JP2004313470A

JP2004313470A - Decayed teeth detector and decayed teeth detection program for realizing the same

Info

Publication number: JP2004313470A
Application number: JP2003111872A
Authority: JP
Inventors: Atsushi Yamagishi; 敦山岸
Original assignee: Kao Corp
Current assignee: Kao Corp
Priority date: 2003-04-16
Filing date: 2003-04-16
Publication date: 2004-11-11
Anticipated expiration: 2023-04-16
Also published as: JP4338425B2

Abstract

<P>PROBLEM TO BE SOLVED: To provide a decayed teeth detector and a decayed teeth detection program for realizing it which achieve the highly sensitive and accurate detection of the initial decayed teeth along with the detection of the degree of progress thereof. <P>SOLUTION: The decayed teeth detection system 1 is provided with an ultraviolet ray irradiator 2, a fluorescence detector 3, a fluorescence data analysis part 4 and a display device 5. The fluorescence data analysis part 4 has an internal memory 16 in which are stored extraction reference values M<SB>1</SB>, M<SB>2</SB>and M<SB>3</SB>serving as references when the fluorescence data are extracted in each of the regions equivalent to the wavelength of the visible light divided by 3. The extraction fluorescence data P<SB>1</SB>, P<SB>2</SB>and P<SB>3</SB>corresponding to the extraction reference values M<SB>1</SB>, M<SB>2</SB>and M<SB>3</SB>are extracted from the fluorescence data. One or two or more of the fluorescence data selected are computed to judge the decayed teeth based on the results of the computation. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

【０００１】
【発明の属する技術分野】
本発明は、虫歯を検出する技術に関し、特に、歯からの蛍光情報に基づいて非破壊的に初期段階の虫歯を検出する技術に関する。
【０００２】
【従来の技術】
光を用いて虫歯を検出する従来技術として、特許文献１に記載された装置がある。かかる装置は、赤色光（６００〜６７０ｎｍ）を励起光として歯に照射し、その歯からの蛍光をフォトダイオードにより受光した光の強度のみを測定するものである。また、前記装置は口腔内細菌由来の蛍光により虫歯を検出するものであるため、虫歯が進行し歯に穴が開いてしまい、その中に細菌が繁殖しているような場合には虫歯の検出が可能である。
【０００３】
しかしながら、初期虫歯の進行度合いは、必ずしも細菌の存在及びその量とは相関していない。特に初期虫歯の場合は、該当箇所に口腔用組成物内細菌が検出されないことがむしろ多いため、前記特許文献１に記載の装置でかかる初期虫歯を検出することは困難である。すなわち、このような蛍光情報によって解析した結果は、口腔内細菌の有無等によって左右されるため、初期虫歯の有無を正確に判断することが困難である。
【０００４】
上記特許文献１の問題を解決すべく、非特許文献１、２に記載されたＱＬＦ（ｑｕａｎｔｉｔａｔｉｖｅｌｉｇｈｔ−ｉｎｄｕｃｅｄｆｌｕｏｒｅｓｃｅｎｃｅ）方法及びこの方法を実現させた装置が開発されている。この装置は、３８０±７０ｎｍの紫外線で照射し、得られた５２０ｎｍ以上の蛍光の強さのみ検出するものであり、虫歯部位からの蛍光強度が歯の健常部位からの蛍光強度に比較して弱くなるという現象を利用して虫歯を検出するものである。この場合の虫歯検出は、細菌の存在に影響を受けないため、特許文献１に開示の装置と比較して虫歯の有無の検出をより正確にできるようになっている。しかし、後述の比較例２に示すとおり、実際のミネラル減少率の変化と上記５２０ｎｍ以上蛍光強度の変化とは一致しないため、初期虫歯の進行度合を計測することは困難である。
【０００５】
さらに、虫歯を検出する装置として、３６０〜５８０ｎｍの紫外線を歯に照射し、歯からの６２０ｍｎ以上の蛍光を測定する装置がある（特許文献２）。この装置は虫歯部位に特異的な赤色蛍光のみを測定対象とするものであり、特許文献１のように、口腔内細菌まで検出してしまうことはない。しかし、特許文献２に記載の装置は、蛍光強度の弱い赤色蛍光のみを測定対象とするため、虫歯の有無を検出するのに蛍光強度が不十分で外光などの計測環境の影響を受けやすく検出感度が低くなるという問題がある。
【０００６】
他方、虫歯の進行度合いを正確に検出し定量できる技術として、非特許文献３に記載された技術がある。この技術は、抜去した虫歯をスライスし、その断面をマイクロＸ線写真で撮影し、前記写真における情報に基づいて、健常歯と比較しつつ、ミネラル減少率を算出し、虫歯の進行状況を定量するものである。かかる方法は、確実に虫歯の進行状況を確認することが可能であるが、歯を抜去およびスライスしなければ、測定することができないという問題がある。
【０００７】
【特許文献１】
特開平２００１−２９９６９９号公報
【特許文献２】
欧州特許出願公開第０５５５６４５号明細書
【非特許文献１】
Ｓｔｏｏｋｅｙ，Ｇ．Ｋ．，ｅｔａｌ．Ｄｅｎｔａｌｃａｒｉｅｓｄｉａｇｎｏｓｉｓ，ＤｅｎｔＣｌｉｎＮｏｒｔｈＡｍ．，４３；６６５−７７，１９９９．
【非特許文献２】
ＳｈｉＸ．Ｑ，ｅｔａｌ．ＣｏｍｐａｒｉｓｏｎｏｆＱＬＦａｎｄＤＩＡＧＮＯｄｅｎｔｆｏｒｑｕａｎｔｉｆｉｃａｔｉｏｎｏｆｓｍｏｏｔｈｓｕｒｆａｃｅｃａｒｉｅｓ，ＣａｒｉｅｓＲｅｓ．，３５（１）：２１−６，２００１．
【非特許文献３】
好川正ら，「エナメル質の脱灰におよぼす０．１Ｍ乳酸のｐＨならびに作用時間の影響」，口腔衛生学会雑誌，１９９０，第４０巻，ｐ．６７１〜６７７
【０００８】
【発明が解決しようとする課題】
本発明の目的は、初期虫歯を感度良くかつ正確に検出し、虫歯の進行度合をも検出できる虫歯を検出する虫歯検出装置及びこれを実現する虫歯検出プログラムを提供することにある。
【０００９】
【課題を解決するための手段】
本発明者等は、歯に紫外光（水銀ランプのｉ線３６５ｎｍ）を照射した場合、健常歯については、４００〜５００ｎｍ付近（青色相当）に強い蛍光が生じるのに対し、虫歯については、４００〜５００ｎｍ付近の蛍光が弱くなり、その一方で、６００〜８００ｎｍ付近（赤色相当）に蛍光が生じることを知見した。
【００１０】
また、本発明者等は、紫外光の照射光強度を減少させた場合、虫歯については、青色相当及び赤色相当の蛍光が弱くなるのに対し、健常歯については、青色相当の蛍光が弱くなるものの、赤色相当の蛍光が強くなることを知見した。
【００１１】
本発明は、上記知見に基づいてなされたものであり、紫外線光源と、該紫外線光源から照射された紫外線により歯からの蛍光を受光する蛍光受光部と、該蛍光受光部から送信された蛍光データを解析する蛍光データ解析部と、該蛍光データ解析部により解析されたデータを表示するデータ表示部とを備えた虫歯検出装置であって、前記蛍光データ解析部は、可視光の波長を分割数ｎで分割した領域毎に前記蛍光データを抽出する場合に基準となる抽出基準値Ｍ_１、Ｍ_２、Ｍ_３、…Ｍ_ｎを記憶した記憶部を有し、前記蛍光データから前記抽出基準値Ｍ_１、Ｍ_２、Ｍ_３、…Ｍ_ｎのそれぞれに対応した抽出蛍光データＰ_１、Ｐ_２、Ｐ_３…Ｐ_ｎを抽出し、前記抽出蛍光データＰ_１、Ｐ_２、Ｐ_３…Ｐ_ｎから選択した１又は２以上の選択蛍光データを演算し、この演算結果に基づいて虫歯の判定を行うように構成された虫歯検出装置を提供することにより、前記目的を達成したものである。
【００１２】
本発明に係る虫歯検出装置及びこれを実現する虫歯検出プログラムにより、初期虫歯を感度よく検出することが出来るため、初期虫歯を削らずに非外科的な処置による治療がよりしやすくなる。さらに、本発明に係る虫歯検出装置は、虫歯の進行度合いも計測することができる。前記初期虫歯の治療経過の観察が可能になり、その回復の度合いの確認ができるため、患者に虫歯の進行状況や回復状況を具体的に示すことができる。さらに、虫歯予防処置の重要性や処置の効果に関する理解を得ることができ、口腔の健康の維持向上に貢献することが可能になる。
【００１３】
本発明に係る虫歯検出装置及びこれを実現する虫歯検出プログラムにより、歯の表面を計測することによって、虫歯を精度良く検出できるのみならず、歯の隙間等のような計測が困難な部位や（１カ所で計測）、歯の健常部位と虫歯部位との対比測定（２カ所で計測）をも行うことが可能である。また、これらの蛍光データを可視光領域の２以上の波長帯における蛍光強度に基づいて解析をすることにより、虫歯（特に初期虫歯）とその進行度合いを感度良く正確に検出することができる。
【００１４】
また、本発明に係る虫歯検出装置及びこれを実現する虫歯検出プログラムにより、紫外線の照射光強度の変化に伴って変化する歯からの蛍光データの中から、虫歯と健常歯とで異なる変化を示す波長帯を選択し、その波長帯における複数の蛍光強度に基づいて解析することができ、それによって虫歯（特に初期虫歯）とその進行度合いを感度良く正確に検出することができる。
【００１５】
本出願において、「抽出基準値」は、特定波長の蛍光データを抽出する際に、波長の上限値及び下限値を示すもので、可視光波長を分割数ｎで分割した場合、Ｍ_１、Ｍ_２、Ｍ_３…Ｍ_ｎとなる。虫歯度合ＣＤ_１（単一部位測定処理）を演算する場合には、抽出基準値Ｍ_１、Ｍ_２、Ｍ_３…Ｍ_ｎを用い、虫歯度合ＣＤ_２（対比測定処理）を演算する場合には、第１抽出基準Ｍ_１１、Ｍ_１２、Ｍ_１３…Ｍ_１ｎ、及び第２抽出基準Ｍ_２１、Ｍ_２２、Ｍ_２３…Ｍ_２ｎを用い、虫歯度合ＣＤ_３、ＣＤ_４（光強度変化測定処理）を演算する場合には、Ｒ抽出基準値Ｍ_Ｒ、Ｇ抽出基準値Ｍ_Ｇ、Ｂ抽出基準値Ｍ_Ｂを用いる。
【００１６】
第１抽出基準Ｍ_１１、Ｍ_１２、Ｍ_１３…Ｍ_１ｎ、及び第２抽出基準Ｍ_２１、Ｍ_２２、Ｍ_２３…Ｍ_２ｎは、互いに等しくても異なっていてもよく、それぞれ、抽出基準値Ｍ_１、Ｍ_２、Ｍ_３…Ｍ_ｎに対応するものである。
Ｒ抽出基準値Ｍ_Ｒは、赤色相当の波長のみならず、緑色相当の波長まで含めた、５５０〜８１０ｎｍの波長帯から選ばれる任意の波長幅を有するものである。Ｂ抽出基準値Ｍ_Ｂは、青色相当の波長のみならず、緑色相当の波長まで含めた、３８０〜５００ｎｍの波長帯から選ばれる任意の波長幅を有するものである。Ｇ抽出基準値Ｍ_Ｇは、緑色相当の波長のみならず、赤色相当の波長及び青色相当の波長まで含めた、４５０〜６５０ｎｍの波長帯から選ばれる任意の波長幅を有するものである。
【００１７】
上記Ｒ抽出基準値Ｍ_Ｒの波長幅は、０．１ｎｍ以上２６０ｎｍ以下の範囲から選ばれる１つ以上の任意の波長幅であって、好ましくは５０ｎｍ以上２６０ｎｍ以下の範囲から選ばれる１つ以上の任意の波長幅である。Ｂ抽出基準値Ｍ_Ｂの波長幅は、０．１ｎｍ以上１７０ｎｍ以下の範囲から選ばれる１つ以上の任意の波長幅であって、好ましくは５０ｎｍ以上２７０ｎｍ以下の範囲から選ばれる１つ以上の任意の波長幅である。Ｇ抽出基準値Ｍ_Ｇの波長幅は、０．１ｎｍ以上２００ｎｍ以下の範囲から選ばれる１つ以上の任意の波長幅であって、好ましくは５０ｎｍ以上２００ｎｍ以下の範囲から選ばれる１つ以上の任意の波長幅である。なお、前記波長幅の範囲内であれば、波長幅の個数は複数であってもよい。
【００１８】
【発明の実施の形態】
以下、本発明の虫歯検出装置及びこれを実現する虫歯検出プログラムの好ましい実施形態について図面を参照して説明する。
図１に示すように、本実施形態の虫歯検出システム（虫歯検出装置）１は、紫外線照射装置（紫外線光源）２と、紫外線照射装置２から照射された紫外線により歯からの蛍光を受光する蛍光受光装置（蛍光受光部）３と、蛍光受光装置３から送信されたデータを解析するデータ解析部４と、データ解析部４により解析された解析データを表示する表示装置（解析データ表示部）５とを備えている。
【００１９】
データ解析部４は、可視光の波長を分割数ｎで分割した領域毎に蛍光データを抽出する場合に基準となる抽出基準値Ｍ_１、Ｍ_２、Ｍ_３、…Ｍ_ｎを記憶した内部メモリ（記憶部）１６を有し、蛍光データから抽出基準値Ｍ_１、Ｍ_２、Ｍ_３、…Ｍ_ｎのそれぞれに対応した抽出蛍光データＰ_１、Ｐ_２、Ｐ_３…Ｐ_ｎを抽出し、抽出蛍光データＰ_１、Ｐ_２、Ｐ_３…Ｐ_ｎから選択した１又は２以上の選択蛍光データを演算し、この演算結果に基づいて虫歯の判定を行うように構成されている。なお、抽出蛍光データＰ_１、Ｐ_２、Ｐ_３…Ｐ_ｎは、それぞれ抽出基準値Ｍ_１、Ｍ_２、Ｍ_３、…Ｍ_ｎに対応する平均輝度値であってもよい。
まず、かかる虫歯検出システム１を詳細に述べる。
【００２０】
虫歯検出システム１は、このシステム全体を統括的に制御する主制御部１０（詳細後述）を有する。この主制御部１０には、入出力部１１を介して、紫外線照射装置２、及び蛍光受光装置３が接続されていると共に、記憶装置１２、表示装置５、及び出力装置１３が接続されている。
【００２１】
紫外線照射装置２は、波長が３００〜４００ｎｍ程度の紫外線を照射するもので、照射光強度が調整可能に構成されていればよい。このような紫外線照射装置２には、例えば、紫外線ＬＥＤ、水銀ランプ、メタルハライドランプ等がある。
紫外線ＬＥＤは、紫外線の照射光強度が調整されるように構成されている。例えば、通電量に関して入出力制御部１１ａで制御する、もしくは複数のＬＥＤの点灯個数を変えることにより、光の強度調整を行う。
【００２２】
水銀ランプ又はメタルハライドランプは、照射光が可視光カットフィルタを通過して紫外光になり、その紫外光の強度が調整できるようになっている。強度調整は例えば電流値の制御やＮＤフィルタを用いることにより行う。
そして、このような紫外線照射装置２から紫外線を導光するものとしては、紫外線吸収率が低いものであれば特に限定はないが、例えば石英ガラスや高分子材料からなるコアを有する光ファイバを通して歯に直接照射されるようになっている。
【００２３】
蛍光受光装置３は、紫外線の照射により歯からの蛍光が、紫外線カットフィルタ１４を通過することにより紫外線領域の光が吸収され、可視光領域の光のみが、光ファイバを通して光デバイスに受光されるように構成されている。
光デバイスは、可視光領域の蛍光から、色情報を含んだ情報を蛍光データとして取り込み、その情報を入出力部１１に送信可能なものであればよい。入出力部１１は、光デバイスからのアナログ情報をＡＤ変換器１１ｂによりデジタル値に変換するように構成されている。
【００２４】
上述の光デバイスには、例えば、分光輝度計等がある。
具体的には、分光輝度計は、蛍光をプリズム等により分光し、分光された光を光センサによって取り込むことにより、それぞれの情報を得るように構成されている。
記憶装置は、データ解析部４により解析された解析データを保存できるものであればよく、例えば、ハードディスク、フレキシブルディスク、光ディスク等がある。
【００２５】
表示装置５は、上記解析データや解析データの選択（測定部位の数、光強度の変化）に必要な情報を表示できるものであればよく、例えば、ＣＲＴディスプレイ、液晶ディスプレイ等がある。
出力装置１３は、上記解析データを出力できるものであればよく、例えば、プリンタ等がある。
【００２６】
主制御部１０は、ＣＰＵ１５及び内部メモリ１６を備えた蛍光データ解析部４等から構成されている。入出力部１１は、入出力制御部１１ａと、ＡＤ変換器１１ｂとから構成されている。
ＣＰＵ１５は、ＯＳ（ＯｐｅｒａｔｉｎｇＳｙｓｔｅｍ）等の制御プログラムや虫歯検出プログラムからの命令を解読して実行するように構成されている。
【００２７】
内部メモリ１６は、入出力制御部１１ａやＡＤ変換器１１ｂからの情報や、記憶装置１２からの解析データを一時的に保存するものである。
また、内部メモリ１６には、抽出基準値Ｍ_１、Ｍ_２、Ｍ_３…Ｍ_ｎ、第１抽出基準Ｍ_１１、Ｍ_１２、Ｍ_１３…Ｍ_１ｎ、第２抽出基準Ｍ_２１、Ｍ_２２、Ｍ_２３…Ｍ_２ｎ、Ｒ抽出基準値Ｍ_Ｒ、Ｇ抽出基準値Ｍ_Ｇ、Ｂ抽出基準値Ｍ_Ｂが記憶されている。
【００２８】
本実施形態では、可視光波長の分割数ｎを３とし、抽出基準値Ｍ_１は、波長が５５０〜８１０ｎｍの基準値である。第１抽出基準値Ｍ_１１、第２抽出基準Ｍ_２１、及びＲ抽出基準値Ｍ_Ｒは、すべて、抽出基準値Ｍ_１と等しいものとする。
【００２９】
また、抽出基準値Ｍ_２は、波長が４５０〜６５０ｎｍの基準値である。第１抽出基準値Ｍ_１２、第２抽出基準Ｍ_２２、及びＧ抽出基準値Ｍ_Ｇは、すべて、抽出基準値Ｍ_２と等しいものとする。
さらに、抽出基準値Ｍ_３は、波長が３８０〜５５０ｎｍの基準値である。第１抽出基準値Ｍ_１３、第２抽出基準Ｍ_２３、及びＢ抽出基準値Ｍ_Ｂは、すべて、抽出基準値Ｍ_３と等しいものとする。
【００３０】
蛍光データ解析部４は、虫歯検出プログラムがＣＰＵ１５により実行されることにより、虫歯検出プログラムと、ＣＰＵ１５、内部メモリ１６等のハードウエア資源とが協働した手段として構成されている。
【００３１】
そして、虫歯検出プログラムは、ＣＰＵ１５に実現させる機能として、測定部位数選択機能、光強度変化機能、データ取込機能、蛍光データ抽出・選択機能、虫歯度合演算機能、虫歯有無・進行度合判断機能等を有し、これらの機能により、上述した虫歯検出システム１が実現される。
【００３２】
次に、本実施形態の虫歯検出プログラムの処理を、図２〜図８を参照して説明する。
虫歯検出方法は、メイン処理（Ｓ１〜Ｓ３、Ｓ５）を共通にし、検出目的や検出方法の違いにより、単一部位測定処理（Ｓ４、Ｓ１１〜Ｓ１９）、対比測定処理（Ｓ２１〜Ｓ３０）、光強度変化測定処理（Ｓ３１〜Ｓ３５、Ｓ４１〜Ｓ４８、Ｓ５１〜Ｓ５８、Ｓ６１〜Ｓ６８）の３通りに大別される。
【００３３】
単一部位測定処理は、外から見える虫歯部位又は虫歯と疑われる部位や、特に歯の隙間や噛み合わせ等のような見えない虫歯部位の虫歯の有無又はその虫歯の進行度合を検出する処理で、虫歯部位と思われる１箇所を１回以上測定する。
対比測定処理は、外から見える虫歯部位又は虫歯と疑われる部位（単に「虫歯部位」とする）の虫歯の有無又はその虫歯の進行度合を検出する処理で、同一の歯における虫歯部位と健常部位の２箇所をそれぞれ独立して測定する。
光強度変化測定処理は、外から見えるか否かにかかわらず虫歯の有無及びその虫歯の進行度合の検出する処理で、紫外線の照射光強度を変化させつつ、虫歯部位と思われる同一箇所を複数回測定する。
【００３４】
具体的には、図２に示すように、ＣＰＵ１５が、測定するか否かを表示装置５に表示させ（Ｓ１）、測定する場合には、虫歯検出プログラムの測定部位数選択機能に基づき、測定部位の数が「１」であるか否かを表示させる（Ｓ２）。
測定部位の数が「１」でない場合には、「対比測定処理」に分岐し（分岐Ｂ、詳細後述）、測定部位の数が「１」である場合には、ＣＰＵ１５が、虫歯検出プログラムの光強度変化選択機能に基づき、光源の光強度を変化させるか否かを表示させる（Ｓ３）。
【００３５】
光源の光強度を変化させる場合には、「光強度変化測定処理」に分岐し（分岐Ｃ、詳細後述）、光源の光強度を変化させない場合には、ＣＰＵ１５が、「単一部位測定処理」を実行する。
【００３６】
ここで、単一部位測定処理においては、まず、測定者が、紫外線照射装置２を用いて、対象部位に照射し、蛍光受光装置３を用いて、歯からの蛍光より情報を得る。
次いで、ＣＰＵ１５が、虫歯検出プログラムのデータ取込機能に基づき、光デバイスからの蛍光データ（アナログ値）を、ＡＤ変換器１１ｂによりＡＤ変換されたデジタル信号として内部メモリ１６に取り込む。
【００３７】
そして、ＣＰＵ１５が、虫歯検出プログラムの蛍光データ抽出・選択機能に基づき、抽出基準値Ｍ_Ｒ、Ｍ_Ｇ、Ｍ_Ｂに対応させて、抽出蛍光データＰ_Ｒ、Ｐ_Ｇ、Ｐ_Ｂを抽出して内部メモリ１６に記憶し、さらに、選択蛍光データＰ_Ｒ、Ｐ_Ｂを選択して内部メモリ１６に記憶する（Ｓ４）。
【００３８】
ここに、抽出基準値Ｍ_Ｒは、可視光領域（３８０〜８１０ｎｍ）において、波長が、５５０〜８１０ｎｍであることが好ましく、より好ましくは、５８０〜６８０ｎｍである。
また、抽出基準値Ｍ_Ｂは、可視光領域において、波長が、３８０〜５５０ｎｍであることが好ましく、より好ましくは、４００〜５００ｎｍである。
さらに、抽出基準値Ｍ_Ｇは、可視光領域において、波長が、４５０〜６５０ｎｍであることが好ましく、より好ましくは、５００〜６００ｎｍである。
【００３９】
その後、図３に示すように、ＣＰＵ１５が、虫歯検出プログラムの虫歯度合演算機能に基づき、選択蛍光データＰ_Ｒ、Ｐ_Ｂのそれぞれの値を求め、その値を次の式（１）に従って虫歯度合ＣＤ_１を演算する（Ｓ１１）。
ＣＤ_１＝Ｐ_Ｒ／Ｐ_Ｂ…式（１）
この虫歯度合ＣＤ_１は、虫歯の進行に伴って、虫歯部位につき、蛍光データＰ_Ｒが増加する一方で、蛍光データＰ_Ｂ、蛍光データＰ_Ｇが減少するという特性を利用し、虫歯の進行度合を定量的な増加関数として表したものである。
【００４０】
ここでは、蛍光データＰ_Ｂの絶対的強度が蛍光データＰ_Ｇより大きいため、外光等の影響を受けにくくノイズが小さいため、虫歯度合ＣＤ_１をより高い精度で算出できる。
また、虫歯検出プログラムの蛍光データ抽出・選択機能に基づき、選択蛍光データＰ_Ｂの代わりに選択蛍光データＰ_Ｇを選択し、次の式（２）に従って虫歯度合ＣＤ_１を演算してもよい。
ＣＤ_１＝Ｐ_Ｒ／Ｐ_Ｇ…式（２）
【００４１】
Ｓ１２〜Ｓ１９の処理は、ＣＰＵ１５が虫歯検出プログラムの虫歯有無・進行度合判断機能に基づいて実行する処理である。
Ｓ１２では、虫歯度合ＣＤ_１を、下限しきい値Ｅ_１と比較する。ここに、「下限しきい値」とは、健常歯と虫歯（特に初期虫歯、以下同じ）とを判別するための値で、紫外線照射装置２における照射光強度、照射面積等の条件や、蛍光受光装置３における光路長、受光素子の感度等の条件によって異なり、虫歯検出システム１におけるキャリブレーションによって決定される。
【００４２】
虫歯度合ＣＤ_１が、下限しきい値Ｅ_１より小さい、又は下限しきい値Ｅ_１と等しい場合には、健常歯である旨（解析データ）を表示してメイン処理のＳ１に戻り（Ｓ１８、１９）、虫歯度合ＣＤ_１が下限しきい値Ｅ_１より大きい場合には、虫歯である旨（解析データ）を表示する（Ｓ１３）。
【００４３】
Ｓ１４では、虫歯度合ＣＤ_１を、上限しきい値Ｆ_１と比較する。ここに、「上限しきい値」とは、軽度の虫歯と重度の虫歯とを判別するための値で、上記下限しきい値と同様に決定される。
【００４４】
虫歯度合ＣＤ_１が上限しきい値Ｆ_１より小さい場合には、軽度の初期虫歯である旨（解析データ）を表示し（Ｓ１５）、虫歯度合ＣＤ_１が、上限しきい値Ｆ_１より大きい、又は下限しきい値Ｆ_１と等しい場合には、重度の初期虫歯である旨（解析データ）を表示し（Ｓ１６）、メイン処理のＳ１に戻る（Ｓ１７）。
【００４５】
上記Ｓ２において、測定部位の数が「１」でない場合には、ＣＰＵ１５が、「対比測定処理」を実行する。
ここで、対比測定処理においては、まず、測定者が、紫外線照射装置２を用いて、紫外線を、同一の歯において、虫歯部位（虫歯と疑われる部位）と、その近傍の健常部位とにそれぞれ照射し、蛍光受光装置３を用いて、虫歯部位の蛍光から第１情報の蛍光データを得ると共に、健常部位の蛍光から第２情報の蛍光データを得る。
【００４６】
次いで、図４に示すように、ＣＰＵ１５が、虫歯検出プログラムのデータ取込機能に基づき、光デバイスからの第１、第２情報の蛍光データを、それぞれ、ＡＤ変換器１１ｂによりＡＤ変換されたデジタル信号として内部メモリ１６に取り込む。
そして、ＣＰＵ１５が、虫歯検出プログラムの蛍光データ抽出・選択機能に基づき、第１抽出基準値Ｍ_１Ｒ、Ｍ_１Ｇ、Ｍ_１Ｂに対応させて、抽出蛍光データＰ_１Ｒ、Ｐ_１Ｇ、Ｐ_１Ｂを抽出して内部メモリ１６に記憶し、さらに、選択蛍光データＰ_１Ｒ、Ｐ_１Ｂを選択して内部メモリ１６に記憶する（Ｓ２１）。
同様に、ＣＰＵ１５が、第２抽出基準値Ｍ_２Ｒ、Ｍ_２Ｇ、Ｍ_２Ｂに対応させて、抽出蛍光データＰ_２Ｒ、Ｐ_２Ｇ、Ｐ_２Ｂを抽出して内部メモリ１６に記憶し、さらに、選択蛍光データＰ_２Ｒ、Ｐ_２Ｂを選択して内部メモリ１６に記憶する（Ｓ２１）。
【００４７】
その後、ＣＰＵ１５が、虫歯検出プログラムの虫歯度合演算機能に基づき、選択蛍光データＰ_１Ｒ、Ｐ_１Ｂ、Ｐ_２Ｒ、Ｐ_２Ｂのそれぞれの値を求め、その値を次の式（３）に従って虫歯度合ＣＤ_２を演算する（Ｓ２２）。
ＣＤ_２＝｜Ｐ_１Ｒ−Ｐ_２Ｒ｜×｜Ｐ_１Ｂ−Ｐ_２Ｂ｜…式（３）
【００４８】
蛍光データＰ_１Ｒ、Ｐ_１Ｇ、Ｐ_１Ｂ（虫歯部位）、及び蛍光データＰ_２Ｒ、Ｐ_２Ｇ、Ｐ_２Ｂ（健常部位）の大きさを、それぞれ、蛍光データＰ_Ｒ１、Ｐ_Ｇ１、Ｐ_Ｂ１、及び蛍光データＰ_Ｒ２、Ｐ_Ｇ２、Ｐ_Ｂ２で示した場合、この虫歯度合ＣＤ_２は、虫歯の進行に伴って、虫歯部位の蛍光データＰ_Ｒ１が健常部位の蛍光データＰ_Ｒ２より大きくなり、かつ、虫歯部位の蛍光データＰ_Ｂ１、Ｐ_Ｇ１が健常部位の蛍光データＰ_Ｂ２、Ｐ_Ｇ２より小さくなるという特性を利用し、虫歯の進行度合を定量的な増加関数として表したものである。
【００４９】
ここでは、蛍光データＰ_Ｂの絶対的強度が蛍光データＰ_Ｇより大きいため、外光等の影響を受けにくくノイズが小さいため、虫歯度合ＣＤ_１の精度を高める観点から、抽出蛍光データＰ_Ｇを用いていないが、虫歯検出プログラムの蛍光データ抽出・選択機能に基づき、選択蛍光データＰ_１Ｂ、Ｐ_２Ｂの代わりに選択蛍光データＰ_１Ｇ、Ｐ_２Ｇを選択し、次の式（４）に従って虫歯度合ＣＤ_２を演算してもよく、また、選択蛍光データＰ_１Ｂ、Ｐ_２Ｂ及び選択蛍光データＰ_１Ｇ、Ｐ_２Ｇの双方を選択し、次の式（４．１）に従って虫歯度合ＣＤ_２を演算してもよい。
ＣＤ_２＝｜Ｐ_１Ｒ−Ｐ_２Ｒ｜×｜Ｐ_１Ｇ−Ｐ_２Ｂ｜…式（４）
ＣＤ_２＝｜Ｐ_１Ｒ−Ｐ_２Ｒ｜×｛｜Ｐ_１Ｂ−Ｐ_２Ｂ｜＋｜Ｐ_１Ｇ−Ｐ_２Ｂ｜｝…式（４．１）
【００５０】
Ｓ２３〜Ｓ３０の処理は、ＣＰＵ１５が虫歯検出プログラムの虫歯有無・進行度合判断機能に基づいて実行する処理であり、上記Ｓ１２〜Ｓ１９の処理とほぼ同様である。
【００５１】
Ｓ２３では、虫歯度合ＣＤ_２を、下限しきい値Ｅ_２と比較する。
虫歯度合ＣＤ_２が、下限しきい値Ｅ_２より小さい、又は下限しきい値Ｅ_２と等しい場合には、健常歯である旨を表示してメイン処理のＳ１に戻り（Ｓ２９、Ｓ３０）、虫歯度合ＣＤ_２が下限しきい値Ｅ_２より大きい場合には、虫歯である旨を表示する（Ｓ２４）。
【００５２】
Ｓ２５では、虫歯度合ＣＤ_２を、上限しきい値Ｆ_２と比較する。
虫歯度合ＣＤ_２が上限しきい値Ｆ_２より小さい場合には、軽度の初期虫歯である旨を表示し（Ｓ２６）、虫歯度合ＣＤ_２が、上限しきい値Ｆ_２より大きい、又は上限しきい値Ｆ_２と等しい場合には、重度の初期虫歯である旨を表示し（Ｓ２７）、メイン処理のＳ１に戻る（Ｓ２８）。
【００５３】
上記Ｓ３において、光源の光強度を変化させる場合には、ＣＰＵ１５が、「光強度変化測定処理」を実行する。
ここで、光強度変化測定処理においては、まず、測定者が、紫外線照射装置２を用いて、光強度Ｕ_１、Ｕ_２（Ｕ_１＞Ｕ_２）を変化させた紫外線を、同一歯の同一部位にそれぞれ照射し、蛍光受光装置３を用いて、光強度Ｕ_１についての蛍光から第１情報の蛍光データを得ると共に、光強度Ｕ_２についての蛍光から第２情報の蛍光データを得る。
【００５４】
次いで、図５に示すように、ＣＰＵ１５が、虫歯検出プログラムのデータ取込機能に基づき、光デバイスからの第１、第２情報の蛍光データを、それぞれ、ＡＤ変換器１１ｂによりＡＤ変換されたデジタル信号として内部メモリ１６に取り込む。
【００５５】
そして、ＣＰＵ１５が、虫歯検出プログラムの蛍光データ抽出・選択機能に基づき、Ｒ、Ｇ、Ｂ抽出基準値Ｍ_Ｒ、Ｍ_Ｇ、Ｍ_Ｂに対応させて、第１情報の蛍光データから抽出蛍光データＰ_１Ｒ、Ｐ_１Ｇ、Ｐ_１Ｂを抽出して内部メモリ１６に記憶し、さらに、選択蛍光データＰ_１Ｒ、Ｐ_１Ｂを選択して内部メモリ１６に記憶する（Ｓ３１）。
【００５６】
同様に、ＣＰＵ１５が、Ｒ、Ｇ、Ｂ抽出基準値Ｍ_Ｒ、Ｍ_Ｇ、Ｍ_Ｂに対応させて、第２情報の蛍光データから抽出蛍光データＰ_２Ｒ、Ｐ_２Ｇ、Ｐ_２Ｂを抽出して内部メモリ１６に記憶し、さらに、選択蛍光データＰ_２Ｒ、Ｐ_２Ｂを選択して内部メモリ１６に記憶する（Ｓ３２）。
なお、光強度は２つに限定されるものではなく、３つ以上であってもよい。
【００５７】
その後、ＣＰＵ１５が、虫歯検出プログラムの虫歯有無・進行度合判断機能に基づき、光強度Ｕ_１の選択蛍光データＰ_１Ｒと、光強度Ｕ_２の選択蛍光データＰ_２Ｒとの大小関係、すなわち、次の式（５）の符号が「正（＋）」であるか否かを判断し（Ｓ３３）、「正（＋）」の場合には、虫歯の可能性がある旨を表示し（Ｓ３４）、「負（−）」の場合には、健常歯である旨を表示してメイン処理のＳ１に戻る（Ｓ３５）。
（Ｐ_１Ｒ―Ｐ_２Ｒ）…式（５）
【００５８】
なお、判別方法はこれに限らず、複数の抽出蛍光データＰ_１Ｒ、Ｐ_２Ｒ…と光強度Ｕ_１、Ｕ_２との相関関係を求め、その相関が「正」である場合は虫歯、「負」である場合は健常と判断する方法を用いてもよい。
【００５９】
Ｓ３３〜Ｓ３５の処理は、虫歯部位については、蛍光データＰ_２Ｒが蛍光データＰ_１Ｒより小さくなる（紫外線照射強度に正の相関）のに対し、健常部位については、蛍光データＰ_２Ｒが蛍光データＰ_１Ｒより大きくなる（紫外線照射強度に負の相関）という特性を利用し、虫歯の進行度合を判断する前に、虫歯の有無を判断したものである。
【００６０】
Ｓ３４に進んだ後の処理は、虫歯度合の演算処理の違いにより、虫歯度合ＣＤ_３１の処理（分岐Ｄ_１、Ｓ４１〜Ｓ４８）、虫歯度合ＣＤ_３２の処理（分岐Ｄ_２、Ｓ５１〜Ｓ５８）、虫歯度合ＣＤ_４の処理（分岐Ｄ_３、Ｓ６１〜Ｓ６８）の３つに分岐する。
【００６１】
図６に示すように、虫歯度合ＣＤ_３１の処理においては、ＣＰＵ１５が、虫歯検出プログラムの虫歯度合演算機能に基づき、光強度Ｕ_１の選択蛍光データＰ_１Ｒ、Ｐ_１Ｂ、及び光強度Ｕ_２の選択蛍光データＰ_２Ｒ、Ｐ_２Ｂのそれぞれの値を求め、その値を次の式（６）に従って虫歯度合ＣＤ_３１を演算する（Ｓ４１）。
ＣＤ_３１＝（Ｐ_１Ｒ／Ｐ_２Ｒ）×（Ｐ_１Ｂ／Ｐ_２Ｂ）…式（６）
【００６２】
この虫歯度合ＣＤ_３１は、虫歯部位については、蛍光データＰ_２Ｒ、Ｐ_２Ｇ、Ｐ_２Ｂが、それぞれ、蛍光データＰ_１Ｒ、Ｐ_１Ｇ、Ｐ_１Ｂより小さくなるのに対し、健常部位については、Ｐ_Ｂ２、Ｐ_Ｇ２が、それぞれ、Ｐ_Ｂ１、Ｐ_Ｇ１より小さくなるものの、Ｐ_Ｒ２がＰ_Ｒ１より大きくなるという特性を利用し、虫歯の進行度合を関数として表したものである。
【００６３】
Ｓ４２〜Ｓ４８の処理は、ＣＰＵ１５が虫歯検出プログラムの虫歯有無・進行度合判断機能に基づいて実行する処理であり、上記Ｓ２３〜Ｓ３０の処理とほぼ同様である。
Ｓ４２では、虫歯度合ＣＤ_３１を、上限しきい値Ｆ_３１と比較する。虫歯度合ＣＤ_３１が、上限しきい値Ｆ_３１より大きい、又は上限しきい値Ｆ_３１と等しい場合には、健常歯である旨を表示してメイン処理のＳ１に戻り（Ｓ４７、４８）、虫歯度合ＣＤ_３１が、上限しきい値Ｆ_３１より小さい場合には、Ｓ４３に進む。
【００６４】
Ｓ４３では、虫歯度合ＣＤ_３１を、下限しきい値Ｅ_３１と比較する。虫歯度合ＣＤ_３１が下限しきい値Ｅ_３１より大きい場合には、軽度の初期虫歯である旨を表示し（Ｓ４４）、虫歯度合ＣＤ_３１が、下限しきい値Ｅ_３１より大きい、又は下限しきい値Ｅ_３１と等しい場合には、重度の初期虫歯である旨を表示し（Ｓ４５）、メイン処理のＳ１に戻る（Ｓ４６）。
【００６５】
図７に示すように、虫歯度合ＣＤ_３２の処理においては、虫歯検出プログラムの蛍光データ抽出・選択機能に基づき、選択蛍光データＰ_１Ｂ、Ｐ_２Ｂの代わりに選択蛍光データＰ_１Ｇ、Ｐ_２Ｇを選択し、上記虫歯度合ＣＤ_３１の処理の比較した場合、Ｓ５１、Ｓ５２、Ｓ５３の処理のみが異なる。
【００６６】
Ｓ５１では、光強度Ｕ_１の選択蛍光データＰ_１Ｒ、Ｐ_１Ｇ、及び光強度Ｕ_２の選択蛍光データＰ_２Ｒ、Ｐ_２Ｇそれぞれの値を求め、その値を次の式（７）に従って虫歯度合ＣＤ_３２を演算する。
ＣＤ_３２＝（Ｐ_１Ｒ／Ｐ_２Ｒ）×（Ｐ_１Ｇ／Ｐ_２Ｇ）…式（７）
Ｓ５２では、上限しきい値Ｆ_３２の設定の仕方が異なり、Ｓ５３では、下限しきい値Ｅ_３２の設定の仕方が異なる。
その他の処理は、上記同様であるので説明を省略する。
【００６７】
図８に示すように、虫歯度合ＣＤ_４の処理においては、虫歯検出プログラムの蛍光データ抽出・選択機能に基づき、選択蛍光データＰ_１Ｂ、Ｐ_２Ｂ、Ｐ_１Ｇ、Ｐ_２Ｇを選択し、上記虫歯度合ＣＤ_３１の処理の比較した場合、Ｓ６１、Ｓ６２、Ｓ６３の処理のみが異なる。
【００６８】
Ｓ６１では、光強度Ｕ_１の選択蛍光データＰ_１Ｒ、Ｐ_１Ｇ、Ｐ_１Ｂ、及び光強度Ｕ_２の選択蛍光データＰ_２Ｒ、Ｐ_２Ｇ、Ｐ_２Ｂのそれぞれの値を求め、その値を次の式（８）に従って虫歯度合ＣＤ_４を演算する。
ＣＤ_４＝（Ｐ_１Ｒ／Ｐ_２Ｒ）×｛（Ｐ_１Ｇ／Ｐ_２Ｇ）＋（Ｐ_１Ｂ／Ｐ_２Ｂ）｝…式（８）
Ｓ６２では、上限しきい値Ｆ_４の設定の仕方が異なり、Ｓ６３では、下限しきい値Ｅ_４の設定の仕方が異なる。その他の処理は、上記同様であるので説明を省略する。
【００６９】
このような光強度変化測定処理においては、図示しないが、上記虫歯度合ＣＤ_３１、ＣＤ_３２、ＣＤ_４のほか、次の式（９）に従って虫歯度合ＣＤ_５を演算してもよい。
ＣＤ_５＝（Ｐ_１Ｒ／Ｐ_２Ｒ）×（Ｐ_１Ｇ／Ｐ_２Ｇ）×（Ｐ_１Ｇ／Ｐ_２Ｇ）…式（９）
【００７０】
以上述べたように、本実施形態によれば、虫歯検出方法において、虫歯度合ＣＤを、エネルギ値の高低にわたる選択蛍光データＰ_Ｒ、Ｐ_Ｂ、Ｐ_Ｇに基づいて定量的な関数で表し、その虫歯度合ＣＤを下限しきい値Ｅ及び上限しきい値Ｆと比較することにより、細菌の侵襲を受けていない初期段階の虫歯について、「健常歯」、「軽度の虫歯」又は「重度の虫歯」の何れであるかの判断を感度よく正確に行うことができる。
【００７１】
また、本実施形態によれば、虫歯検出方法を、１カ所から得られるデータを用いた測定処理、２カ所から得られるデータを対比する測定処理、光強度を変化させる測定処理の３つに大別できる、これらの方法を検出目的、計測部位により使い分ける、組み合わせることを可能にすることにより、効率的に精度良く虫歯の有無や虫歯の進行度合を検出できる。
【００７２】
すなわち、１カ所から得られるデータを用いた測定処理にあっては、見えている部分のみならず歯の隙間や噛み合わせ等のような比較部位の得られにくい部位に用いることができ、その１箇所を測定するだけで、虫歯の有無や進行度合を検出できる。この測定方法は、得られた虫歯度合ＣＤ_１に基づいて虫歯の検出を瞬時に行える方法としてあらゆる部位の測定に有利である。
【００７３】
また、２カ所から得られるデータを対比する測定処理にあっては、見えている虫歯部位又は虫歯と疑われる部位について、健常部位との比較において、２箇所測定することにより、虫歯の有無や進行度合を検出できる。この測定処理は、虫歯部位と健常部位との比較を考慮に入れた虫歯度合ＣＤ_２のみに基づいて瞬時に虫歯の進行度合を検出できる点で有利である。
【００７４】
さらに、光強度変化測定処理にあっては、紫外線の光強度を変化させつつ、同一の虫歯部位について、少なくとも２回測定することにより、虫歯の進行度合を検出できる。この測定処理は、光強度の異なる選択蛍光データＰ_１Ｒ、Ｐ_２Ｒの大小を比較するだけで虫歯の有無を瞬時に判断できる点や、光強度の変化により歯の深度に応じた、虫歯の進行度合を得られる点で有利である。
【００７５】
さらに、本実施形態によれば、虫歯検出プログラムを実行することにより、上記効果を奏する虫歯検出システム１を実現することができる。
特に、抽出基準値Ｍ_Ｒ、Ｍ_Ｇ、Ｍ_Ｂ等を用いて、蛍光データＰ_Ｒ、Ｐ_Ｇ、Ｐ_Ｂを選択・抽出するようにしたため、受光蛍光装置３により蛍光データの取り込みを１回行うだけで、種々の虫歯度合ＣＤを演算することができる。
また、抽出基準値Ｍ_Ｒ、Ｍ_Ｇ、Ｍ_Ｂ等の設定値を変更するだけで、外光等やノイズの影響に適宜対応して虫歯度合ＣＤの精度を高めることができる。
【００７６】
本発明は、上記実施形態に限られることなく、種々の変更を行うことができる。
例えば、上記光強度測定方法においては、光強度を２種に変化させたが、これに限られず、光強度を３種以上に変化させ、虫歯度合ＣＤ_３１、ＣＤ_３２、ＣＤ_４を演算してもよい。
また、虫歯度合ＣＤ_３１、ＣＤ_３２、ＣＤ_４を演算するにあたって、光強度の異なる蛍光データの比（Ｐ_１Ｒ／Ｐ_２Ｒ）等を用いたが、この代わりに、蛍光データの変化の傾きや相関関係を用いることもできる。
【００７７】
さらに、虫歯度合ＣＤと、下限しきい値Ｅ及び上限しきい値Ｆとの比較のほか、さらに、別のしきい値を加えることにより、重度と軽度との中間的な程度の中等度を示すこともできる。さらにまた、表示装置５に解析データとして、健常歯である旨等のデータのほか、虫歯度合ＣＤ自体を表示してもよく、このような解析データを出力装置１３に出力してもよい。
【００７８】
さらにまた、抽出基準値Ｍ_Ｒ、Ｍ_Ｇ、Ｍ_Ｂ等を、内部メモリ１６に記憶せずに、直接、虫歯検出プログラムに書き込んでもよい。
【００７９】
【実施例】
本発明者等は、現在のところ最も正確に虫歯の進行度合いを測定できる非特許文献３記載の方法と実施例１〜４と比較例１、２との相関関係を求めることにより本発明に係る虫歯検出装置の検出精度を評価した。
【００８０】
実験に用いた抜去歯は、表層が脱落してなく非外科的処置で回復可能な初期虫歯であるものを選んだ。これらの抜去歯は経験を積んだ歯科医師の目視により、ごく初期のもの（軽度）、ある程度進んだもの（中等度）、穴のあく寸前のもの（重度）の３種類に分類した。
【００８１】
分類した抜去歯をまず本発明に係る虫歯検出装置で計測した。その後、非特許文献３に記載の方法に基づき、前記の抜去歯をスライスし、マイクロＸ線写真撮影用の試料を作成した。実施例において、本発明に係る虫歯検出装置での計測結果と非特許文献３で示した方法で得られたミネラル減少率との相関係数を求めることにより本発明の虫歯検出装置の正確さを検証した。
【００８２】
ミネラル減少率とは、虫歯の進行度合を示すもので、上記非特許文献３に従い、マイクロＸ線写真を用いて、表面から深さ３００ミクロンまでの部位についてコンピュータ画像解析により得られた値であり、健常部位のミネラル減少率を０％とし、溶けて歯のすべてが無くなった場合はミネラル減少率を１００％とする。
【００８３】
本実施例で用いた虫歯検出システム１及びこれを用いた虫歯検出方法について説明する。紫外線照射装置２として水銀ランプを用いた。この水銀ランプは、４００ｎｍ以下の波長の紫外線を透過する可視光カットフィルタの装着により、ｉ線を効率よく照射できるようにした。また、水銀ランプは、ＮＤフィルタの装着により、光強度をＵ_１（＝３４０ｍＶ／ｃｍ^２）、Ｕ_２（＝９４ｍＶ／ｃｍ^２）の２段階に変化できるようにした。水銀ランプからの紫外線は、光ファイバにより直接歯に照射した。
【００８４】
蛍光受光装置３として分光輝度計を用いた。分光輝度計は、４００ｎｍ以上の光を透過するＵＶカットフィルタを装着し、可視光領域の蛍光データを取り込めるようにした。取り込んだ蛍光データはＡ／Ｄ変換を行い、１６ｂｉｔのスペクトルデータとして蛍光データ解析部に転送した。抽出基準値Ｍ_Ｒを６００〜８００ｎｍ、抽出基準値Ｍ_Ｇを５００〜６００ｎｍ、抽出基準値Ｍ_Ｂを４００〜５００ｎｍとし、それぞれに対応した蛍光データＰ_Ｒ、Ｐ_Ｇ、Ｐ_Ｂを抽出した。
【００８５】
歯の測定部位及び光強度Ｕ_１、Ｕ_２を変化させた測定について説明する。
虫歯部位について、軽度部位Ｌ、中等度部位Ｍ、重度部位Ｈの３箇所を測定の対象にすると共に、それぞれの近傍（同一歯の中）にある健常部位について、健常部位（軽）Ｌ’、健常部位（中）Ｍ’、健常部位（重）Ｈ’の３箇所を測定の対象とした。
【００８６】
それぞれの測定部位について、光強度Ｕ_１と、光強度Ｕ_２とに対応して、測定部位の記号に添字「１」、「２」を付す。例えば、「Ｌ_１」は、光強度Ｕ_１の紫外線を照射した、虫歯の軽度部位についての測定部位を示し、「Ｈ_２、１」は、光強度Ｕ_１、Ｕ_２の紫外線をそれぞれ照射した、虫歯の重度部位についての測定部位を示す。
本実施例において計測した、各測定部位毎の光強度Ｕ_１、Ｕ_２と蛍光データＰ_Ｒ、Ｐ_Ｂ、Ｐ_Ｇとの関係を図９に示し、光強度Ｕ_１、Ｕ_２、Ｐ_Ｒ、Ｐ_Ｂ、Ｐ_Ｇのデータ（最大２^１６＝６５５３６）を表１、表２、表３に示した。
【００８７】
【表１】

【００８８】
【表２】

【００８９】
【表３】

【００９０】
［実施例１］
実施例１では、上記実施形態で示した虫歯検出処理の「単一部位測定処理」に従い、光強度Ｕ_１の測定部位Ｌ_１、Ｍ_１、Ｈ_１、Ｌ_１’、Ｍ_１’、Ｈ_１’について、それぞれ、虫歯度合ＣＤ_１を算出し、虫歯度合ＣＤ_１とミネラル減少率とのそれぞれの相関係数を求めた。
【００９１】
［比較例１］
比較例１では、上記特許文献２に記載の技術に従い、紫外線の光強度をＵ_１にし、測定部位Ｌ_１、Ｍ_１、Ｈ_１、Ｌ_１’、Ｍ_１’、Ｈ_１’について計測した。カラーＣＣＤに、６２０ｎｍ以上の光を透過するカットフィルタを装着し、カラーＣＣＤが赤色蛍光のみの画像を取り込めるようにした。この画像をグレー画像に変換し、各測定部位毎にＰ_Ｒ（１６ｂｉｔ）を得た。Ｐ_Ｒとミネラル減少率とのそれぞれの相関係数を求めた。実施例１と比較例１の計測結果を表４に示す。
【００９２】
【表４】

【００９３】
表４に示したように、ミネラル減少率が高い場合は虫歯が進行していることを意味している。本発明に係る実施例１の虫歯度合ＣＤ_１とミネラル減少率との相関係数が高く、虫歯度合ＣＤ_１は、虫歯の進行度合を客観的に定量値することができることが実証された。
【００９４】
虫歯の進行度合いを的確に捉えるためには、ミネラル減少率の値に応じて、蛍光データＰ_Ｒも高くならなければならない。しかし、これに対し比較例１の場合は、虫歯の中等度部位Ｍ_１と重度部位Ｈ_１の間で、蛍光データＰ_Ｒの大小関係が逆転しており、必ずしも虫歯の進行度合とは一致していないため、虫歯の進行度合いの検出は困難である。
【００９５】
［実施例２］
実施例２では、上記実施形態で示した虫歯検出処理の「対比測定処理」に従い、光強度Ｕ_１の測定部位（Ｌ_１、Ｌ_１’）、（Ｍ_１、Ｍ_１’）、（Ｈ_１、Ｈ_１’）について、それぞれ、虫歯度合ＣＤ_２を算出し、虫歯度合ＣＤ_２とミネラル減少率とのそれぞれの相関係数を求めた。
【００９６】
［比較例２］
比較例２では、上記特許文献１で示した従来技術に従い、紫外線の光強度をＵ_１にし、測定部位（Ｌ_１、Ｌ_１’）、（Ｍ_１、Ｍ_１’）、（Ｈ_１、Ｈ_１’）について計測した。カラーＣＣＤに、５２０ｎｍ以上の光を透過するカットフィルタを装着し、カラーＣＣＤが５２０〜８００ｎｍの画像を取り込めるようにした。この画像をグレー画像に変換し、各測定部位毎に、虫歯部位の輝度（１６ｂｉｔ）と、健常部位の輝度（１６ｂｉｔ）とを求め、その比を相対輝度として算出した。相対輝度とミネラル減少率とのそれぞれの相関係数を求めた。実施例２と比較例２の計測結果を表５に示す。
【００９７】
【表５】

【００９８】
表５から、虫歯度合ＣＤ_２とミネラル減少率との相関係数が高く、虫歯度合ＣＤ_２は、虫歯の進行度合について客観的な定量値で示すことができることが実証された。その一方、虫歯の中等度部位（Ｍ_１、Ｍ_１’）と重度部位（Ｈ_１、Ｈ_１’）の間で、相対輝度の大小関係が逆転しており、単色光の輝度のみでは、必ずしも虫歯の進行度合とは一致していないため、虫歯の進行度合いの検出は困難である。
【００９９】
［実施例３］
実施例３では、上記実施形態で示した虫歯検出処理の「光強度変化測定処理」に従い、光強度Ｕ_１、Ｕ_２の測定部位Ｌ２、_１、Ｍ２、_１、Ｈ２、_１、Ｌ２、_１’、Ｍ２、_１’、Ｈ２、_１’について、それぞれ、輝度変化（Ｐ_Ｒ１―Ｐ_Ｒ２）、（Ｐ_Ｇ１―Ｐ_Ｇ２）、（Ｐ_Ｂ１―Ｐ_Ｂ２）と、虫歯度合ＣＤ_３１、ＣＤ_３２とを演算し、虫歯度合ＣＤ_３１、ＣＤ_３２とミネラル減少率とのそれぞれの相関係数を求めた。実施例３の計測結果を表６、表７に示す。
【０１００】
【表６】

【０１０１】
【表７】

【０１０２】
表６から、輝度変化（Ｐ_Ｒ１―Ｐ_Ｒ２）の符号は、虫歯の有無を示す客観的な判断基準であることが明らかになった。また、表７から、虫歯度合ＣＤ_３１、ＣＤ_３２とミネラル減少率との相関係数が高く、虫歯度合ＣＤ_３１、ＣＤ_３２は、虫歯の進行度合について客観的な定量値で示すことができることが実証された。
【０１０３】
［実施例４］
実施例４では、上記実施例３と同様に、虫歯度合ＣＤ_４、ＣＤ_５とを演算し、虫歯度合ＣＤ_４、ＣＤ_５とミネラル減少率とのそれぞれの相関係数を求めた。
上記虫歯度合ＣＤ_３１、ＣＤ_３２が、選択蛍光データＰ_Ｒと、選択蛍光データＰ_Ｂ、選択蛍光データＰ_Ｇの何れか一方との二者を演算対象にしているのに対し、虫歯度合ＣＤ_４、ＣＤ_５は、蛍光データＰ_Ｒ、Ｐ_Ｂ、Ｐ_Ｇの三者を演算対象にしている点が異なる。実施例４の計測結果を表８に示す。
【０１０４】
【表８】

【０１０５】
表８から、虫歯度合ＣＤ_４、ＣＤ_５とミネラル減少率との相関係数が高く、虫歯度合ＣＤ_４、ＣＤ_５は、虫歯の進行度合について客観的な定量値で示すことができることが実証された。
【０１０６】
【発明の効果】
本発明によれば、初期虫歯を感度良く正確に検出し、しかもその進行度合をも検出できる虫歯検出装置及びこれを実現する虫歯検出プログラム得ることができる。
【図面の簡単な説明】
【図１】本実施形態の虫歯検出システムの概略構成を示す図である。
【図２】本実施形態の虫歯検出プログラムに基づいて虫歯検出処理（メイン処理及び単一部位測定処理）を示すフローチャートである。
【図３】本実施形態の虫歯検出プログラムに基づいて虫歯検出処理（単一部位測定処理、ＣＤ_１）を示すフローチャートである。
【図４】本実施形態の虫歯検出プログラムに基づいて虫歯検出処理（対比測定処理、ＣＤ_２）を示すフローチャートである。
【図５】本実施形態の虫歯検出プログラムに基づいて虫歯検出処理（光強度変化測定処理）を示すフローチャートである。
【図６】本実施形態の虫歯検出プログラムに基づいて虫歯検出処理（光強度変化測定処理、ＣＤ_３１）を示すフローチャートである。
【図７】本実施形態の虫歯検出プログラムに基づいて虫歯検出処理（光強度変化測定処理、ＣＤ_３２）を示すフローチャートである。
【図８】本実施形態の虫歯検出プログラムに基づいて虫歯検出処理（光強度変化測定処理、ＣＤ_４）を示すフローチャートである。
【図９】（ａ）〜（ｆ）は、実施例１〜４に用いられる光強度及び輝度の関係を、（ａ）：健常歯部位（軽）、（ｂ）：健常歯部位（中）、（ｃ）：健常歯部位（重）、（ｄ）：虫歯の軽度部位、（ｅ）：虫歯の中等度部位、（ｆ）：虫歯の重度部位について示すグラフである。
【符号の説明】
１虫歯検出システム（虫歯検出装置）
２紫外線照射装置（紫外線光源）
３蛍光受光装置（蛍光受光部）
４蛍光データ解析部
５表示装置（解析データ表示部）
ＣＤ_１、ＣＤ_２、ＣＤ_３１、ＣＤ_３２、ＣＤ_４虫歯度合[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a technique for detecting caries, and more particularly to a technique for non-destructively detecting caries in an early stage based on fluorescence information from the teeth.
[0002]
[Prior art]
As a conventional technique for detecting tooth decay using light, there is an apparatus described in Patent Document 1. Such an apparatus irradiates a tooth with red light (600 to 670 nm) as excitation light, and measures only the intensity of light received by a photodiode from fluorescence from the tooth. In addition, since the above-mentioned device detects caries by fluorescence derived from bacteria in the oral cavity, the caries are advanced and a hole is formed in the tooth, and when bacteria are proliferating in the caries, the caries are detected. Is possible.
[0003]
However, the degree of progress of the initial caries is not always correlated with the presence and amount of bacteria. In particular, in the case of early caries, it is rather difficult to detect bacteria in the oral composition at the corresponding site, and it is difficult to detect such caries using the apparatus described in Patent Document 1. That is, since the result of analysis based on such fluorescence information depends on the presence or absence of oral bacteria, etc., it is difficult to accurately determine the presence or absence of initial caries.
[0004]
In order to solve the problem of Patent Document 1, a QLF (Quantitative Light-Induced Fluorescence) method described in

Non-Patent Documents

1 and 2, and an apparatus realizing this method have been developed. This device irradiates with ultraviolet rays of 380 ± 70 nm and detects only the obtained fluorescence intensity of 520 nm or more, and the fluorescence intensity from the carious part is weaker than the fluorescence intensity from the healthy part of the tooth. The detection of tooth decay is carried out by utilizing the phenomenon of decay. Since the detection of caries in this case is not affected by the presence of bacteria, the presence or absence of caries can be detected more accurately than the apparatus disclosed in Patent Document 1. However, as shown in Comparative Example 2 described below, since the actual change in the mineral decrease rate does not match the change in the fluorescence intensity of 520 nm or more, it is difficult to measure the progress of the initial caries.
[0005]
Further, as an apparatus for detecting caries, there is an apparatus that irradiates a tooth with ultraviolet rays of 360 to 580 nm and measures fluorescence of 620 nm or more from the tooth (Patent Document 2). This device measures only the red fluorescence specific to the carious site, and does not detect even intraoral bacteria as in Patent Document 1. However, since the device described in Patent Document 2 measures only red fluorescence having a weak fluorescence intensity, the fluorescence intensity is insufficient to detect the presence of caries and is easily affected by the measurement environment such as external light. There is a problem that the detection sensitivity is lowered.
[0006]
On the other hand, there is a technique described in Non-Patent Document 3 as a technique capable of accurately detecting and quantifying the degree of progress of caries. This technology slices the extracted caries, takes a cross-section of the caries with a micro X-ray photograph, calculates the mineral reduction rate based on the information in the photograph, and calculates the mineral reduction rate to quantify the progress of caries. Is what you do. Such a method can surely confirm the progress of caries, but has the problem that it cannot be measured unless the teeth are removed and sliced.
[0007]
[Patent Document 1]
JP-A-2001-299699
[Patent Document 2]
European Patent Application No. 0555645
[Non-patent document 1]
Stokey, G .; K. , Et al. Dental Caries Diagnosis, Dent Clin North Am. , 43; 665-77, 1999.
[Non-patent document 2]
Shi X. Q, et al. Comparison of QLF and DIAGNOdent for quantification of smooth surface cares, Caries Res. , 35 (1): 21-6, 2001.
[Non-Patent Document 3]
Tadashi Yoshikawa et al., "Effects of pH and action time of 0.1 M lactic acid on demineralization of enamel", Journal of Oral Health Society, 1990, Vol. 40, p. 671-677
[0008]
[Problems to be solved by the invention]
SUMMARY OF THE INVENTION An object of the present invention is to provide a caries detection device for detecting caries that can detect the initial caries with high sensitivity and accuracy and detect the degree of progress of caries, and a caries detection program for realizing the caries detection apparatus.
[0009]
[Means for Solving the Problems]
The present inventors have found that when a tooth is irradiated with ultraviolet light (i-line of a mercury lamp at 365 nm), strong fluorescence is generated in the vicinity of 400 to 500 nm (equivalent to blue color) for a healthy tooth, whereas 400 nm is obtained for a carious tooth. It was found that the fluorescence around 500 nm was weakened, while the fluorescence was around 600-800 nm (corresponding to red).
[0010]
Further, the present inventors, when the irradiation light intensity of ultraviolet light is reduced, for caries, the fluorescence equivalent to blue and red is weakened, whereas for healthy teeth, the fluorescence equivalent to blue is weakened. However, it was found that the fluorescence corresponding to the red color became stronger.
[0011]
The present invention has been made based on the above findings, and has an ultraviolet light source, a fluorescent light receiving unit that receives fluorescent light from teeth by ultraviolet light emitted from the ultraviolet light source, and fluorescent light data transmitted from the fluorescent light receiving unit. And a data display unit for displaying data analyzed by the fluorescence data analysis unit, wherein the fluorescence data analysis unit divides the wavelength of visible light by the number of divisions. an extraction reference value M serving as a reference when extracting the fluorescence data for each area divided by n ₁ , M ₂ , M ₃ …… M _n And a storage unit for storing the extraction reference value M from the fluorescence data. ₁ , M ₂ , M ₃ …… M _n Extracted fluorescence data P corresponding to each of ₁ , P ₂ , P ₃ … P _n And extract the extracted fluorescence data P ₁ , P ₂ , P ₃ … P _n The above object has been achieved by providing a caries detection device configured to calculate one or two or more pieces of selected fluorescence data selected from the above, and to determine caries based on the calculation results.
[0012]
Since the tooth decay detecting device according to the present invention and the tooth decay detecting program for realizing the same can detect the initial tooth decay with high sensitivity, the treatment by the non-surgical treatment becomes easier without cutting the initial tooth decay. Furthermore, the caries detection device according to the present invention can also measure the degree of progress of caries. The progress of treatment of the initial caries can be observed and the degree of recovery can be confirmed, so that the progress of caries and the recovery of caries can be specifically shown to the patient. Further, it is possible to gain an understanding of the importance of the dental caries prevention treatment and the effects of the treatment, thereby contributing to the maintenance and improvement of oral health.
[0013]
By measuring the tooth surface with the dental caries detection device and the dental caries detection program for realizing the dental caries detection device according to the present invention, not only can the dental caries be detected with high accuracy, but also a part that is difficult to measure such as a tooth gap or ( It is also possible to perform a comparison measurement (measured at two places) between a healthy tooth part and a caries part (measured at two places). Further, by analyzing these fluorescence data based on the fluorescence intensities in two or more wavelength bands in the visible light region, caries (particularly, initial caries) and the degree of progress thereof can be accurately and accurately detected.
[0014]
In addition, the caries detection device according to the present invention and the caries detection program for realizing the same show different changes between caries and healthy teeth from among the fluorescence data from the teeth that change with the change in the intensity of the ultraviolet irradiation light. A wavelength band can be selected and analyzed based on a plurality of fluorescence intensities in the wavelength band, whereby a caries (particularly, an initial caries) and its progress degree can be detected accurately and accurately.
[0015]
In the present application, the “extraction reference value” indicates an upper limit value and a lower limit value of a wavelength when fluorescent data of a specific wavelength is extracted. When the visible light wavelength is divided by the division number n, M ₁ , M ₂ , M ₃ ... M _n It becomes. Caries degree CD ₁ When calculating (single site measurement processing), the extraction reference value M ₁ , M ₂ , M ₃ ... M _n Using caries degree CD ₂ When calculating (contrast measurement processing), the first extraction criterion M ₁₁ , M ₁₂ , M _Thirteen ... M _1n , And the second extraction criterion M ₂₁ , M ₂₂ , M ₂₃ ... M _2n Using caries degree CD ₃ , CD ₄ When calculating (light intensity change measurement process), the R extraction reference value M _R , G extraction reference value M _G , B extraction reference value M _B Is used.
[0016]
First extraction criterion M ₁₁ , M ₁₂ , M _Thirteen ... M _1n , And the second extraction criterion M ₂₁ , M ₂₂ , M ₂₃ ... M _2n May be equal or different from each other, and respectively ₁ , M ₂ , M ₃ ... M _n It corresponds to.
R extraction reference value M _R Has an arbitrary wavelength width selected from a wavelength band of 550 to 810 nm including not only a wavelength corresponding to red but also a wavelength corresponding to green. B extraction reference value M _B Has an arbitrary wavelength width selected from a wavelength band of 380 to 500 nm including not only a wavelength corresponding to blue but also a wavelength corresponding to green. G extraction reference value M _G Has an arbitrary wavelength width selected from a wavelength band of 450 to 650 nm including not only a wavelength corresponding to green, but also a wavelength corresponding to red and a wavelength corresponding to blue.
[0017]
R extraction reference value M _R Is one or more arbitrary wavelength widths selected from the range of 0.1 nm or more and 260 nm or less, and preferably one or more arbitrary wavelength widths selected from the range of 50 nm or more and 260 nm or less. B extraction reference value M _B Is one or more arbitrary wavelength widths selected from the range of 0.1 nm or more and 170 nm or less, and preferably one or more arbitrary wavelength widths selected from the range of 50 nm or more and 270 nm or less. G extraction reference value M _G Is one or more arbitrary wavelength widths selected from the range of 0.1 nm or more and 200 nm or less, and preferably one or more arbitrary wavelength widths selected from the range of 50 nm or more and 200 nm or less. The number of wavelength widths may be plural as long as it is within the range of the wavelength width.
[0018]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, preferred embodiments of a caries detection device of the present invention and a caries detection program for realizing the same will be described with reference to the drawings.
As shown in FIG. 1, a caries detection system (cavity detection device) 1 of the present embodiment includes an ultraviolet irradiation device (ultraviolet light source) 2 and a fluorescent light that receives fluorescence from teeth by ultraviolet light irradiated from the ultraviolet irradiation device 2. A light receiving device (fluorescent light receiving unit) 3, a data analyzing unit 4 for analyzing data transmitted from the fluorescent light receiving device 3, and a display device (analysis data display unit) 5 for displaying the analysis data analyzed by the data analyzing unit 4. And
[0019]
The data analysis unit 4 extracts an extraction reference value M serving as a reference when extracting fluorescence data for each region obtained by dividing the wavelength of visible light by the division number n. ₁ , M ₂ , M ₃ …… M _n Has an internal memory (storage unit) 16 for storing the extraction reference value M ₁ , M ₂ , M ₃ …… M _n Extracted fluorescence data P corresponding to each of ₁ , P ₂ , P ₃ … P _n And extract the extracted fluorescence data P ₁ , P ₂ , P ₃ … P _n One or two or more pieces of selected fluorescence data selected from are calculated, and the determination of caries is performed based on the calculation result. The extracted fluorescence data P ₁ , P ₂ , P ₃ … P _n Is the extraction reference value M ₁ , M ₂ , M ₃ …… M _n May be the average luminance value corresponding to
First, the caries detection system 1 will be described in detail.
[0020]
The caries detection system 1 has a main control unit 10 (to be described in detail later) that controls the entire system. The main control unit 10 is connected to the ultraviolet irradiation device 2 and the fluorescent light receiving device 3 via the input / output unit 11, and is also connected to the storage device 12, the display device 5, and the output device 13. .
[0021]
The ultraviolet irradiation device 2 irradiates ultraviolet light having a wavelength of about 300 to 400 nm, and may be configured so that the irradiation light intensity can be adjusted. Examples of such an ultraviolet irradiation device 2 include an ultraviolet LED, a mercury lamp, and a metal halide lamp.
The ultraviolet LED is configured such that the intensity of irradiation light of ultraviolet light is adjusted. For example, the intensity of light is adjusted by controlling the amount of energization by the input / output control unit 11a or by changing the number of lit LEDs.
[0022]
In a mercury lamp or a metal halide lamp, irradiation light passes through a visible light cut filter to become ultraviolet light, and the intensity of the ultraviolet light can be adjusted. The intensity adjustment is performed by, for example, controlling the current value or using an ND filter.
The ultraviolet light is guided from the ultraviolet irradiation device 2 as long as it has a low ultraviolet absorptivity, but is not particularly limited. Is directly illuminated.
[0023]
The fluorescence receiving device 3 absorbs the fluorescence from the teeth by the irradiation of the ultraviolet light, the light in the ultraviolet region by passing through the ultraviolet cut filter 14, and receives only the light in the visible light region to the optical device through the optical fiber. It is configured as follows.
The optical device may be any device that can capture information including color information from the fluorescent light in the visible light region as fluorescent data and transmit the information to the input / output unit 11. The input / output unit 11 is configured to convert analog information from the optical device into a digital value by the AD converter 11b.
[0024]
The optical device described above includes, for example, a spectral luminance meter.
Specifically, the spectral luminance meter is configured to obtain the respective information by splitting the fluorescent light by a prism or the like and capturing the split light by an optical sensor.
The storage device may be any device that can store the analysis data analyzed by the data analysis unit 4, and includes, for example, a hard disk, a flexible disk, and an optical disk.
[0025]
The display device 5 may be any device that can display the analysis data and information necessary for selecting the analysis data (the number of measurement sites and the change in light intensity), such as a CRT display and a liquid crystal display.
The output device 13 may be any device that can output the analysis data, and includes, for example, a printer.
[0026]
The main control unit 10 includes a fluorescence data analysis unit 4 including a CPU 15 and an internal memory 16. The input / output unit 11 includes an input / output control unit 11a and an AD converter 11b.
The CPU 15 is configured to decode and execute commands from a control program such as an OS (Operating System) or a caries detection program.
[0027]
The internal memory 16 temporarily stores information from the input / output control unit 11a and the AD converter 11b and analysis data from the storage device 12.
Further, the internal memory 16 has an extraction reference value M ₁ , M ₂ , M ₃ ... M _n , The first extraction criterion M ₁₁ , M ₁₂ , M _Thirteen ... M _1n , The second extraction criterion M ₂₁ , M ₂₂ , M ₂₃ ... M _2n , R extraction reference value M _R , G extraction reference value M _G , B extraction reference value M _B Is stored.
[0028]
In the present embodiment, the division number n of the visible light wavelength is set to 3 and the extraction reference value M ₁ Is a reference value having a wavelength of 550 to 810 nm. First extraction reference value M ₁₁ , The second extraction criterion M ₂₁ , And R extraction reference value M _R Are all extraction reference values M ₁ Shall be equal to
[0029]
In addition, the extraction reference value M ₂ Is a reference value at a wavelength of 450 to 650 nm. First extraction reference value M ₁₂ , The second extraction criterion M ₂₂ , And G extraction reference value M _G Are all extraction reference values M ₂ Shall be equal to
Further, the extraction reference value M ₃ Is a reference value at a wavelength of 380 to 550 nm. First extraction reference value M _Thirteen , The second extraction criterion M ₂₃ , And B extraction reference value M _B Are all extraction reference values M ₃ Shall be equal to
[0030]
The fluorescence data analyzing unit 4 is configured as a means in which the dental caries detection program is executed by the CPU 15 so that the dental caries detection program and hardware resources such as the CPU 15 and the internal memory 16 cooperate.
[0031]
The caries detection program includes functions to be implemented by the CPU 15 such as a measurement site number selection function, a light intensity change function, a data acquisition function, a fluorescence data extraction / selection function, a caries degree calculation function, a caries presence / progression degree judgment function, and the like. With these functions, the above-mentioned caries detection system 1 is realized.
[0032]
Next, the processing of the caries detection program according to the present embodiment will be described with reference to FIGS.
The caries detection method uses a common main process (S1 to S3, S5), and a single site measurement process (S4, S11 to S19), a comparison measurement process (S21 to S30), light Intensity change measurement processing (S31 to S35, S41 to S48, S51 to S58, S61 to S68) is roughly classified into three types.
[0033]
The single site measurement process is a process for detecting the presence or absence of caries at an externally visible caries site or a suspected caries site, particularly at an invisible caries site such as a tooth gap or bite, or the degree of progress of the caries. One or more cavities are measured at least once.
The contrast measurement process is a process for detecting the presence or absence of caries in a caries part or a carious part that is visible from the outside (hereinafter simply referred to as a caries part) or the degree of progress of the caries. Are measured independently of each other.
The light intensity change measurement process is a process for detecting the presence or absence of caries and the degree of progress of the caries, regardless of whether it is visible from the outside. Measure twice.
[0034]
More specifically, as shown in FIG. 2, the CPU 15 causes the display device 5 to display whether or not to perform measurement (S1). When measurement is to be performed, measurement is performed based on the measurement site number selection function of the caries detection program. It is displayed whether or not the number of parts is "1" (S2).
If the number of measurement sites is not “1”, the process branches to “contrast measurement process” (branch B, described in detail below). If the number of measurement sites is “1”, the CPU 15 Based on the light intensity change selection function, whether or not to change the light intensity of the light source is displayed (S3).
[0035]
When the light intensity of the light source is changed, the process branches to “light intensity change measurement process” (branch C, details will be described later). When the light intensity of the light source is not changed, the CPU 15 executes the “single site measurement process”. Execute
[0036]
Here, in the single site measurement processing, first, the measurer irradiates the target site using the ultraviolet irradiation device 2 and obtains information from the fluorescence from the teeth using the fluorescence receiving device 3.
Next, the CPU 15 fetches the fluorescence data (analog value) from the optical device into the internal memory 16 as a digital signal AD-converted by the AD converter 11b based on the data fetching function of the caries detection program.
[0037]
Then, the CPU 15 determines the extraction reference value M based on the fluorescence data extraction / selection function of the caries detection program. _R , M _G , M _B Corresponding to the extracted fluorescence data P _R , P _G , P _B Is extracted and stored in the internal memory 16, and the selected fluorescence data P _R , P _B Is selected and stored in the internal memory 16 (S4).
[0038]
Here, the extraction reference value M _R In the visible light region (380 to 810 nm), the wavelength is preferably 550 to 810 nm, more preferably 580 to 680 nm.
In addition, the extraction reference value M _B Has a wavelength of preferably 380 to 550 nm, more preferably 400 to 500 nm, in the visible light region.
Further, the extraction reference value M _G Has a wavelength of preferably 450 to 650 nm, more preferably 500 to 600 nm in the visible light region.
[0039]
Thereafter, as shown in FIG. 3, the CPU 15 selects the selected fluorescence data P based on the caries degree calculation function of the caries detection program. _R , P _B Is determined, and the value is determined according to the following equation (1). ₁ Is calculated (S11).
CD ₁ = P _R / P _B … Equation (1)
This caries degree CD ₁ Indicates the fluorescence data P for the caries site as the caries progress. _R While the fluorescence data P _B , Fluorescence data P _G The degree of caries is reduced and the degree of caries progression is expressed as a quantitative increasing function.
[0040]
Here, the fluorescence data P _B Is the absolute intensity of the fluorescence data P _G Larger, less susceptible to external light, etc. ₁ Can be calculated with higher accuracy.
Also, based on the fluorescence data extraction / selection function of the caries detection program, the selected fluorescence data P _B Instead of selected fluorescence data P _G And the degree of tooth decay CD according to the following equation (2): ₁ May be calculated.
CD ₁ = P _R / P _G … Equation (2)
[0041]
The processing of S12 to S19 is processing executed by the CPU 15 based on the decay detection / progression degree determination function of the decay detection program.
In S12, the caries degree CD ₁ To the lower threshold E ₁ Compare with Here, the “lower threshold” is a value for discriminating healthy teeth from caries (especially initial caries, the same applies hereinafter), and conditions such as irradiation light intensity and irradiation area in the ultraviolet irradiation device 2 and fluorescence It depends on conditions such as the optical path length in the light receiving device 3 and the sensitivity of the light receiving element, and is determined by calibration in the caries detection system 1.
[0042]
Caries degree CD ₁ Is the lower threshold E ₁ Less than or lower threshold E ₁ If it is equal to, it is displayed that the tooth is a healthy tooth (analysis data) and the process returns to S1 of the main processing (S18, 19), and the caries degree CD ₁ Is the lower threshold E ₁ If it is larger, a message indicating that it is a tooth decay (analysis data) is displayed (S13).
[0043]
In S14, the caries degree CD ₁ To the upper threshold F ₁ Compare with Here, the “upper limit threshold” is a value for discriminating between mild caries and severe caries, and is determined in the same manner as the lower threshold.
[0044]
Caries degree CD ₁ Is the upper threshold F ₁ If it is smaller, a message indicating that it is a mild initial caries (analysis data) is displayed (S15), and the caries degree CD ₁ Is the upper threshold F ₁ Greater than or lower threshold F ₁ If it is equal to, the fact that it is a severe initial caries (analysis data) is displayed (S16), and the process returns to S1 of the main processing (S17).
[0045]
In S2, if the number of measurement sites is not “1”, the CPU 15 executes “contrast measurement processing”.
Here, in the comparison measurement process, first, the measurer uses the ultraviolet irradiation device 2 to apply ultraviolet rays to the carious site (a site suspected to be carious) and a healthy region in the vicinity thereof on the same tooth. Irradiation is performed, and the fluorescence data of the first information is obtained from the fluorescence of the carious part and the fluorescence data of the second information is obtained from the fluorescence of the healthy part using the fluorescence receiving device 3.
[0046]
Next, as shown in FIG. 4, the CPU 15 converts the fluorescence data of the first and second information from the optical device into digital data obtained by AD conversion by the AD converter 11b based on the data capturing function of the caries detection program. The signal is taken into the internal memory 16 as a signal.
Then, the CPU 15 executes the first extraction reference value M based on the fluorescence data extraction / selection function of the caries detection program. _1R , M _1G , M _1B Corresponding to the extracted fluorescence data P _1R , P _1G , P _1B Is extracted and stored in the internal memory 16, and the selected fluorescence data P _1R , P _1B Is selected and stored in the internal memory 16 (S21).
Similarly, the CPU 15 sets the second extraction reference value M _2R , M _2G , M _2B Corresponding to the extracted fluorescence data P _2R , P _2G , P _2B Is extracted and stored in the internal memory 16, and the selected fluorescence data P _2R , P _2B Is selected and stored in the internal memory 16 (S21).
[0047]
Thereafter, the CPU 15 selects the selected fluorescence data P based on the caries degree calculation function of the caries detection program. _1R , P _1B , P _2R , P _2B Is determined, and the value is determined according to the following equation (3). ₂ Is calculated (S22).
CD ₂ = | P _1R −P _2R │ × │P _1B −P _2B |… Equation (3)
[0048]
Fluorescence data P _1R , P _1G , P _1B (Cavities) and fluorescence data P _2R , P _2G , P _2B The size of the (healthy part) is determined by the fluorescence data P _R1 , P _G1 , P _B1 , And fluorescence data P _R2 , P _G2 , P _B2 In the case indicated by, this caries degree CD ₂ Indicates the fluorescence data P of the carious site as the caries progress. _R1 Is the fluorescence data P of the healthy part _R2 And the fluorescence data P of the carious region _B1 , P _G1 Is the fluorescence data P of the healthy part _B2 , P _G2 The degree of caries progression is expressed as a quantitative increasing function using the characteristic of becoming smaller.
[0049]
Here, the fluorescence data P _B Is the absolute intensity of the fluorescence data P _G Larger, less susceptible to external light, etc. ₁ From the viewpoint of improving the accuracy of the extracted fluorescence data P _G Is not used, but based on the fluorescence data extraction / selection function of the caries detection program, the selected fluorescence data P _1B , P _2B Instead of selected fluorescence data P _1G , P _2G Is selected and the caries degree CD is determined according to the following equation (4). ₂ May be calculated, and the selected fluorescence data P _1B , P _2B And selected fluorescence data P _1G , P _2G Are selected, and the caries degree CD is determined according to the following equation (4.1). ₂ May be calculated.
CD ₂ = | P _1R −P _2R │ × │P _1G −P _2B |… Equation (4)
CD ₂ = | P _1R −P _2R | × ｛| P _1B −P _2B | + | P _1G −P _2B |｝ ... Equation (4.1)
[0050]
The processing of S23 to S30 is processing executed by the CPU 15 based on the decay detection / progression degree determination function of the decay detection program, and is substantially the same as the processing of S12 to S19.
[0051]
In S23, the caries degree CD ₂ To the lower threshold E ₂ Compare with
Caries degree CD ₂ Is the lower threshold E ₂ Less than or lower threshold E ₂ If it is equal to the normal tooth, it is displayed that the tooth is healthy and the process returns to S1 of the main process (S29, S30), and the caries degree CD ₂ Is the lower threshold E ₂ If it is larger, a message indicating that the tooth is a caries is displayed (S24).
[0052]
In S25, the caries degree CD ₂ To the upper threshold F ₂ Compare with
Caries degree CD ₂ Is the upper threshold F ₂ If it is smaller, it is displayed that the tooth is a mild initial caries (S26), and the caries degree CD ₂ Is the upper threshold F ₂ Greater than or upper threshold F ₂ If it is equal to, it indicates that the tooth is a severe initial caries (S27), and returns to S1 of the main processing (S28).
[0053]
When the light intensity of the light source is changed in S3, the CPU 15 executes a “light intensity change measurement process”.
Here, in the light intensity change measurement process, first, the measurer uses the ultraviolet irradiation device 2 to ₁ , U ₂ (U ₁ > U ₂ ) Is applied to the same site of the same tooth, respectively, and the light intensity U is ₁ Fluorescence data of the first information is obtained from the fluorescence of ₂ The fluorescence data of the second information is obtained from the fluorescence of.
[0054]
Next, as shown in FIG. 5, the CPU 15 converts the fluorescence data of the first and second information from the optical device into digital data obtained by AD conversion by the AD converter 11b based on the data capturing function of the caries detection program. It is taken into the internal memory 16 as a signal.
[0055]
Then, the CPU 15 determines the R, G, B extraction reference value M based on the fluorescence data extraction / selection function of the caries detection program. _R , M _G , M _B Corresponding to the fluorescence data P extracted from the fluorescence data of the first information. _1R , P _1G , P _1B Is extracted and stored in the internal memory 16, and the selected fluorescence data P _1R , P _1B Is selected and stored in the internal memory 16 (S31).
[0056]
Similarly, the CPU 15 sets the R, G, B extraction reference value M _R , M _G , M _B Corresponding to the fluorescence data P extracted from the fluorescence data of the second information. _2R , P _2G , P _2B Is extracted and stored in the internal memory 16, and the selected fluorescence data P _2R , P _2B Is selected and stored in the internal memory 16 (S32).
The light intensity is not limited to two, but may be three or more.
[0057]
Thereafter, the CPU 15 determines the light intensity U based on the decay detection / presence function of the decay detection program. ₁ Selected fluorescence data P _1R And the light intensity U ₂ Selected fluorescence data P _2R It is determined whether or not the sign of the following equation (5) is “positive (+)” (S33), and if “positive (+)”, the possibility of tooth decay is determined. The fact that there is a certain tooth is displayed (S34), and in the case of "negative (-)", the fact that it is a healthy tooth is displayed and the process returns to S1 of the main processing (S35).
(P _1R ―P _2R ) ... Equation (5)
[0058]
The discrimination method is not limited to this, and a plurality of extracted fluorescence data P _1R , P _2R ... and light intensity U ₁ , U ₂ A method may be used in which a correlation is determined, and if the correlation is “positive”, it is determined that the tooth is tooth decay, and if the correlation is “negative”, it is determined that the tooth is healthy.
[0059]
The processing in steps S33 to S35 is based on the fluorescent data P _2R Is the fluorescence data P _1R For the healthy part, the fluorescence data P becomes smaller (positive correlation with the ultraviolet irradiation intensity). _2R Is the fluorescence data P _1R Utilizing the characteristic of becoming larger (negative correlation with ultraviolet irradiation intensity), the presence or absence of tooth decay is determined before determining the degree of caries progression.
[0060]
The processing after proceeding to S34 is based on the difference in the processing of calculating the degree of tooth decay. ₃₁ Processing (branch D ₁ , S41-S48), caries degree CD ₃₂ Processing (branch D ₂ S51-S58), caries degree CD ₄ Processing (branch D ₃ , S61 to S68).
[0061]
As shown in FIG. ₃₁ In the processing of (1), the CPU 15 determines the light intensity U based on the caries degree calculation function of the caries detection program. ₁ Selected fluorescence data P _1R , P _1B , And light intensity U ₂ Selected fluorescence data P _2R , P _2B Is determined, and the value is determined according to the following equation (6). ₃₁ Is calculated (S41).
CD ₃₁ = (P _1R / P _2R ) × (P _1B / P _2B ) ... Equation (6)
[0062]
This caries degree CD ₃₁ Indicates the fluorescence data P _2R , P _2G , P _2B Is the fluorescence data P _1R , P _1G , P _1B On the other hand, P _B2 , P _G2 , Respectively, _B1 , P _G1 P, although smaller _R2 Is P _R1 The degree of progress of tooth decay is expressed as a function using the characteristic of becoming larger.
[0063]
The processing of S42 to S48 is processing executed by the CPU 15 based on the decay detection / progression degree determination function of the decay detection program, and is substantially the same as the processing of S23 to S30.
In S42, the caries degree CD ₃₁ To the upper threshold F ₃₁ Compare with Caries degree CD ₃₁ Is the upper threshold F ₃₁ Greater than or upper threshold F ₃₁ If it is equal to the normal tooth, it is displayed that the tooth is a healthy tooth, and the process returns to S1 of the main process (S47, 48), and the caries degree CD ₃₁ Is the upper threshold F ₃₁ If it is smaller, the process proceeds to S43.
[0064]
In S43, the caries degree CD ₃₁ To the lower threshold E ₃₁ Compare with Caries degree CD ₃₁ Is the lower threshold E ₃₁ If it is larger, it is displayed that the tooth is a mild initial caries (S44), and the caries degree CD ₃₁ Is the lower threshold E ₃₁ Greater or lower threshold E ₃₁ If it is equal to, it is displayed that the tooth is a severe initial caries (S45), and the process returns to S1 of the main processing (S46).
[0065]
As shown in FIG. ₃₂ In the processing of (3), based on the fluorescence data extraction / selection function of the caries detection program, the selected fluorescence data P _1B , P _2B Instead of selected fluorescence data P _1G , P _2G Select the above caries degree CD ₃₁ In the comparison of the processes of the above, only the processes of S51, S52 and S53 are different.
[0066]
In S51, the light intensity U ₁ Selected fluorescence data P _1R , P _1G , And light intensity U ₂ Selected fluorescence data P _2R , P _2G The respective values are obtained, and the values are determined according to the following equation (7). ₃₂ Is calculated.
CD ₃₂ = (P _1R / P _2R ) × (P _1G / P _2G ) ... Equation (7)
In S52, the upper threshold F ₃₂ Is set differently, and in S53, the lower threshold E ₃₂ Setting method is different.
Other processes are the same as those described above, and a description thereof will be omitted.
[0067]
As shown in FIG. ₄ In the processing of (3), based on the fluorescence data extraction / selection function of the caries detection program, the selected fluorescence data P _1B , P _2B , P _1G , P _2G Select the above caries degree CD ₃₁ In the comparison of the processes of the above, only the processes of S61, S62 and S63 are different.
[0068]
In S61, the light intensity U ₁ Selected fluorescence data P _1R , P _1G , P _1B , And light intensity U ₂ Selected fluorescence data P _2R , P _2G , P _2B Is determined, and the value is determined according to the following equation (8). ₄ Is calculated.
CD ₄ = (P _1R / P _2R ) × ｛(P _1G / P _2G ) + (P _1B / P _2B )｝… Equation (8)
In S62, the upper threshold F ₄ Is set differently. In S63, the lower threshold E ₄ Setting method is different. Other processes are the same as those described above, and a description thereof will be omitted.
[0069]
In such light intensity change measurement processing, although not shown, the above-mentioned caries degree CD ₃₁ , CD ₃₂ , CD ₄ And the caries degree CD according to the following equation (9): ₅ May be calculated.
CD ₅ = (P _1R / P _2R ) × (P _1G / P _2G ) × (P _1G / P _2G ) ... Equation (9)
[0070]
As described above, according to the present embodiment, in the dental caries detection method, the degree of dental caries is determined by selecting the selected fluorescence data P over a range of energy values. _R , P _B , P _G , And comparing the caries degree CD with the lower threshold E and the upper threshold F, the "healthy teeth", It is possible to accurately and accurately determine whether the condition is “mild tooth decay” or “severe tooth decay”.
[0071]
Further, according to the present embodiment, the caries detection method can be roughly classified into three types: a measurement process using data obtained from one location, a measurement process for comparing data obtained from two locations, and a measurement process for changing light intensity. By enabling these methods to be selectively used or combined depending on the detection purpose and the measurement site, the presence / absence of caries and the degree of progress of caries can be detected efficiently and accurately.
[0072]
That is, in the measurement processing using the data obtained from one place, it is possible to use not only a visible part but also a part where it is difficult to obtain a comparative part such as a tooth gap or a bite. Just by measuring the location, the presence or absence of caries and the degree of progress can be detected. This measuring method is based on the obtained caries degree CD. ₁ This method is advantageous for measuring any part as a method that can instantaneously detect tooth decay based on
[0073]
In addition, in the measurement processing comparing the data obtained from the two locations, the presence or absence of decay and the progress The degree can be detected. This measurement process is performed in consideration of the comparison between the carious site and the healthy site. ₂ This is advantageous in that the degree of caries progression can be instantaneously detected on the basis of only this.
[0074]
Further, in the light intensity change measurement processing, the degree of caries progression can be detected by measuring the same carious part at least twice while changing the light intensity of ultraviolet light. This measurement process is based on the selected fluorescence data P having different light intensities. _1R , P _2R This is advantageous in that the presence or absence of tooth decay can be instantaneously determined only by comparing the size of the tooth, and that the degree of progress of the tooth decay according to the depth of the tooth can be obtained by changing the light intensity.
[0075]
Further, according to the present embodiment, by executing the caries detection program, it is possible to realize the caries detection system 1 having the above effects.
In particular, the extraction reference value M _R , M _G , M _B Fluorescence data P _R , P _G , P _B Is selected and extracted, it is possible to calculate various caries degrees CD only by taking in the fluorescence data once by the light-receiving fluorescent device 3.
In addition, the extraction reference value M _R , M _G , M _B By simply changing the setting values such as the above, the accuracy of the caries degree CD can be improved in response to the influence of external light and the like and noise.
[0076]
The present invention is not limited to the above embodiment, and various changes can be made.
For example, in the above light intensity measurement method, the light intensity was changed to two types. However, the present invention is not limited to this. ₃₁ , CD ₃₂ , CD ₄ May be calculated.
In addition, caries degree CD ₃₁ , CD ₃₂ , CD ₄ Is calculated, the ratio of fluorescence data with different light intensities (P _1R / P _2R ), Etc., but instead, the slope or correlation of the change in the fluorescence data may be used.
[0077]
Furthermore, in addition to the comparison of the caries degree CD with the lower threshold value E and the upper threshold value F, by adding another threshold value, the intermediate degree between the severe and the mild is indicated. You can also. Furthermore, in addition to the data indicating that the tooth is a healthy tooth, the caries degree CD itself may be displayed as the analysis data on the display device 5, and such analysis data may be output to the output device 13.
[0078]
Furthermore, the extraction reference value M _R , M _G , M _B May be directly written into the caries detection program without being stored in the internal memory 16.
[0079]
【Example】
The present inventors have determined the correlation between Examples 1 to 4 and Comparative Examples 1 and 2 according to the method described in Non-Patent Document 3, which can most accurately measure the degree of caries progression at present. The detection accuracy of the caries detection device was evaluated.
[0080]
The extracted tooth used in the experiment was an initial caries which did not lose its surface and could be recovered by non-surgical treatment. These extracted teeth were categorized into three types: very early (mild), advanced to some extent (moderate), and just before drilling (heavy) by the eyes of an experienced dentist.
[0081]
The extracted tooth which was classified was first measured by the caries detecting device according to the present invention. Thereafter, based on the method described in Non-Patent Document 3, the extracted tooth was sliced to prepare a sample for micro X-ray photography. In the embodiment, the accuracy of the dental caries detecting device of the present invention is determined by calculating the correlation coefficient between the measurement result of the dental caries detecting device according to the present invention and the mineral reduction rate obtained by the method described in Non-Patent Document 3. Verified.
[0082]
The mineral reduction rate indicates the degree of progress of tooth decay, and is a value obtained by computer image analysis of a portion from the surface to a depth of 300 microns using a micro X-ray photograph according to Non-Patent Document 3 described above. In addition, the mineral reduction rate of a healthy part is set to 0%, and when all of the teeth are lost due to melting, the mineral reduction rate is set to 100%.
[0083]
A caries detection system 1 used in the present embodiment and a caries detection method using the same will be described. A mercury lamp was used as the ultraviolet irradiation device 2. This mercury lamp was capable of efficiently irradiating i-rays by mounting a visible light cut filter that transmits ultraviolet light having a wavelength of 400 nm or less. Also, the mercury lamp reduces the light intensity to U by attaching an ND filter. ₁ (= 340mV / cm ² ), U ₂ (= 94mV / cm ² ) Can be changed to two stages. Ultraviolet light from a mercury lamp was directly applied to the teeth via an optical fiber.
[0084]
A spectral luminance meter was used as the fluorescence receiving device 3. The spectral luminance meter was equipped with a UV cut filter that transmits light of 400 nm or more, so that fluorescence data in the visible light region could be captured. The acquired fluorescence data was subjected to A / D conversion and transferred to the fluorescence data analysis unit as 16-bit spectrum data. Extraction reference value M _R From 600 to 800 nm, extraction standard value M _G From 500 to 600 nm, extraction reference value M _B Are set to 400 to 500 nm, and the corresponding fluorescence data P _R , P _G , P _B Was extracted.
[0085]
Tooth measurement site and light intensity U ₁ , U ₂ Will be described.
With regard to the carious parts, the light part L, the moderate part M, and the severe part H are set as measurement targets, and healthy parts (light) L ′, Three healthy sites (medium) M ′ and healthy sites (heavy) H ′ were measured.
[0086]
For each measurement site, the light intensity U ₁ And the light intensity U ₂ Corresponding to, subscripts “1” and “2” are added to the symbols of the measurement sites. For example, "L ₁ Is the light intensity U ₁ Shows the measurement site for the mild part of the caries, which was irradiated with ultraviolet rays ₂ , 1 ”is the light intensity U ₁ , U ₂ 3 shows the measurement site for the severe site of the caries, which was irradiated with ultraviolet light of each.
Light intensity U of each measurement site measured in this embodiment ₁ , U ₂ And fluorescence data P _R , P _B , P _G Is shown in FIG. 9 and the light intensity U ₁ , U ₂ , P _R , P _B , P _G Data (maximum 2 ¹⁶ = 65536) are shown in Tables 1, 2 and 3.
[0087]
[Table 1]

[0088]
[Table 2]

[0089]
[Table 3]

[0090]
[Example 1]
In Example 1, according to the “single site measurement process” of the caries detection process described in the above embodiment, the light intensity U ₁ Measurement site L ₁ , M ₁ , H ₁ , L ₁ ', M ₁ ', H ₁ 'For each caries degree CD ₁ Calculate the caries degree CD ₁ And the respective correlation coefficients between the mineral reduction rates.
[0091]
[Comparative Example 1]
In Comparative Example 1, in accordance with the technique described in Patent Document 2, the light intensity of the ultraviolet light was set to U ₁ And the measurement site L ₁ , M ₁ , H ₁ , L ₁ ', M ₁ ', H ₁ 'Was measured. A cut filter that transmits light of 620 nm or more was attached to the color CCD so that the color CCD could capture an image of only red fluorescence. This image is converted to a gray image, and P _R (16 bits). P _R And the respective correlation coefficients between the mineral reduction rates. Table 4 shows the measurement results of Example 1 and Comparative Example 1.
[0092]
[Table 4]

[0093]
As shown in Table 4, when the mineral reduction rate is high, it means that caries have progressed. Caries degree CD of Example 1 according to the present invention ₁ Coefficient of correlation with the rate of decrease in minerals and the degree of caries ₁ Demonstrated that the degree of caries progress can be objectively quantified.
[0094]
In order to accurately determine the degree of caries progression, the fluorescence data P _R Must also be higher. However, in contrast, in the case of Comparative Example 1, the moderate site M ₁ And severe site H ₁ Between the fluorescence data P _R Since the magnitude relationship is reversed and does not always match the degree of progress of caries, it is difficult to detect the degree of progress of caries.
[0095]
[Example 2]
In the second embodiment, the light intensity U is set according to the “contrast measurement process” of the caries detection process described in the above embodiment. ₁ Measurement site (L ₁ , L ₁ '), (M ₁ , M ₁ '), (H ₁ , H ₁ ') For each caries degree CD ₂ Calculate the caries degree CD ₂ And the respective correlation coefficients between the mineral reduction rates.
[0096]
[Comparative Example 2]
In Comparative Example 2, the intensity of the ultraviolet light was set to U ₁ And the measurement site (L ₁ , L ₁ '), (M ₁ , M ₁ '), (H ₁ , H ₁ ') Was measured. A cut filter that transmits light of 520 nm or more was attached to the color CCD so that the color CCD could capture images of 520 to 800 nm. This image was converted into a gray image, and the luminance (16 bits) of the carious part and the luminance (16 bits) of the healthy part were obtained for each measurement part, and the ratio was calculated as relative luminance. The respective correlation coefficients between the relative luminance and the mineral reduction rate were determined. Table 5 shows the measurement results of Example 2 and Comparative Example 2.
[0097]
[Table 5]

[0098]
From Table 5, the caries degree CD ₂ Coefficient of correlation with the rate of decrease in minerals and the degree of caries ₂ Demonstrated that the degree of progress of caries could be shown as an objective quantitative value. On the other hand, moderate sites of caries (M ₁ , M ₁ ') And severe site (H ₁ , H ₁ Since the magnitude relation of the relative luminances is reversed between ') and the luminance of the monochromatic light alone does not always coincide with the degree of progress of caries, it is difficult to detect the degree of progress of caries.
[0099]
[Example 3]
In Example 3, according to the “light intensity change measurement process” of the caries detection process described in the above embodiment, the light intensity U ₁ , U ₂ Measurement site L2, ₁ , M2, ₁ , H2, ₁ , L2, ₁ ', M2, ₁ ', H2, ₁ ', The brightness change (P _R1 ―P _R2 ), (P _G1 ―P _G2 ), (P _B1 ―P _B2 ) And caries degree CD ₃₁ , CD ₃₂ And calculate the caries degree CD ₃₁ , CD ₃₂ And the respective correlation coefficients between the mineral reduction rates. Tables 6 and 7 show the measurement results of Example 3.
[0100]
[Table 6]

[0101]
[Table 7]

[0102]
From Table 6, the luminance change (P _R1 ―P _R2 It has been found that the sign in parentheses) is an objective criterion for indicating the presence or absence of tooth decay. Also, from Table 7, the degree of tooth decay CD ₃₁ , CD ₃₂ Coefficient of correlation with the rate of decrease in minerals and the degree of caries ₃₁ , CD ₃₂ Demonstrated that the degree of progress of caries could be shown as an objective quantitative value.
[0103]
[Example 4]
In Example 4, similarly to Example 3 described above, the caries degree CD ₄ , CD ₅ And calculate the caries degree CD ₄ , CD ₅ And the respective correlation coefficients between the mineral reduction rates.
The above caries degree CD ₃₁ , CD ₃₂ Is the selected fluorescence data P _R And the selected fluorescence data P _B , Selected fluorescence data P _G While either one of them is the object of calculation, the caries degree CD ₄ , CD ₅ Is the fluorescence data P _R , P _B , P _G The difference is that the three are calculated. Table 8 shows the measurement results of Example 4.
[0104]
[Table 8]

[0105]
From Table 8, the caries degree CD ₄ , CD ₅ Coefficient of correlation with the rate of decrease in minerals and the degree of caries ₄ , CD ₅ Demonstrated that the degree of progress of caries could be shown as an objective quantitative value.
[0106]
【The invention's effect】
ADVANTAGE OF THE INVENTION According to this invention, the caries detection apparatus which can detect the initial caries with high sensitivity and accuracy, and can also detect the progress degree, and the caries detection program which implement | achieves this can be obtained.
[Brief description of the drawings]
FIG. 1 is a diagram illustrating a schematic configuration of a caries detection system according to an embodiment.
FIG. 2 is a flowchart showing a tooth decay detection process (main process and single site measurement process) based on a tooth decay detection program of the present embodiment.
FIG. 3 shows a dental caries detection process (single site measurement process, CD ₁ FIG.
FIG. 4 shows a dental caries detection process (contrast measurement process, CD ₂ FIG.
FIG. 5 is a flowchart showing a caries detection process (light intensity change measurement process) based on the caries detection program of the embodiment.
FIG. 6 shows a tooth decay detection process (light intensity change measurement process, CD ₃₁ FIG.
FIG. 7 shows a dental caries detection process (light intensity change measurement process, CD ₃₂ FIG.
FIG. 8 shows a dental caries detection process (light intensity change measurement process, CD ₄ FIG.
9 (a) to 9 (f) show the relationship between light intensity and luminance used in Examples 1 to 4, wherein (a): healthy tooth portion (light), and (b): healthy tooth portion (middle). (C): healthy tooth region (heavy), (d): mild carious region, (e): moderate carious region, (f): severe carious region.
[Explanation of symbols]
1 Caries detection system (Caries detection device)
2 UV irradiation device (UV light source)
3 Fluorescent receiver (fluorescent receiver)
4 Fluorescence data analyzer
5 Display device (analysis data display unit)
CD ₁ , CD ₂ , CD ₃₁ , CD ₃₂ , CD ₄ Degree of tooth decay

Claims

An ultraviolet light source, a fluorescent light receiving unit that receives fluorescent light from teeth by ultraviolet light emitted from the ultraviolet light source, a fluorescent data analyzing unit that analyzes fluorescent data transmitted from the fluorescent light receiving unit, and a fluorescent data analyzing unit. A caries detection device comprising a data display unit for displaying the analyzed data,
The fluorescence data analysis unit stores extraction reference values M ₁ , M ₂ , M ₃ ,..., M _n that serve as references when the fluorescence data is extracted for each region obtained by dividing the wavelength of visible light by the number of divisions n. .. _Mn , and extracts extracted fluorescence data P ₁ , P ₂ , P _3, ... P _n corresponding to the respective extraction reference values M ₁ , M ₂ , M ₃ ,. A caries detection device configured to calculate one or more selected fluorescence data selected from the extracted fluorescence data P ₁ , P ₂ , P _3, ... _{Pn, and} to determine caries based on the calculation result.

A caries detection program for implementing caries detection by the caries detection device according to claim 1,
Capture the fluorescence data from the fluorescence receiving unit into the fluorescence data analysis unit,
The extracted fluorescence data P corresponding to each of the extraction reference values M ₁ , M ₂ , M ₃ ,..., M _{n serving as} a reference when extracting the fluorescence data for each area obtained by dividing the wavelength of the visible light by the division number n. _1, to extract the _{_{_{P 2, P 3 ... P n}}} ,
A caries detection program configured to calculate one or more selected fluorescence data selected from the extracted fluorescence data P ₁ , P ₂ , P ₃ ... _Pn, and to output the calculation result.

3. The non-caries detection program according to claim 2, wherein the number of divisions n is set to 2 or 3.

A first step of calculating the caries degree CD ₁ from the selected fluorescence data according to the following equation (1) or equation (2):
CD ₁ = P _R / P _B Equation (1)
CD ₁ = P _R / P _G Equation (2)
(In the formula (1) or the formula (2), the division number n is 3 or more,
P _R; extracted & selected corresponding to the extracted reference value M _R selectivity fluorescence data,
M _R ; a reference value that corresponds to any of the extraction reference values M _{1 to} M _n and extracts fluorescence data having a wavelength of 550 to 810 nm;
P _G; extracted & selected corresponding to the extracted reference value M _G selectivity fluorescence data,
M _G; corresponding to any of the extraction reference value _M 1 ~M _n, the reference value a wavelength to extract fluorescence data 450 to 650 nm,
P _B; extracted & selected corresponding to the extracted reference value M _B selectivity fluorescence data,
M _B; corresponding to any of the extraction reference value _M 1 ~M _n, indicates a reference value that wavelength to extract fluorescence data 380～550Nm)
A second step of comparing the value and a lower threshold E ₁ of the dental caries degree CD _1,
If the value of the caries degree CD ₁ is larger than the lower threshold value E _1, it is determined that the tooth is a caries, and the value of the caries degree CD ₁ is smaller than the lower threshold value E ₁ or the lower limit. third claim 2 wherein caries detection program for executing the steps of determining that if equal to threshold E ₁ is healthy teeth.

A fourth step of comparing the value of the caries degree CD ₁ with an upper threshold value F ₁ when the third step is determined to be a caries;
When the value of the caries degree CD ₁ is larger than the upper threshold value F _1, it is determined that the caries are severe caries, and the value of the caries degree CD ₁ is smaller than the upper threshold value F ₁ or caries detection program according to claim 4 for performing a fifth step of determining that if equal to the upper threshold F ₁ is a minor dental caries.

A tooth decay detection program that irradiates ultraviolet rays from a light source to a measurement site of the tooth and performs detection of the caries by fluorescence from the measurement site,
When the number of the measurement sites is two, a first step of capturing fluorescence data of the measurement site as first information and second information, respectively;
First extraction reference values M ₁₁ , M ₁₂ , and M that serve as references when the fluorescence data of the first information and the fluorescence data of the second information are respectively extracted for each region obtained by dividing the wavelength of visible light by the number of divisions n. _13, ... _{M 1n} and the second extraction reference value _{_{_{M 21, M 22, M 23}}} , ... with _{M 2n,} the first extraction reference value _{_{_{M 11, M 12, M 13}}} , ... corresponding to each of the _{M 1n} extraction fluorescence data _P _11, to extract the _{_{P 12, P 13 ... P 1n}} , extraction fluorescence data _{_{_{P 11, P 12, P 13}}} ... selected from _{P 1n} fluorescence data _P _{_1R,} _P _1G, with selecting a _{P 1B,} The extracted fluorescence data P ₂₁ , P ₂₂ , P ₂₃ ... P _2n are extracted corresponding to the second extraction reference values M ₂₁ , M ₂₂ , M ₂₃ ,... M _2n , respectively, and the extracted fluorescence data P ₂₁ , P _22, _{_P} 23 ... _P ₂ a second step of selecting selected fluorescence data P _2R , P _2G , P _2B from _n .
The following equation (3), a third step of calculating the dental caries degree CD ₂ from the selected fluorescence data according any one of formulas (4) and (4.1),
CD ₂ = | P _1R -P _2R | × | P _1B -P _2B | Equation (3)
CD ₂ = | P _1R -P _2R | × | P _1G -P _2G | Equation (4)
CD ₂ = | P _1R -P _2R | × ｛| P _1B -P _2B | + | P _1G -P _2B |｝ Equation (4.1)
(In the formulas (3), (4) and (4.1), the number of divisions n is 3 or more,
P _1R , P _2R ; selected fluorescence data of first and second information having a wavelength of 550 to 810 nm;
P _1G , P _2G ; selected fluorescence data of first and second information having a wavelength of 450 to 650 nm;
P _1B , P _2B ; indicating the selected fluorescence data of the first and second information having a wavelength of 380 to 550 nm)
A fourth step of comparing the dental caries degree CD ₂ value and lower threshold E _2,
The value of the dental caries degree CD ₂ is the judges that when the lower limit is greater than the threshold E ₂ are caries, the value of the dental caries degree CD ₂ is, the lower threshold E ₂ is less than or the lower limit to caries detection program to equal the threshold E ₂ executes a fifth step of determining that the healthy tooth.

When it is determined that the tooth is a tooth decay in the fifth step,
A step of comparing the value of the caries degree CD ₂ with an upper threshold F ₂ ;
The value of the dental caries degree CD ₂ is, when the larger upper threshold F ₂ is determined to be severe caries, the value of the dental caries degree CD ₂ is the upper threshold F ₂ is smaller than or the 5.2 claim 6 wherein caries detection program for executing the steps of determining that if equal to the upper threshold F ₂ is the minor dental caries.

An ultraviolet light source, a fluorescent light receiving unit that receives fluorescent light from teeth by ultraviolet light emitted from the ultraviolet light source, a fluorescent data analyzing unit that analyzes fluorescent data transmitted from the fluorescent light receiving unit, and a fluorescent data analyzing unit. A caries detection device comprising a data display unit for displaying the analyzed data,
The fluorescence data analysis unit stores extraction reference values M ₁ , M ₂ , M ₃ ,..., M _n that serve as references when the fluorescence data is extracted for each region obtained by dividing the wavelength of visible light by the number of divisions n. It has a storage unit,
Two or more different light intensity _{_{_{_{U 1, U 2, ... U}}}} n (U 1> U 2, ...> U n) the extraction reference value from the fluorescence data acquired fluorescence data of the measurement site per _M _{1, M} 2, M _3, ... extracted fluorescence data _P 1 corresponding to each of the _{_{_{M n, P 2, P 3}}} ... extracts _{P n,} the extract fluorescence data _{_{_{P 1, P 2, P 3}}} ... 1 or 2 selected from _{P n} A tooth decay detecting device configured to calculate the above selected fluorescence data and determine a tooth decay based on the calculation result.

A tooth decay detection program that irradiates ultraviolet rays from a light source to a measurement site of the tooth and performs detection of the caries by fluorescence from the measurement site,
Two or more different light intensity _{_{_{_{U 1, U 2, ... U}}}} n (U 1> U 2, ...> U n) For each first information fluorescence data of the measurement site, the second information, ... taking as the n information A first step;
With a reference R extracted reference value M _R when the wavelength in the visible light is respectively extracted fluorescence data of the first to n-th information region of 550～810Nm, corresponding to the R extracted reference value M _R extraction fluorescence data _{_{_{P 1R, P 2R, P 3R}}} ... P nR extracts, extraction fluorescence data _{_{_{P 1R, P 2R, P 3R}}} ... selected from _{P nR} fluorescence data _P _1R, and a second step of selecting _{P 2R,}
A third step of calculating a sign from the selected fluorescence data according to the following equation (5):
_(P 1R -P _2R) ... (5)
(In the above formula (5),
P _1R; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _{U i} and the i information of the selected fluorescent data corresponding to R extracted reference value _{M R} of,
P _2R; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _U j of indicating the selection fluorescence data of the j information corresponding to _{(<U i)} and R extracted reference value _{M R)}
If the sign obtained from the above equation (5) is positive, it is determined that there is a possibility of tooth decay, and if it is negative or zero, it is determined that the tooth is healthy. Detection program.

When it is determined that there is a possibility of caries in the fourth step,
Using G extraction reference value M _G as a reference when the wavelength in the visible light is respectively extracted fluorescence data of the first to n-th information in the region of 450 to 650 nm, corresponding to the G extracted reference value M _G extraction fluorescence data _P _{_1G,} _P _{_2G,} extracts the _{_P} 3G ... _P _nG, extraction fluorescence data _P _{_1G,} _P _{_2G,} selected from _P 3G ... _{P nG} fluorescence data _P _1G, with selecting the _{P 2G,} in the visible light with reference to become B extracted reference value M _B when wavelength is respectively extracted fluorescence data of the first to n-th information region of 380～550Nm, extracted fluorescence data corresponding to the B extracted reference value M _B _{_{_{P 1B, P 2B, P 3B}}} ... extracts _{P nB,} extraction fluorescence data _P _{_1B,} _P _{_2B,} selected from _P 3B ... _{P nB} fluorescence data _P _1B, a 4.1 selecting a _{P 2B,}
And 4.2 step of calculating the dental caries degree CD ₃ from the selected fluorescence data in accordance with the following equation (6) or Formula (7),
CD ₃ = (P _1R / P _2R ) × (P _1B / P _2B ) Formula (6)
CD ₃ = (P _1R / P _2R ) × (P _1G / P _2G ) Equation (7)
(In the above formula (6) or (7),
P _1G; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _{U i} and the i information of the selected fluorescence data corresponding to the G extracted reference value _{M G} of,
P _2G; light intensity _{_U} _1, _U _2, ... _U one of the _n _{_U} j _(<U _i) and the j information of the selected fluorescence data corresponding to the G extracted reference value _{M G,}
P _1B; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _{U i} and B extracted reference value the i information of the selected fluorescent data corresponding to _{M B} of
P _2B; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _U j of indicating the selection fluorescence data of the j information corresponding to _{(<U i)} and B extracted reference value _{M B)}
A step 4.3 of comparing the value of the caries degree CD ₃ with the upper threshold value F ₃ ;
The value of the dental caries degree CD ₃ is, the judges that if equal to the upper threshold F ₃ is larger than or the upper threshold F ₃ is a healthy tooth, the value of the dental caries degree CD ₃ is the 4.4 according to claim 9 caries detection program for executing the steps of determining that if the upper threshold F ₃ is smaller than a tooth decay.

When it is determined that the tooth is a tooth decay in the step 4.4,
A 4.5 step of comparing the value of the caries degree CD ₃ with a lower threshold E ₃ ;
The value of the dental caries degree CD ₃ is the determined to be mild caries when equal lower threshold E ₃ greater than or the lower threshold E _3, the value of the dental caries degree CD ₃ is the 4.6 10. caries detection program according to execute a step of determining that if the lower threshold E ₃ is smaller than a severe dental caries.

When it is determined that there is a possibility of caries in the fourth step,
Using G extraction reference value M _G as a reference when the wavelength in the visible light is respectively extracted fluorescence data of the first to n-th information in the region of 450 to 650 nm, corresponding to the G extracted reference value M _G extraction fluorescence data _P _{_1G,} _P _{_2G,} extracts the _{_P} 3G ... _P _nG, extraction fluorescence data _P _{_1G,} _P _{_2G,} selected from _P 3G ... _{P nG} fluorescence data _P _1G, with selecting the _{P 2G,} in the visible light with reference to become B extracted reference value M _B when wavelength is respectively extracted fluorescence data of the first to n-th information region of 380～550Nm, extracted fluorescence data corresponding to the B extracted reference value M _B _{_{_{P 1B, P 2B, P 3B}}} ... extracts _{P nB,} extraction fluorescence data _P _{_1B,} _P _{_2B,} selected from _P 3B ... _{P nB} fluorescence data _P _1B, a 4.1 selecting a _{P 2B,}
And 4.2 step of calculating the dental caries degree CD ₄ from the selected fluorescence data in accordance with the following equation (8),
CD ₄ = (P _1R / P _2R ) × {(P _1G / P _2G ) + (P _1B / P _2B )} Equation (8)
(In the above formula (8),
P _1G; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _{U i} and the i information of the selected fluorescence data corresponding to the G extracted reference value _{M G} of,
P _2G; light intensity _{_U} _1, _U _2, ... _U one of the _n _{_U} j _(<U _i) and the j information of the selected fluorescence data corresponding to the G extracted reference value _{M G,}
P _1B; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _{U i} and B extracted reference value the i information of the selected fluorescent data corresponding to _{M B} of
P _2B; light intensity _{_{_{U 1, U 2, ... U}}} n any one of _U j of indicating the selection fluorescence data of the j information corresponding to _{(<U i)} and B extracted reference value _{M B)}
A 4.3 step of comparing the value of the caries degree CD ₄ with the upper threshold value F ₄ ;
The value of the dental caries degree CD ₄ judges that the to equal to the upper threshold F ₄ is larger than or the upper threshold F ₄ are teeth healthy, the value of the dental caries degree CD ₄ is the 4.4 according to claim 9 caries detection program for executing the steps of determining that if the upper threshold F ₄ smaller than a tooth decay.

When it is determined that the tooth is a tooth decay in the step 4.4,
A 4.5 step of comparing the value of the caries degree CD ₄ with the lower threshold E ₄ ;
The value of the dental caries degree CD ₄ is the equal to the lower threshold E ₄ is greater than or the lower threshold E ₄ is determined to be a minor dental caries, the value of the dental caries degree CD ₄ is the 12. caries detection program according to run a 4.6 determining that if the lower threshold E ₄ smaller than a severe dental caries.

A tooth decay detection device that realizes processing by the tooth decay detection program according to any one of claims 9 to 13.