JPH03191848A - Method for judging particle aggregation pattern - Google Patents

Method for judging particle aggregation pattern

Info

Publication number
JPH03191848A
JPH03191848A JP32966289A JP32966289A JPH03191848A JP H03191848 A JPH03191848 A JP H03191848A JP 32966289 A JP32966289 A JP 32966289A JP 32966289 A JP32966289 A JP 32966289A JP H03191848 A JPH03191848 A JP H03191848A
Authority
JP
Japan
Prior art keywords
pattern
particle aggregation
determined
reaction
aggregation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
JP32966289A
Other languages
Japanese (ja)
Inventor
Haruhisa Watanabe
晴久 渡辺
Tomohito Tanaka
智史 田中
Shinya Matsuyama
真也 松山
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Olympus Corp
Original Assignee
Olympus Optical Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Olympus Optical Co Ltd filed Critical Olympus Optical Co Ltd
Priority to JP32966289A priority Critical patent/JPH03191848A/en
Priority to DE19904040726 priority patent/DE4040726C2/en
Priority to DE4042523A priority patent/DE4042523C2/en
Publication of JPH03191848A publication Critical patent/JPH03191848A/en
Priority to US08/080,592 priority patent/US5389555A/en
Pending legal-status Critical Current

Links

Abstract

PURPOSE:To make it possible to perform accurate judgment by picking up the image of particle aggregation pattern in two dimensions, and judging the aggregated state and non-aggregated state based on the distributing state of the pattern. CONSTITUTION:A reaction container has the slant bottom surface at at least one part. Many conical wells as the reaction containers are formed in a matrix pattern in a microplate 1. A sample and a reagent are put in the microplate, and particle aggregation reaction is performed. The formed particle aggregation pattern is judged, and the aggregation reaction is measured. A lamp 2 as a light source is arranged at the lower side of the plate 1, and a TV camera 3 as an image sensor is arranged at the upper side. The image of the particle aggregation reaction pattern is picked up in two dimensions. The image data are amplified in a signal processing circuit 4 and converted into the digital signal. Then the signal is stored in a memory 5. The pattern is read out and displayed on the screen of a monitor 6. The differentiated value is obtained in a differentiating circuit 7 at the same time. The pattern is judged based on the distribution of the differentiated value in a judging circuit 8.

Description

【発明の詳細な説明】 (産業上の利用分野〕 本発明は少なくとも一部分に傾斜底面を有する反応容器
に検体と試薬とを入れて凝集反応を行わせ、この反応容
器の傾斜底面に形成される粒子凝集パターンを判定して
凝集反応を測定する方法に関するものである。
Detailed Description of the Invention (Industrial Field of Application) The present invention involves placing a sample and a reagent in a reaction container having at least a portion of an inclined bottom surface, causing an agglutination reaction to occur; The present invention relates to a method for determining a particle aggregation pattern and measuring an agglutination reaction.

〔従来の技術〕[Conventional technology]

円錐状の底面を有する反応容器または円錐状の底面を有
する多数のウェルを形成したマイクロプレートを用い、
この底面に形成される粒子凝集パターンを判定して凝集
の有無を判定する技術は既知であり、例えば米国特許第
4,727,033号明細書に開示されている。この既
知の粒子凝集パターン判定方法は、円錐状の底面の中央
部と周辺部とを格別の受光素子で受光し、これらの受光
素子の出力の比から凝集および非凝集を判定するように
している。すなわち、凝集の場合には凝集した粒子は底
面に均一に堆積するので中央部と周辺部とで受光素子の
出力の比は大きいが、非凝集の場合には多くの粒子は傾
斜した底面を転がり落ちて中央部に集まるので中央部と
周辺部とでは受光素子の出力に大きな差が生ずるので、
これらの受光素子の出力のは小さな値となる。このよう
に中央部と周辺部との受光素子からの出力の比から凝集
、非凝集を判定するものである。また、このような従来
の判定方法においては、前記の比の値を上下の限界値と
比較し、上限値よりも大きいときは凝集、下限値よりも
小さいときは非凝集と判断し、さらにこれらの限界値の
間の値のときには、判定不能若しくは不明と判定するよ
うにしている。
Using a reaction container with a conical bottom or a microplate with a large number of wells with a conical bottom,
A technique for determining the presence or absence of aggregation by determining the particle aggregation pattern formed on the bottom surface is known, and is disclosed, for example, in US Pat. No. 4,727,033. This known particle aggregation pattern determination method uses special light-receiving elements to receive light at the center and periphery of a conical bottom, and determines aggregation or non-aggregation from the ratio of the outputs of these light-receiving elements. . In other words, in the case of agglomeration, the agglomerated particles are deposited uniformly on the bottom surface, so the ratio of the output of the light-receiving element is large between the central part and the peripheral part, but in the case of non-aggregation, many particles roll on the inclined bottom surface. Since the light falls and gathers in the center, there is a large difference in the output of the light receiving element between the center and the periphery.
The output of these light receiving elements becomes a small value. In this way, aggregation or non-aggregation is determined from the ratio of the outputs from the light-receiving elements in the central part and the peripheral part. In addition, in such conventional determination methods, the value of the ratio is compared with upper and lower limit values, and when it is larger than the upper limit value, it is judged as agglomeration, and when it is smaller than the lower limit value, it is judged that there is no aggregation. When the value is between the limit values of , it is determined that the determination is impossible or unknown.

このような従来例をさらに発展させ、ウェル中心を通る
直線上を光検知器によって走査して一次元の画像信号を
得、この画像信号を処理して中央部と周辺部との差を求
めることも提案されている。
Further developing this conventional example, a photodetector scans a straight line passing through the center of the well to obtain a one-dimensional image signal, and this image signal is processed to determine the difference between the center and the periphery. has also been proposed.

また、特開昭63−58237号公報には、ウェルの底
面の像をテレビカメラによって撮像し、得られる画像信
号を処理してウェルの中心位置を求め、この中心位置を
中点とする円の円周に沿った画像信号の輝度差を求めて
凝集パターンの輪郭を求め、このようにして求めた輪郭
内の面積を求め、これを予め決めた基準値と比較し、基
準値よりも大きいときには凝集と判定し、小さいときに
は非凝集と判定する方法が開示されている。すなわち、
この従来の方法は、ウェルの中心に集められる粒子の個
数によって凝集および非凝集を判定するようにしている
In addition, Japanese Patent Application Laid-Open No. 63-58237 discloses that an image of the bottom surface of a well is taken with a television camera, the obtained image signal is processed to determine the center position of the well, and a circle with this center position as the midpoint is created. The contour of the agglomerated pattern is determined by determining the brightness difference of the image signal along the circumference, the area within the contour thus determined is determined, and this is compared with a predetermined reference value, and if it is larger than the reference value, A method is disclosed in which it is determined that the amount is agglomerated, and when it is small, it is determined that it is not agglomerated. That is,
This conventional method attempts to determine aggregation and non-aggregation by the number of particles collected in the center of the well.

また、特開昭63−256839号公報には、上記の方
法と同じようにしてウェルの中心位置を求め、粒子の集
まった中心部分の大きさとパターンの微分係数の標準偏
差との相関によって凝集、非凝集の判定を行う方法が開
示されている。
In addition, Japanese Patent Application Laid-Open No. 63-256839 discloses that the center position of the well is determined in the same manner as the above method, and the agglomeration is determined based on the correlation between the size of the central part where particles gather and the standard deviation of the differential coefficient of the pattern. A method for determining non-aggregation is disclosed.

[発明が解決しようとする課題] 上述した従来の粒子凝集パターンの判定方法では、凝集
および非凝集を明確に判定することができない欠点があ
る。すなわち、中心部と周辺部とを格別の受光素子で受
光し、これらの受光素子の出力の比から凝集、非凝集を
判定する方法では、不明と判定される検体が多くなる。
[Problems to be Solved by the Invention] The conventional method for determining particle aggregation patterns described above has the drawback that aggregation and non-aggregation cannot be clearly determined. That is, in a method in which light is received at the center and the periphery using special light-receiving elements, and agglutination or non-aggregation is determined based on the ratio of the outputs of these light-receiving elements, a large number of specimens are determined to be unknown.

一般に、凝集反応は微妙なものであり、はっきりとした
輪郭を有する粒子凝集パターンが形成されることは少な
く、したがって不明と判断されるものが比較的多く出現
することになる。このように不明と判定されたパターン
はオペレータが目視により観察して凝集、非凝集を判定
しているが、不明と判定されるものが多くなると目視観
察する必要のある検体数が多くなり、処理能率が低下す
る欠点があるとともに人的誤りも混入されることになり
、分析精度および信頼度が損なわれる欠点がある。また
、特開昭63−58237号公報に記載された方法では
、パターンの中心を正確に決定することができるが、パ
ターンの中心に粒子が集まって形成される凝集部分の大
きさが、凝集、非凝集だけによって決まらず、試薬や検
体の分注量によっても変化することになるため、正確な
判定が困難である。さらに、特開昭63−256839
号公報に記載された方法では、粒子凝集パターンに含ま
れる気泡、崩れ、めくれなどの影響を受は易く、正確な
判定を行うことができない欠点がある。
Generally, the aggregation reaction is subtle, and a particle aggregation pattern with a clear outline is rarely formed, so a relatively large number of particles that are judged to be unknown appear. Patterns that are determined to be unknown in this way are visually observed by operators to determine whether they are agglutinated or non-agglutinated, but as the number of patterns that are determined to be unknown increases, the number of samples that need to be visually observed increases, making processing difficult. There is a disadvantage that efficiency is reduced, and human error is also introduced, resulting in a disadvantage that analysis accuracy and reliability are impaired. Furthermore, although the method described in JP-A No. 63-58237 can accurately determine the center of a pattern, the size of the agglomerated area formed by particles gathering at the center of the pattern is Accurate determination is difficult because it is not determined only by non-aggregation, but also changes depending on the amount of reagent or sample dispensed. Furthermore, JP-A No. 63-256839
The method described in the above publication has the disadvantage that accurate determination cannot be made because it is easily affected by bubbles, collapse, and curling contained in the particle aggregation pattern.

本発明の目的は上述した従来の欠点を除去し、粒子凝集
パターンに含まれる崩れおよびめくれなどの形状異常や
気泡に影響されることなく、凝集、非凝集を正確に判定
することができ、その結果として目視観察を必要とする
検体数を減らして効率良く分析を行うことができる粒子
凝集パターン判定方法を提供しようとするものである。
The purpose of the present invention is to eliminate the above-mentioned conventional drawbacks, and to be able to accurately determine agglomeration or non-aggregation without being affected by shape abnormalities such as collapse and curling, or bubbles included in particle aggregation patterns. As a result, the present invention aims to provide a particle aggregation pattern determination method that can reduce the number of specimens that require visual observation and perform analysis efficiently.

〔課題を解決するための手段および作用〕本発明の粒子
凝集パターンの判定方法は、少なくとも一部分に傾斜底
面を有する反応容器に検体と試薬とを入れて粒子凝集反
応を行わせ、この反応容器の傾斜底面に形成される粒子
凝集パターンを判定して凝集反応を測定するに当たり、
反応容器の底面に形成された粒子凝集パターンを二次元
的に撮像して二次元画像情報を得る工程と、この二次元
画像情報を微分して微分値を求める工程と、この微分値
の分布に基づいて粒子凝集パターンを判定する工程とを
含むことを特徴とするものである。
[Means and effects for solving the problem] The method for determining a particle aggregation pattern of the present invention involves placing a sample and a reagent in a reaction container having at least a portion of an inclined bottom surface, allowing a particle agglutination reaction to take place; In determining the particle aggregation pattern formed on the inclined bottom surface and measuring the aggregation reaction,
A process of two-dimensionally imaging the particle aggregation pattern formed on the bottom of the reaction vessel to obtain two-dimensional image information, a process of differentiating this two-dimensional image information to obtain a differential value, and a process of determining the distribution of this differential value. and determining a particle aggregation pattern based on the method.

このような本発明の粒子凝集パターンの判定方法は、粒
子凝集パターンに気泡が含まれている場合、気泡の輪郭
部分の画像濃度が高くなり、崩れやめくれの部分では濃
度が低くなり、その下側で高くなるので、二次元画像信
号の微分値の分布状態からこれらの形状異常を判別する
ことができると言う事実を確かめ、この認識に基づいて
成したものである。したがって、本発明の方法によれば
粒子凝集パターンを気泡や崩れ、まくれ等に影響される
ことなく正確に判定することができ、したがって判定不
能とな−、て目視による再検査が必要となる検体数は少
なくなり、分析効率を向上することができる。また、従
来の判定方法と比べた場合、粒子凝集部分の面積のみの
情報で凝集、非凝集を判定しないので、検体や試薬の分
汀星の変動による判定誤差が4トづることもない。
In the particle aggregation pattern determination method of the present invention, when a particle aggregation pattern contains air bubbles, the image density is high at the outline of the air bubbles, and the image density is low at the collapsed or curled areas, and the image density below the bubbles is high. This was based on the fact that these shape abnormalities can be determined from the distribution state of the differential values of the two-dimensional image signal. Therefore, according to the method of the present invention, it is possible to accurately determine the particle aggregation pattern without being affected by bubbles, collapse, curling, etc., and therefore, it is possible to accurately determine the particle aggregation pattern for samples that cannot be determined and require visual re-examination. The number is reduced, and analysis efficiency can be improved. Furthermore, compared to conventional determination methods, since the method does not determine whether particles are agglomerated or non-agglutinated based only on the area of the agglomerated part, there is no error in determination due to fluctuations in the distribution of the sample or reagent.

[実施例] 第1図は本発明の粒子凝集パターンの判定方法を実施す
る装置の一例の全体の構成を示す線図である。本例では
、反応容器として多数のウェルをマトリックス状に形成
したマイクロプレート1を用いる。各ウェルの底面は円
錐状とする。また、マイクロブレー川・1はアクリル樹
脂のような透明な材料で形成1−る。マイクロプレー 
ト1は駆動テーブル(図示せず))、に乗せ、撮像光軸
に対して変位させるようにする。マイクロプレート1の
下側には、光源2を配置し、上方にはウェルの底面に形
成される粒子凝集パターンを二次元的に撮像することが
できる撮像装置3を配置する。本例では、ごの撮像装置
3はCCDテレビカメラを以て構成する。撮像装置3か
ら出力される二次元画像情報は信号処理回路4に供給し
て増幅U7、デジタル信号に変換した後、メモリ5に供
給し、ごこに記憶するように構成する。メモリ5に記憶
した画像情報を読み出してモニタ6に供給し、マイクロ
プレート1のウェルの底面に形成されている粒子凝集パ
ターンをスクリーン上に映出できるようにする。本発明
においては、メモリ5から読み出した二次元画像情報を
微分回路7に供給し、微分値を求める。この微分動作は
、微分オペレータを使用して以下に説明するように行う
。第2図および第3図は微分オペレータを示すもので、
第2図の微分オペレータは水平方向の輝度変化を検出(
〜、第3図に示す微分オペレータは垂直方向の輝度変化
を検出するものである。第4図6ご示ずように3×3の
大きさを有する画素領域を抽出し、以下に示す演算式に
基づいて各画素の輝度値に微分オペレータの係数を乗算
して加算することによりYlおよびY2を求め、さらに
これらの和の平均値を求めてこの値を画素領域の中心の
画素の微分値Yを求める。
[Example] FIG. 1 is a diagram showing the overall configuration of an example of an apparatus for implementing the particle aggregation pattern determination method of the present invention. In this example, a microplate 1 in which a large number of wells are formed in a matrix is used as a reaction container. The bottom of each well is conical. Further, the microbrake 1 is made of a transparent material such as acrylic resin. micro play
The lens 1 is placed on a drive table (not shown) and is displaced relative to the imaging optical axis. A light source 2 is disposed below the microplate 1, and an imaging device 3 capable of two-dimensionally capturing an image of a particle aggregation pattern formed on the bottom surface of the well is disposed above. In this example, the imaging device 3 includes a CCD television camera. The two-dimensional image information output from the imaging device 3 is supplied to the signal processing circuit 4, amplified by U7, and converted into a digital signal, and then supplied to the memory 5 and stored therein. The image information stored in the memory 5 is read out and supplied to the monitor 6 so that the particle aggregation pattern formed on the bottom surface of the well of the microplate 1 can be displayed on the screen. In the present invention, the two-dimensional image information read from the memory 5 is supplied to the differentiation circuit 7 to obtain a differential value. This differentiation operation is performed using a differentiation operator as described below. Figures 2 and 3 show the differential operator,
The differential operator in Figure 2 detects horizontal brightness changes (
~, The differential operator shown in FIG. 3 detects luminance changes in the vertical direction. As shown in Figure 4 and 6, a pixel area having a size of 3 x 3 is extracted, and the brightness value of each pixel is multiplied by the coefficient of the differential operator based on the calculation formula shown below and added. and Y2 are determined, and the average value of these sums is determined, and this value is used to determine the differential value Y of the pixel at the center of the pixel area.

Yl=(−1X八   十 (OXB  )  + (
IXC)+−(−2XD  + (OXE ) + (
2XF )+(−iXG  +(Ox)I)+(lxl
)Y 2 = (lXA  十(−2Xf+ ) +−
(−1XC)+ (OXD  + (OXE ”) +
(OXF ’)+(IXG)+(2XI+)+(IXT
)Y=Y1+Y2/2 画素領域を順次にずらしながら上記の演算を行って二次
元画像の全面に亘って微分値を求める。
Yl=(-1X80 (OXB) + (
IXC)+-(-2XD+(OXE)+(
2XF ) + (-iXG + (Ox)I) + (lxl
)Y 2 = (lXA 10(-2Xf+) +-
(-1XC) + (OXD + (OXE ”) +
(OXF')+(IXG)+(2XI+)+(IXT
)Y=Y1+Y2/2 The above calculation is performed while sequentially shifting the pixel areas to find the differential value over the entire surface of the two-dimensional image.

このようにして求めた二次元画像の微分値は判定回路8
に供給し、そこに設けたメモリに順次記憶する。本発明
においては、判定回路8において、上述したようにして
求めた微分値の分布から粒子凝集パターンの判定を行う
が、その判定基準の一例について第5図に示すフローチ
ャートをも参照して説明する。
The differential value of the two-dimensional image obtained in this way is determined by the judgment circuit 8.
and sequentially store it in the memory provided there. In the present invention, the determination circuit 8 determines the particle aggregation pattern from the distribution of the differential values obtained as described above, and an example of the determination criteria will be explained with reference to the flowchart shown in FIG. .

本発明においては、一つのウェルの底面に形成される粒
子凝集パターンについて微分値を求め、その分布から粒
子凝集パターンの判定を行うものである。
In the present invention, a differential value is obtained for a particle aggregation pattern formed on the bottom surface of one well, and the particle aggregation pattern is determined from the distribution.

(1)崩れ 微分値が20以上で40以下の値を持つ画素が2500
個以上ある場合には、粒子凝集パターンに崩れがあると
判定する。すなわち、粒子凝集パターンにめくれに近い
大きな崩れがあると、中程度の濃淡の変化がきわめて多
く現れる点に着目し、微分値が20〜40の画素の個数
を数え、その個数が2500以上の場合には粒子凝集パ
ターンに崩れがあると判定する。このような崩れが生ず
るのは凝集反応の場合であるから、崩れがあると判定さ
れた場合には凝集があると判断されるので、この場合に
は凝集反応であると判定する。
(1) 2500 pixels have a collapse differential value of 20 or more and 40 or less
If there are more than 1, it is determined that the particle aggregation pattern is disrupted. In other words, we focused on the fact that when a particle agglomeration pattern has a large collapse similar to turning over, a large number of moderate changes in shading appear, and we counted the number of pixels with a differential value of 20 to 40, and if the number was 2500 or more, It is determined that there is a collapse in the particle aggregation pattern. Since such collapse occurs in the case of an aggregation reaction, if it is determined that there is collapse, it is determined that there is aggregation, and in this case, it is determined that it is an aggregation reaction.

(2)気泡混入 微分値が200以上の値を持つ画素が10個よりも多い
ときは、粒子凝集パターンに気泡が混入していると判定
する。すなわち、粒子凝集パターンに気泡が入っている
と、濃淡の差がきわめて大きくなり、したがって大きな
微分値が多く現れる点に着目し、200以上の微分値を
有する画素が10個よりも多いときには気泡が混入して
いると判断する。
(2) When there are more than 10 pixels with a bubble inclusion differential value of 200 or more, it is determined that bubbles are included in the particle aggregation pattern. In other words, when there are bubbles in the particle aggregation pattern, the difference in density becomes extremely large, and therefore many large differential values appear. It is determined that it is mixed.

(3)凝集している(陽性) 微分値が20以上で50以下の画素数Aを、微分値が1
00以上で200以下の画素数Bで除した比R=A/B
の値が22以下であるときは、凝集していると判定する
(3) Agglomerated (positive) The number of pixels A with a differential value of 20 or more and 50 or less is
Ratio R = A/B divided by the number of pixels B that is greater than or equal to 00 and less than or equal to 200
When the value is 22 or less, it is determined that the particles are agglomerated.

(4)凝集していない(陰性) 前記の比Rの値が40以上のときは、非凝集であると判
定する。
(4) No agglutination (negative) When the value of the ratio R is 40 or more, it is determined that there is no agglutination.

(5)判定不能 前記の比Rの値が22より大きく、40より小さい場合
には、凝集でも非凝集でもないと判断し、判定不能とす
る。このように判定不能と判断されたサンプルについて
は、粒子凝集パターンを目視観察したり、再検査したり
する。
(5) Impossible to judge When the value of the ratio R is larger than 22 and smaller than 40, it is judged that the substance is neither agglomerated nor non-agglomerated, and it is judged that it cannot be judged. For samples determined to be undeterminable in this way, the particle aggregation pattern is visually observed or re-examined.

上述した判定において、気泡が混入していると判定され
た場合には、微分値が20〜50の画素数に1.2を乗
じたCと、微分値が100〜200の画素数に0.5を
乗じた値りとの比E=C/Dを求め、この比を上述した
判定基準(3)〜(5)の比Rの値として判定を行い、
凝集、非凝集および判定不能を判断する。このように、
20〜50の微分値を有する画素数に1.2を乗算し、
100〜200の微分値を有する画素数に0.5を乗算
することにより、小さな濃淡の変化を強調し、大きな濃
淡の変化を低減することになり、これによって気泡の影
響を少なくすることができる。
In the above-described determination, if it is determined that bubbles are mixed in, C is calculated by multiplying the number of pixels with a differential value of 20 to 50 by 1.2, and 0. Find the ratio E = C / D with the value multiplied by 5, and make a judgment using this ratio as the value of the ratio R of the above-mentioned judgment criteria (3) to (5),
Determine agglutination, non-aggregation, and indeterminable. in this way,
Multiply the number of pixels with a differential value of 20 to 50 by 1.2,
By multiplying the number of pixels with a differential value of 100 to 200 by 0.5, small changes in shading are emphasized and large changes in shading are reduced, thereby reducing the effect of bubbles. .

このようにして求めた判定結果をプリンタ等の出力装置
9へ供給して表示する。
The determination result obtained in this manner is supplied to an output device 9 such as a printer and displayed.

次に、種々のサンプルについて、粒子凝集パターンを二
次元的に撮像して得た画像信号の微分値を求め、その分
布を調べた結果を以下の表に示す。
Next, for various samples, the differential values of the image signals obtained by two-dimensionally imaging the particle aggregation patterns were obtained, and the distribution thereof was investigated. The results are shown in the table below.

上記の表には、各微分値範囲に属する画素数だけでなく
、微分値が200より大きい画素数、100〜200の
画素数、20〜40の画素数、20〜50の画素数、比
R1225以下の画素数、CおよびDの値、補正した比
Eの値、判定結果をも示す。サンプル1.6,7.8は
典型的な陰性パターンであり、サンプル13〜18は典
型的な陽性パターンである。
The table above includes not only the number of pixels belonging to each differential value range, but also the number of pixels with a differential value greater than 200, the number of pixels between 100 and 200, the number of pixels between 20 and 40, the number of pixels between 20 and 50, and the ratio R1225. The number of pixels, the values of C and D, the value of the corrected ratio E, and the determination results are also shown below. Samples 1.6 and 7.8 are typical negative patterns, and samples 13-18 are typical positive patterns.

また、サンプル9〜12はいずれも判定不能とされたも
のである。さらに、サンプル3および4は気泡があると
判定され、さらに補正された比Eの値からそれぞれ陰性
および陽性と判定されたものである。サンプル5は崩れ
と判定され、最終的に陽性と判断されたものである。こ
のように、本発明の方法によれば、気泡が混入していた
り、崩れがあるような場合でも凝集、非凝集を正確に判
定することができるとともに判定不能と判断されて目視
検査や再検査にまわされるサンプルの個数は少なくなり
、処理能力を向上することができる。
In addition, samples 9 to 12 were all determined to be undeterminable. Furthermore, samples 3 and 4 were determined to have air bubbles, and were further determined to be negative and positive, respectively, based on the corrected ratio E values. Sample 5 was determined to have collapsed and was ultimately determined to be positive. As described above, according to the method of the present invention, it is possible to accurately determine whether agglomeration or non-aggregation occurs even when air bubbles are mixed in or there is collapse, and even when it is determined that it cannot be determined, visual inspection or re-examination is required. The number of samples to be passed through is reduced, and processing capacity can be improved.

(発明の効果) 上述したように、本発明の判定方法によれば、反応容器
の傾斜底面に形成される粒子成果パターンを二次元的に
撮像し、得られる画像信号を微分し、その微分値の分布
を求め、この分布状態から凝集、非凝集を判断するよう
にしたため、粒子凝集パターンに気泡が混入していたり
、凝集パターンが崩れているような場合でも、凝集、非
凝集を正確に判定することができる。特に、粒子凝集パ
ターンに気泡が混入している場合には、これを補正した
値から凝集、非凝集を判定するようにしたため、判定不
能と判断されるサンプルは少なくなり、したがって目視
検査や再検査をしなければならないサンプルの数が減り
、処理能力を向上することができる。
(Effects of the Invention) As described above, according to the determination method of the present invention, the particle pattern formed on the inclined bottom of the reaction vessel is imaged two-dimensionally, the obtained image signal is differentiated, and the differential value is calculated. Since the distribution of particles is determined, and aggregation or non-aggregation is determined from this distribution state, it is possible to accurately determine agglomeration or non-aggregation even when air bubbles are mixed into the particle aggregation pattern or the aggregation pattern is disrupted. can do. In particular, when air bubbles are mixed into the particle aggregation pattern, aggregation or non-aggregation is determined based on the corrected value, which reduces the number of samples that are judged to be undeterminable, and therefore requires visual inspection or re-inspection. This reduces the number of samples that need to be processed and increases processing power.

【図面の簡単な説明】[Brief explanation of drawings]

第1図は本発明による粒子凝集パターンの判定方法を実
施する装置の構成を示すブロック図、第2図および第3
図は画像信号を微分するだめのオペレータを示す線図、 第4図は微分を行う際の画素領域を示す線図、第5図は
判定のフローチャートを示す図である。 1・・・マイクロプレート 4・・・信号処理回路 6・・・モニタ 8・・・判定回路 3・・・テレビカメラ 5・・・メモリ 7・・・微分回路 9・・・出力回路
FIG. 1 is a block diagram showing the configuration of an apparatus for implementing the particle aggregation pattern determination method according to the present invention, and FIGS.
FIG. 4 is a diagram showing the operator responsible for differentiating the image signal, FIG. 4 is a diagram showing the pixel area when performing differentiation, and FIG. 5 is a diagram showing a flowchart of determination. 1... Microplate 4... Signal processing circuit 6... Monitor 8... Judgment circuit 3... Television camera 5... Memory 7... Differentiating circuit 9... Output circuit

Claims (1)

【特許請求の範囲】 1、少なくとも一部分に傾斜底面を有する反応容器に検
体と試薬とを入れて凝集反応を行わせ、この反応容器の
傾斜底面に形成される粒子凝集パターンを判定して凝集
反応を測定するに当たり、 前記反応容器の傾斜底面に形成された粒子 凝集パターンを二次元的に撮像して二次元画像情報を得
る工程と、 この二次元画像情報を微分して微分値を求 める工程と、 この微分値の分布に基づいて粒子凝集パタ ーンを判定する工程とを含むことを特徴とする粒子凝集
パターンの判定方法。
[Claims] 1. A sample and a reagent are put into a reaction container having at least a portion of an inclined bottom surface to perform an agglutination reaction, and the agglutination reaction is performed by determining a particle aggregation pattern formed on the inclined bottom surface of the reaction container. In measuring, the step of two-dimensionally imaging the particle aggregation pattern formed on the inclined bottom surface of the reaction vessel to obtain two-dimensional image information, and the step of differentiating this two-dimensional image information to obtain a differential value. A method for determining a particle aggregation pattern, comprising: determining a particle aggregation pattern based on the distribution of the differential values.
JP32966289A 1989-12-21 1989-12-21 Method for judging particle aggregation pattern Pending JPH03191848A (en)

Priority Applications (4)

Application Number Priority Date Filing Date Title
JP32966289A JPH03191848A (en) 1989-12-21 1989-12-21 Method for judging particle aggregation pattern
DE19904040726 DE4040726C2 (en) 1989-12-21 1990-12-19 Methods for examining particle patterns
DE4042523A DE4042523C2 (en) 1989-12-21 1990-12-19 Investigation of particle patterns formed
US08/080,592 US5389555A (en) 1989-12-21 1993-06-24 Particle pattern judging method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP32966289A JPH03191848A (en) 1989-12-21 1989-12-21 Method for judging particle aggregation pattern

Publications (1)

Publication Number Publication Date
JPH03191848A true JPH03191848A (en) 1991-08-21

Family

ID=18223859

Family Applications (1)

Application Number Title Priority Date Filing Date
JP32966289A Pending JPH03191848A (en) 1989-12-21 1989-12-21 Method for judging particle aggregation pattern

Country Status (1)

Country Link
JP (1) JPH03191848A (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007507706A (en) * 2003-10-03 2007-03-29 カイロン ソチエタ ア レスポンサビリタ リミタータ Digital image of a simple radial immune diffusion assay
JP2009031191A (en) * 2007-07-30 2009-02-12 Yokohama National Univ Polymerization state determination device
JP2013185950A (en) * 2012-03-08 2013-09-19 Dainippon Screen Mfg Co Ltd Image evaluation method
WO2021186992A1 (en) * 2020-03-17 2021-09-23 オルガノ株式会社 Water treatment system, control device, water treatment method, and program

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007507706A (en) * 2003-10-03 2007-03-29 カイロン ソチエタ ア レスポンサビリタ リミタータ Digital image of a simple radial immune diffusion assay
JP2009031191A (en) * 2007-07-30 2009-02-12 Yokohama National Univ Polymerization state determination device
JP2013185950A (en) * 2012-03-08 2013-09-19 Dainippon Screen Mfg Co Ltd Image evaluation method
WO2021186992A1 (en) * 2020-03-17 2021-09-23 オルガノ株式会社 Water treatment system, control device, water treatment method, and program

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