医学序列图像中的多目标跟踪技术与实现

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华中科技大学硕士学位论文医学序列图像中的多目标跟踪技术与实现姓名:蔡征申请学位级别:硕士专业:通信与信息系统指导教师:黄瑞光20060507AbstractRealizingacomputerassistedspermmotionanalysissystemisakeytaskinthisproject.So,findingakindofrapidandprecisealgorithmisthekeypointofthisprojectandalsothispaper.Kalmanforecasttrackingalgorithmhasthemeritsofsimplerecursivealgorithmsmalldatastorageandgoodperformanceinrealtimerealizing.Socomparingdifferentkindsoftrackingalgorithms,the'forecastassociationmodifying'methodwhichisbasedonKalmanfilteristakenintoaccount.However,thestandardKalmanfilterisestablishedonthestandardmathematicalmodelwhichisjustakindofsimilitudetotherealmodel.Sothereisestimationbias.Withtheincrementoftargets,theprobabilityofsuperpositionandmotionmutationincreases.Thatwillinducetheincrementofestimationbiaswhichwillprobablyleadtothetrackingfailure.Basedontheanalysisofthemotioncharacteristics,theretrospectivemethodisusedtocompensatethebias.Thesystemrealizedwiththisalgorithmshowsperfectperformanceintheclinicalexperiments.Howeverthiscompensationalgorithmtriestomodifythebiasfromtheresultsbutnottheessence.So,deeperresearchesaremadebasedontheexperimentsintherealizedsystem.Anewmodifiedalgorithmisbroughtforward.Theanalysisandcompensationoftheestimationbiasarethekeypointsofthispaperandalsoourinnovation.Thestudywaywhichisfromtheorytopractice,thenbacktotheorytosublimingtheorygivesathoroughresearchinthissubject.Thesuccessfulclinicalexperimentstestifythatthesettlementofthisprojectissatisfied.Keywords:Multi-targettrackingDataassociationCompensationalgorithmStrongtrackingfilter_____111.11937SCRWax1955Wax1964Sittler2[1]70Bar-ShalomSinger[2]Mk3B“”Mk1.2DNApH[3][4][5][6][7]31.31.4422.1MacroCCD25/2-1020070maxVMacro8mm10mm5DDD2-2Dmax/DVf=2-1fD123462.2CCDPCIWindowsXP2-32-3CCD2.32.3.12-42-32-4CCD72-3CCDMMTT[8]2-52-5//2.3.211971Signer[9]82PDAProbabilisticDataAssociationPDABar-Shalom1972Bayes[10]PDAjk1()()NjijijiYkPyk==∑2-2ijPij()ijykjiNjPDA[11]3JPDAJointProbablilisticDataAssociation80Bar-ShalomPDA[12]JPDAJPDA94MHTMultipleHypothesisTrackingReid[13]1977[14]Bar-ShalomJPDA5[15]Matlab2-6502102-7matlab2-81112stSsttsStSt=2-33452-9aocboaocbocabocaobcoaobocoaocbocoaocbocco122.3.325/2-101332-13-13-13.1143.3.13-1RGB0.2990.5870.114GreyRGB=++3-12-13-23-23.3.2CCD[17]3153.21[19]3-22OtsuOtsu[18]3-23-3OtsuOtsu163-3Otsu1-miin1miNn=∑3-2iinPN=3-3k0{1~}Ck=1{1~}Ckm=+0C01kikiPww===∑3-41C111mikikPww=+==-∑3-5170C010kikikiPmmww=×==∑3-61C11111mikikkiPmmww=+×-==-∑3-71miiiPm==∑1kkiiiPm==∑k0011mwmwm=+3-82222001101102()()()[][1]kkkkkswmmwmmwwmmwmmww=-+-=-×-=×-3-91mkkOtsu3-43-4OtsuOtsu183-4Otsu3[20]ABAB0ThOtsu`1Th3-419L0Th1Th0A(Th23-53-50LOtsu`1Th0LMAXSiSMAXSiMAXSSiMAXSSiMAXSSiS12,iiSSL,1,2,3ijMAXSSj=L3-10Otsu`1Th`1Th203-63-43-63.33.3.10110[21]3.3.2214884(,)fxy(,)xyp4(1,),(1,),(,1),(,1)xyxyxyxy+-+-rp44()Np3-7prrrr3-7444()Np4()Np3.43.4.1223.4.2RGB[22]3(R)(G)(B)RGBCCDRGBRGB3-8(0,1,0)(1,0,0)(0,0,1)(0,0,0)(1,1,1)3-8RGB23RRe(,)dxy(,)xy(,)Greenxy(,)xy(,)(,)(,)(,)(,)Re(,)(,)Re(,)xyRxyRxyRxyRGreenxyThresholddxyGreenxyThresholddxy∈∈∈∈⎧⎪⎪⎪⎪⎨⎪⎪≤⎪⎪⎩∑∑∑∑3-11ThresholdRGB3-83.4.32-13-93-924[23][24]2-12-12544.14.1.11CVCACVCACV....()()010()001()()xtxttxtxtw⎡⎤⎡⎤⎡⎤⎡⎤⎢⎥=+⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎣⎦⎣⎦4-1x.x..x()tw2s2..()(1)0T()00()(1)xkxkTkTxkxkw⎡⎤⎡⎤+⎡⎤⎡⎤⎢⎥=+⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎣⎦+⎣⎦4-2T()kw2[()()]wEkksww=CA.22........1/2/201()0011xxTTTTTtxxxxw⎡⎤⎡⎤⎢⎥⎢⎥⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥=+⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎢⎥⎢⎥⎣⎦⎣⎦4-32622......(1)()1/2/2(1)01()()0011(1)()xkxkTTTxkTxkTkxkxkw⎡⎤+⎡⎤⎢⎥⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥+=+⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦+⎢⎥⎣⎦⎣⎦4-4CV2SingerSinger[25]2(){()()}taaREatatebtts-=+=4-52asb.()()()atatwtb=-+4-6.........()()0100()001()0()00-1()()xtxtxtxtwtxtxtb⎡⎤⎡⎤⎢⎥⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥=+⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎢⎥⎢⎥⎣⎦⎣⎦4-7270b=SingerCACVCA3[26]..()()()xtatat-=+4-8.()()aaatwt=-+4-9()at-.....()()()()xtaxtaatwt-=-++4-10.........010000010()0()00-1xxatwtxxaaxx-⎡⎤⎡⎤⎢⎥⎡⎤⎡⎤⎡⎤⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥=++⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎢⎥⎣⎦⎣⎦⎣⎦⎢⎥⎢⎥⎣⎦⎣⎦4-11Singer4.1.22CV28XYk01(,)xx,01(,)vvktd25/0.04T1,EwwkkkkxAxwQ+=+=4-121kx+1k+kAwQ1t000100001t0001Add⎡⎤⎢⎥⎢⎥=⎢⎥⎢⎥⎣⎦4-130011xvxxv⎧⎫⎪⎪⎪⎪=⎨⎬⎪⎪⎪⎪⎩⎭4-14kzk01zzz⎧⎫=⎨⎬⎩⎭4-15T,EvvkkkkzHxvR=+=4-1629vRH1000=0010H⎡⎤⎢⎥⎣⎦4-174.2[33][35][34]4.2.1[27][28]k()xk(1|1)xkk--%4-12()xkˆˆ(|1)()(1|1)xkkAkxkk-=--4-1830()wk()xk4-16ˆ(|1)xkk-()zkˆˆˆ(|1)()(|1)()()(1|1)zkkHkxkkAkHkxkk-=-=--4-19()zkˆ(|1)zkk-()zkˆˆ()()(|1)()()()(1|1)kzkzkkzkAkHkxkka=--=---4-20()ka()zk()Gk()kaˆ(|1)xkk-ˆˆ(|)(|1)()()xkkxkkGkka=-+4-21()kx22ˆ()[()][(()(|))]kEenExnxnnx==-4-22()kx()Gkkˆˆˆ(|)=A(k)(1|1)G[()()()(1|1)]xkkxkkzkAkHkxkk--+---4-23T()=A(k)(k-1)A()()pkkQkx+4-24T-1k()=p(k)H(k)[H(k)p(k)H(k)+R]Gk4-25()=[I-H(k)G(k)]p(k)kx4-26ˆ(|)xkkk()xkˆ(1|1)xkk--1k-ˆ(1)xk-()Gk()pk()kx314.2.24.2()ka4-201()()()TgkkSkaa-=4-27()Sk()Sk()gkM2McM2M=()ka2()/2/2[()](2)|()|gkMefkSkap-=4-28|()|Sk()ka()zkˆ(|1)zkk-i()ika()izkˆ(|1)izkk-iGK()zkˆ()|()(|1)|1,2,iiiGrikzkzkkKiMas=--≤=K4-29()zkrisi22rioipisss=+4-302oisi2pis(|1)Pkk-i32M2()(2)MGRGVMK=4-314.2.3[29][32]25/0.04{}|1,2,iAiI=L1kt-{}|1,2,jBjJ=LktiA1iAiA%tan(,)|1,2,ijdDisceABjJ==%LdjB2iAaViAjBtan(,)/iiiVDisceABt=Δ||aiVV-iB3iAiSAiAjBjSB||jiSBSA-jB[30][31]ijijijijCOST(A,B)=(A,B)(A,B)(A,B),j=1,2,...JDKMabg++ggg4-3233ijijikiji

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