Dttion n Counting of R Bloo Clls in Bloo Cll Imgs using Hough Trnsform Musumi Mitr Informtion Thnology Govt. Collg of Enginring n Crmi Thnology 73, A. C. Bnrj Ln, Kolkt, Ini Rhul Kumr Gupt Computr Sin n Enginring Govt. Collg of Enginring n Crmi Thnology 73, A. C. Bnrj Ln, Kolkt, Ini Mnli Mukhrj Informtion Thnology Govt. Collg of Enginring n Crmi Thnology 73, A. C. Bnrj Ln, Kolkt, Ini ABSTRACT Counting of r loo lls (r) in loo ll imgs is vry importnt to tt s wll s to follow th pross of trtmnt of mny isss lik nmi, lukmi t. Howvr, loting, intifying n ounting of -r loo lls mnully r tious n tim-onsuming tht oul simplifi y mns of utomti nlysis, in whih sgmnttion is ruil stp. In this ppr, w prsnt n pproh to utomti sgmnttion n ounting of r loo lls in mirosopi loo ll imgs using Hough Trnsform. Dttion n ounting of r hv n on on fiv mirosopi imgs n finlly isussion hs n m y ompring th rsults hiv y th propos mtho n th onvntionl mnul ounting mtho. Gnrl Trms Digitl Img Prossing Kywors Img Sgmnttion, Dttion, R Bloo Cll, Counting, Hough Trnsform. 1. INTRODUCTION Contnt-s img inxing n rtrivl hs n n importnt rsrh r in omputr sin for th lst fw s. Mny igitl imgs r ing ptur n stor suh s mil imgs, rhitturl, vrtising, sign n fshion imgs, t. As rsult lrg img tss r ing rt n ing us in mny pplitions. In this work, th fous of our stuy is on mil imgs. A lrg numr of mil imgs in igitl formt r gnrt y hospitls n mil institutions vry y. Consquntly, how to mk us of this hug mount of imgs fftivly oms hllnging prolm [1]. In th fil of iomiin, us of ll s omplx ntur, it still rmins hllnging tsk to sgmnt lls from its kgroun n ount thm utomtilly [2-5]. Counting prolm riss in mny rl worl pplitions inluing ll ounting in mirosopi imgs, monitoring rows in survilln systms n prforming willif nsus or ounting th numr of trs in n ril img of forst [6-12]. Th mirosop insption of loo slis provis importnt qulittiv n quntittiv informtion onrning th prsn of hmti pthologis. From s this oprtion is prform y xprin oprtors, whih silly prforms two min nlyss. Th first is th qulittiv stuy of th morphology of th lls n it givs informtion of gnrtiv n tumorl pthologis. Th son pproh is quntittiv n it onsists of iffrntil ounting of th loo lls. Automt ll ountr systms (for xmpl lsr-s itomtrs [13] r vill in th mrkt, ut thy r not img s or morphologil n thy stroy th loo smpls uring th nlysis [13,14]. Only fw ttmpts of prtil / full utomt systms s on img prossing systms r prsnt in litrtur n thy r still t prototyp stg. Vinnzo t.l. [15] show th lssifition n ount of whit loo lls in mirosopi imgs for th ssssmnt of wi rng of importnt hmti pthologis. Aoring to Amrin Cnr Soity(2009), th norml r loo lls in our oy is ivi into four tgoris of gs, whih r nw orn, hilrn, womn n mn. R loo is msur y th mount of hmogloin. W suffr ftigu n short of rth whn th lvl of hmogloin is too low u to insuffiint oxygn supply. Th fft of high r loo lls in our loo n inition of n untt hrt or lung prolms. Thrfor, r ount is vry importnt in ignosis of mny iss. In this ppr w fous on th prolm of intifition n ounting of r loo lls y mirosopi imgs. Th propos work iniviuts th r loo lls from th othr loo lls in th loo ll imgs y using Hough Trnsform mtho n susquntly it ounts th numr of r loo lls in th imgs. Th whol work hs n on on MATLAB 7.1 pltform. Finlly, th ount is normliz to gt it pr ui millilitr, whih is th norml prti y mil prtitionr. 2. METHODS 2.1. Img Enhnmnt n Intifition of R Bloo Clls Th purpos of th work is to ount th numr of r loo lls in givn loo smpl. For this w hv ppli vrious pr-prossing thniqus lik g ttion, sptil smoothing filtring n ptiv histogrm quliztion to tt n xtrt th r loo lls from th imgs. Ftur xtrtion hs n on through th Hough Trnsform mtho whih hs n us to fin out th r loo lls s on thir sizs n thir shps. This isolts th r loo lls from th rst of th img of th loo smpl so tht furthr prosss lik ounting n ppli xlusivly on thm. Fig.1 shows fiv loo ll mirosopi imgs tkn for our stuy n fig.2 rprsnts orrsponing pr-pross gry lvl imgs. 18
Fig. 2: Pr-pross Gry Lvl Imgs Fig. 1: Originl Bloo Cll Imgs 2.2. Hough Trnsform in Ojt Dttion Th Hough trnsform[16] is ftur xtrtion thniqu us in img nlysis, omputr vision n igitl img prossing. It ws initilly suggst s mtho for lin ttion in g mps of imgs, thn xtn to tt gnrl low-prmtri ojts suh s irls [17,18].To tt stright lin in n n x n img, th simplst mtho is to omput ll possil lins fin y vry pir of points in th y i = x i +, Rwriting th qution =-x i + y i img n thn fin ll susts of points tht r los to prtiulr lin. Th omputtion involv will normous us th mximl possil lin is n(n-1)/2 ~ n 2 n thn (n) [n(n-1)]/2 ~ n 3. Comprisons n to prform for h n vry point in th img. Th prolm is solv using Hough Trnsform tht uss th prmtri sription of th shp to ru th omputtion involv. Consiring two points (x 1,y 1 ) n (x 2,y 2 ) in th x-y pln, th lin qution is: Two points r rprsnt in th x-y s wll s - pln. Th first point (x 1,y 1 ) n th son point (x 2,y 2 ) h yil lin in th - pln n oth th lins intrst t point n this is lso tru for ll th points ontin in th lin. Using this 19
uniqu ftur prmtr sp ll s th umultor ll or Hough sp is rt with -xis n -xis hving min n mx of th xpt rng. Th sm mtho us for th ttion of stright lins n lso xtn for th ttion of irl n th qution is : (x-) 2 + (y-) 2 = r 2 Th qution for irl ttion ontins thr unknowns (,,r) prmtrs n thrfor th umultor ll shoul of thr imnsionl for thr unknown vrils. Th purpos of th thniqu is to fin imprft instns of ojts within rtin lss of shps y voting prour. This voting prour is rri out in prmtr sp, from whih ojt nits r otin s lol mxim in so ll umultor sp tht is xpliitly onstrut y th lgorithm for omputing th Hough Trnsform. Any Hough Trnsform s mtho ssntilly works y splitting th input img into st of voting lmnts. Eh suh lmnt vots for th hypothss tht might hv gnrt this lmnt. Th vots from iffrnt voting lmnt pixls r togthr into Hough img, with th hight of th pk proviing th onfin of th ttion. Hough s pproh for ojt ttion is flxil s th primry voting lmnts r not rstrit to g pixls, ut n inlu intrst points [9], img pths [19,20] or img rgions[21]. Anothr ttrtiv proprty is th simpliity of th lrning prour [7]. Fig.3 shows th intifition of rs y Hough Trnsform. Fig. 3: Imgs ftr Hough trnsform 2.3. Counting Hving sussfully isolt th r loo lls w hv ppli ountr tht hs ount th numr of rs in th img fil. Howvr, loo ount in mil trms mns th numr of loo lls (r or w or pltlts) in ui millimtr of loo volum. Hn w hv u formul to lult th numr of r loo lls pr umm s on th numr of lls in th r of th givn img of th loo smpl. W hv ssum tht th thiknss of th loo smpl film is 0.1 mm whih is th stnr mil prti. This llows for n ovrlpping of mximum two lyrs in thiknss whih is th ommon trn in th imgs provi in fig.3. This formul rquirs n input for proviing th mgnifition ftor whih is th mgnifition lvl unr th mirosop t whih th img hs n tkn. W hv tkn fiv loo ll imgs for our stuy. Eh of th imgs r prpross y th ov mntion thniqus. Finlly th numr of r loo lls wr intifi n ount in h of ths imgs using Hough Trnsform. Th rsults of our stuy hv n isuss in Tl - 1 long with th iffrnt prmtrs us for h of th imgs. 3. RESULTS AND DISCUSSION Atul volum of th loo smpl is lult with propr mgnifition ftor (X n Y irtions). Now suh smpls r usully ilut with n ntiogulnt liqui to sprt th lls to rs ovrlpping. In suh ss w hv to multiply th ount y th ilution ftor. Consiring ths ftors th formul for r ount oms : Atul r ount pr umm = (r ount y Hough Trnsform / ((input img r/(mgnifition * mgnifition)*film thiknss))*ilution ftor 20
Bloo Count pr umm(in Intrntionl Journl of Computr Applitions (0975 8887) Tl 1. Rsult of RBC Count y th Propos Mtho Img Smpls Mgnifition Rius Rng (in pixl) Dilution ftor Bloo Count y th propos mtho pr umm(in 200*200 [2-14] 10 2.38 300*300 [5-18] 10 5.00 300*300 [5-14] 10 3.02 800*800 [5-25] 10 6.22 1000*1000 [5-18] 10 9.12 Tl 2. Comprison of th Rsult twn th propos mtho n th mnul mtho Img Smpls Rius Rng(in pixls) Bloo Count Mnully pr umm(in Bloo Count mthoilly pr umm(in [2-14] 2.80 2.38 [5-18] 5.82 5.00 [5-14] 3.12 3.02 [5-25] 6.40 6.22 [5-18] 9.30 9.12 10 8 6 4 2 0 Grphil Rprsnttion of R Bloo Cll Count Img Smpls Bloo Cll Count Mnully Fig. 4: Grphil Rprsnttion of th rsults It is osrv tht th rsults otin y th propos mtho offr goo onformity with th mnul ounting mtho. In our mtho, w hv lft out th lls tht r not totlly in th img fil. Howvr, in rl loo tst whr loo ount is on mnully, th prti is to ount th lls on two jnt gs of th img fil n tk h ll s on irrsptiv of how muh of it is in th img fil. It is ssum tht two opposit sis hv sm numr of suh lls. As this g orrtion hs not n onsir, in h of th smpls th ount vlus y th propos mtho r slightly lss thn th ount vlus otin mnully. Th softwr must moifi to ount thos rs to otin mor urt rsult. 4. CONCLUSION This ppr prsnts mthoology to hiv n utomt ttion n ounting of r loo lls in mirosopi imgs using Hough Trnsform. Rsults init tht th ounting of r loo ll in mirosopi imgs offr rmrkl ury. Lsr-s itomtrs r vill to ount loo lls, ut thy r not img s n stroy th loo smpls uring th nlysis. Also instlltion of suh systm is vry ostly. Our propos mtho is vry ost-fftiv n n sily implmnt in mil filitis nywhr with miniml invstmnt in infrstrutur. It n lso intify ovrlpping loo lls n ount thm sprtly. It is lso vry tim fftiv s mnul ounting is vry tious jo n tim onsuming. Howvr, th softwr must moifi to ount th fftiv numr of rs whih r prtly in th img fils to otin mor urt rsult. Furthr stuis will fous on omplt loo ll ount i.. totl ount of th numr of r loo lls, whit loo lls n pltlts in th loo smpl. This n sily on y moifying th prsnt softwr to tk into ount thir iffrnt shps n sizs. 5. ACKNOWLEDGEMENT W knowlg Univrsity Grnt Commission (UGC), Ini, for proviing finnil support to th uthors through th mjor rsrh projt Dvlopmnt of I P or for Implmnting Img Prossing Algorithms on FPGA Bor for pursuing this work. 6. REFERENCES [1] Lhmnn T.M., Win B., Dhmn J., Brno J., Voglsng F. & Kohnn M. : Contnt s img rtrivl in mil pplitions : novl multi stp pproh. Intrntionl Soity for Optil Enginring (SPIE), 3972, pp.312-320.(2000) [2] Dwi Anorgingrum : Cll sgmnttion with min filtr n mthmtil morphology oprtion, proing of th IEEE 10th Intrntionl Confrn on Img Anlysis n Prossing (ICIAP), pp. 1043-1046 (1999). [3] Kng Wu t l.: Liv ll img sgmnttion, IEEE Trns on Biomil Enginring, 42(1), pp.1-12.(1995). [4] Mrk B. Jok, Brin C. Lovll : A Multi-rsolution lgorithm for Cytologil img sgmnttion, Th son Austrlin n Nw Zln onfrn on intllignt informtion systms, 322-326 (1994). [5] Choi H, Brniuk R., Multisl : Img sgmnttion using wvlt-omin hin Mrkov mols, IEEE Trnstion on img prossing, 10(9), pp.1309-1321 (2001). [6] S.Y.Cho, T.W.S.Cho n C.T.Lung, : A nurl s row stimtion y hyri glol lrning lgorithm, IEEE Trnstion on Systms, Mn ncyrntis, Prt B, 29(4), pp.535-541(1999). [7] O. Brinov, V.Lmpitsky n P. Kohli, : On th ttion of multipl ojt instns using Hough Trnsforms, CVPR, (2010). 21
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