and reticulocytes using color information of a stained blood specimen and automatically measures reticulocytes using the results.

A reticulocyte counting test is a test in which the collected blood is stained with supravital staining, then smeared onto a slide glass, dried, and the number of reticulocytes per 1000 red blood cells is counted under a microscope.

Similar to the white blood cell classification test, this test is performed visually under a microscope by a laboratory technician, and automation of the test is desired.

Based on the above facts, the present invention aims to provide an apparatus for automating the above reticulocyte counting test.

Hereinafter, the present invention will be explained in detail with reference to Examples.

FIG. 1 is a diagram showing the configuration of an embodiment of the present invention.

Light from a light source 1 is guided to a blood sample 3 placed on the stage of a microscope 2, and transmitted light from the blood sample 3 is guided to a color TV camera 4 to convert it into red (R), green (G), and blue (B) components. Separate colors.

Of these color signals, the G and B components necessary for processing are digitized by the A/D converter 4 and then stored in the IC memory 5.

A schematic diagram of the stored G and B components is shown in FIG.

Here, in FIG. 1, B and G are schematic diagrams of the above-mentioned B component and G component, respectively. For example, in the G component, "A" indicates reticulocytes, and "A" indicates red blood cells.

The B component is read out from the IC memory 5 and a density histogram as shown in FIG. 2 is created by the histogram creation circuit 6.

As can be seen from this figure, each blood cell component BL is distributed in the high concentration area, and the backblung component BG is distributed in the low concentration area, so the boundary value between the two, that is, the concentration value S ( g) is the threshold for separating the two.

In FIG. 1, 7 is a threshold detection circuit for detecting this threshold.

Next, the comparator circuit 8 uses the above components and S (g) to calculate the second
The binarization pattern in Figure 111, that is, the blood cell part is “1”
, a mask pattern with other parts set to "0'" is created and stored in the IC memory 5 again.

In FIG. 2: ij, the part indicated by 8 is the blood cell part indicated by "1", and the part indicated by 2 is the background other than the blood cells indicated by "0".

This mask pattern is read out and labeled using the labeling circuit 9 to label each blood cell (A, B, C, D) as shown in Figure 2 (i).
, E and F, and store them in the IC memory 5 again.

Next, repeat the following operation for each label of A to F above, that is, for each cell, until the number of processed cells reaches 100.
The movement of stage 2 and the input of images are repeated until the number of images becomes 0.

That is, the G component of each cell is read out from the IC memory 5, and the histogram creation circuit 6 is used to obtain density histograms as shown in FIG. 2V and FIG.

FIG. 2V shows a concentration histogram of red blood cells, and FIG. 2Vl shows a concentration histogram of reticulocytes.

As can be seen from both figures, the histograms of the high density portions of the two are clearly different, and by utilizing this property, it is possible to distinguish between the two.

In FIG. 1, numeral 10 represents an identification parameter extraction circuit.

In this parameter extraction circuit, V and Vl (7) in FIG.
- First, find the density and the peak value H8 of the histogram, and then find the density value d corresponding to the α percent frequency value of the peak value H6.

Here, the value of α is a statistically determined value, and is often 20 salaries.

Regarding the value of d, as shown in Figures 2M and 2VI, draw a tangent to the maximum slope point of the histogram between the concentration value C corresponding to the peak value H8 of the histogram and the highest concentration value e of blood cells. It is also effective to set the point where the tangent intersects with the horizontal axis (indicating the concentration g) as d.

Finally, the area 5de (second
The area of the shaded portion in FIGS. V and Vl) and the difference value Dde between the highest density value e and the density value d are determined.

This Sde and Dde and red blood cells and reticulitis The relationship between blood cells is determined as shown in Figure 2 Vi1.

Here, in FIG. 2 v11, the above-mentioned difference value Dde is set on the horizontal axis, and the above-mentioned area value Sde is set on the vertical axis, and these Sd
The area above the straight line L ('fl181J function) defined by the e value and the Dde value is the area where reticulocytes exist, and the area below the line is the area where red blood cells exist.

Therefore, the determination circuit 11 determines that cells having a value larger than the above-mentioned straight line are reticulocytes, and cells having a smaller value are red blood cells.

As described above, the determination circuit 11 in FIG. 1 uses the above two parameters Sde and Dde to determine whether the processed blood cells are red blood cells or reticulocytes, and the number is counted by counters 12 and 13, respectively. .

If you just process the input image, the above count will be 1.
If the number does not reach 000, move the stage attached to the microscope in step 2 and input again.

FIG. 3 is a detailed diagram of the identification parameter extraction circuit 10 of FIG. 1.

20 is a maximum value detection circuit, which determines the maximum value of the output H(g) of the histogram creation circuit 6 in FIG. 1, that is, H8 in FIG. 2;

A latch memory 21 temporarily stores the density level at Ho, that is, the 0 point.

22 is a constant multiplier that calculates αHo.

23 is a comparator, which determines the concentration level where H(g)≦αHo, that is, point d.

At this time, the output of the histogram creation circuit 6 is H(c) to H
The value is (e).

The subtracter 24 calculates Dde=e-d, and the adder 25 calculates s de =A H(g).

That is, the outputs of the subtracter 24 and the adder 25 are the feature parameters Dd used in the discriminant function of FIG.
e and Sde.

As described above in detail, according to the present invention, the calculation of reticulocytes can be easily automated.

[Brief explanation of drawings]

FIG. 1 is a block diagram 1 showing the configuration of an embodiment of the present invention.
, FIG. 2 1 to v11 are diagrams for explaining the operation,
FIG. 3 is a diagram showing the configuration of an embodiment of the main part of the configuration shown in FIG. 1.

Claims (1)

[Claims] 1 A device that separates the transmitted light of a stained blood sample into multiple single colors and uses this separated information to determine the extracted red blood cells and reticulocytes, determines the concentration histogram of each of the above blood cells. means for determining the concentration value of a high concentration portion having a frequency value of a predetermined percentage of the peak value of the histogram; means for determining the sum of frequency values equal to or higher than this concentration value; 1. An automatic reticulocyte measuring device comprising means for calculating a difference in concentration values in a high concentration area, and for identifying red blood cells and reticulocytes using the sum and the difference as parameters.