A Model-Based Approach for Automated Feature Extraction in Fundus Images

Transcription

1 A Model-Based Approah for Automated Feature Extraton n Fundus Images Huq L Shool of Computng Natonal Unversty of Sngapore dslhq@nus.edu.sg Opas Chutatape Shool of Eletral and Eletron Engneerng Nanyang ehnologal Unversty eopas@ntu.edu.sg Abstrat A new approah to automatally extrat the man features n olor fundus mages are proposed n ths paper. Opt dsk s loalzed by the prnpal omponent analyss (PCA) and ts shape s deteted by a modfed atve shape model (ASM). Exudates are extrated by the ombned regon growng and edge deteton. A fundus oordnate system s further set up based on the fovea loalzaton to provde a better desrpton of the features n fundus mages. he suess rates aheved are 99%, 94%, and 100% for dsk loalzaton, dsk boundary deteton, and fovea loalzaton respetvely. he senstvty and spefty for exudate deteton are 100% and 71%. he suess of the proposed algorthms an be attrbuted to the utlzaton of the model-based methods. 1. Introduton he olor fundus mages are used to keep trak of the eye dseases by ophthalmologsts. Developng automat fundus mage analyzng and dagnosng system has been the ultmate am of our researh to faltate lnal dagnoss. Extraton of the normal and abnormal features n olor fundus mages s fundamental and useful to automat understandng of fundus mages. he normal features of fundus mages nlude opt dsk, fovea and blood vessels. Exudates and hemorrhages are the man abnormal features for dabet retnopathy, whh s the leadng ause of blndness n the workng age populaton. Opt dsk s the brghtest part n the normal fundus mages, whh an be seen as a pale, round or vertally slghtly oval dsk [1]. In [2] [3], the brghtest pxels were lustered and the opt dsk was loated by the entrod of the largest luster. In [4], dsk was dentfed by the area wth the hghest varaton n ntensty of adjaent pxels. hese bottom-up methods work well n normal fundus mages, but they wll lead to wrong dsk loalzaton when there are large areas of brght lesons smlar to opt dsk. he geometral relatonshp between opt dsk and blood vessels was utlzed n the dentfaton of opt dsk n [5] [6], whh are top-down methods. he dea sounds reasonable, but t s dffult to put nto prate beause vessel deteton s a more omplated task. he hange n the shape, olor or depth of opt dsk s an ndator of varous ophthalm pathologes espeally for glauoma. he ontour of opt dsk was estmated as a rle or an ellpse n [2] [3] [7]. As the obtaned rle or ellpse wll not exatly math the dsk boundary, the exat ontour of opt dsk has been nvestgated. Snakes was proposed to detet the boundary of opt dsk n [8] [9] [10] due to ts ablty to brdge dsontnutes of the edges. he requrement of the manual ntalzaton makes t sem-automat. he man dffulty of these snakes methods s how to remove the nfluene of vessels. Exudates are one of the most ommon ourrng lesons n dabet retnopathy. he shape, brghtness and loaton of exudates vary a lot among dfferent patents. ehnques n the exudate deteton an be lassfed nto three ategores: thresholdng [3] [11] [12], edge deteton [6] [13], and lassfaton [14] [15]. he thresholdng method s straghtforward, but the automat seleton of the threshold s dffult. he man onern of the methods based on edge deteton s how to dstngush the edges of exudates from the edges of vessels and other lesons. Statstal lassfaton [15] and neural network [14] were also attempted, whh are ataloged nto the lassfaton approah. It s stll dffult for these methods to detet exudates robustly n fundus mages. Novel methods to detet opt dsk, fovea, exudates, and to set up the fundus oordnate system are proposed n ths paper. Model-based approahes are employed n the feature extraton, and the orrespondng experments are arred out to test the algorthms. 2. Methodology 2.1. Dsk loalzaton by PCA Proeedngs of the Nnth IEEE Internatonal Conferene on Computer Vson (ICCV 2003) 2-Volume Set

2 Prnpal omponent analyss (PCA) [16] [17], whh belongs to the top-down strateges, s proposed to loalze opt dsk n ths paper. he loalzaton proedure s performed on the ntensty mage. here are two steps n the loalzaton: the anddate regons are determned frst and PCA s employed only to the anddate regons to speed up the whole proessng. he pxels wth the hghest 1% gray levels n ntensty mage are seleted, whh are manly from the areas n opt dsk or brght lesons. he sngle pass method [18] s employed to luster these pxels. A luster s abandoned f the number of the pxels n t s less than 0.04% of the total pxel number of the whole mage, beause t s most lkely aused by nose or small brght lesons. A square anddate regon, whh s entered on the luster s entrod and wth the sde of 1.4 tmes the average dsk dameter, s defned for eah remanng luster. In the PCA approah, dsk spae s obtaned from the tranng mages frst. An nput mage s then projeted on the dsk spae and ts dstane from the dsk spae s alulated. A square sub-mage around the opt dsk s ropped manually to obtan a tranng mage. Sale normalzaton s performed by reszng t to N N pxels, where N s the average dsk dameter. Intensty normalzaton s next arred out by resalng the ntensty to the range of 0~255 va a smple lnear quantzaton. he PCA transform s performed on the tranng vetors, whh are n N 2 dmensons. en sub-mages are employed as the tranng set here and the frst sx egenvetors orrespondng to the largest sx egenvalues are seleted. hese sx egenvetors an represent 90% of the total varane n the tranng set. he subspae defned by these egenvetors s referred to as dsk spae. For eah pxel n the anddate regons n an nput mage, an N N sub-mage wth the pxel as the enter s obtaned automatally. he ntensty normalzaton s arred out before the sub-mage s projeted onto the dsk spae by the PCA transformaton. he dstane from dsk spae, whh measures the lkelness of opt dsk, s defned as the Euldean dstane between the sub-mage and ts reonstruton onto the dsk spae. Sne the sze of opt dsk vares among ndvduals, PCA wth dfferent sales (0.8~1.2) s appled. hus an nput sub-mage s ompared wth the egendsks at a number of sales. he pxel (L x, L y ) wth the mnmum dstane n all the anddate regons and among all the sales s loated as the dsk enter. he approxmate sze of the dsk n a testng mage an be obtaned as well Dsk boundary deteton by a modfed ASM Some parts of the dsk boundary are not well defned and some parts are partly obsured by blood vessels n fundus mages, whh make the deteton of dsk shape omplated. A modfed atve shape model (ASM), whh s a parametr deformable model, s proposed to detet the dsk boundary n ths paper. he ASM method [19] [20] s a searhng proedure to ft the pont dstrbuton model (PDM) n a new mage to fnd the modeled objet. A shape of opt dsk s represented by the poston of n (n = 48) landmark ponts (see Fg. 1). he eght tranng shapes are algned by a transformaton that nludes translaton, rotaton and salng. he algnment s performed by mnmzng the Euldean dstane between the shapes usng a routne least square approah. PCA s next performed on the algned tranng shapes. A shape model an be represented by x = x + Φ b (1) where x s the mean shape of the algned tranng set, b = b, b,, ) s termed shape parameter vetor, ( 1 2 Κ b t 2n t t R and Φ = ( Φ1, Φ 2, Κ, Φ ) s the set of egenvetors orrespondng to the largest t egenvalues of the ovarane matrx of the tranng shapes. he frst four egenvetors are seleted (t = 4) n our applaton. he model obtaned n Eq. (1) s termed as PDM. It s a statstal desrpton of the dsk shape and ts varatons of the tranng set. Fgure 1. A shape nstane he spae defned by the nput mage s referred to as mage spae and the spae desrbed by Eq. (1) s termed as shape spae. he varables n the shape spae and the mage spae are denoted by the lowerase and upperase respetvely n ths paper. he transformaton between the two spaes s defned by s osθ s snθ x = = + t x X ( x) (2) s snθ s osθ y t y where x and X are the shape models n the shape spae and mage spae respetvely. x, y denote the oordnates of the th landmark pont n the shape spae. t, represent the poston of the model enter n the x t y Proeedngs of the Nnth IEEE Internatonal Conferene on Computer Vson (ICCV 2003) 2-Volume Set

3 mage spae. τ s, θ, t x, t ) determnes the transformaton ( y between the two spaes, whh s termed as pose parameter. he frst step n ASM s ntalzaton. he dsk loalzaton ( Lx, Ly ) and the mean shape are utlzed to ntalze the shape model n the mage spae aordng to Eq. (2), where x = x, s = 1, θ = 0, t x = Lx, t y = Ly. Mathng pont deteton s the seond task. he frst dervatve of the ntensty dstrbuton along the normal profle s employed to fnd the mathng pont for eah landmark pont. A blood vessel s dentfed by a negatve pulse followed by a postve pulse wthn the wdth range of vessels, and there s a sngle negatve pulse where dsk edge appears. he last part of ASM s parameter update. he pose parameter τ ( s, θ, t x, t y ) an be updated by mnmzng the followng expresson, Eτ = ( Y ( x) ) ( Y ( x) ) (3) where Y s the set of mathng ponts n the mage spae. he nverse transformaton s used to transform the mathng ponts Y n the mage spae bak to y n the shape spae. he shape parameter b s updated by projetng the mathng ponts y onto the shape spae. b = Φ ( y x) (4) he onstrton of b 3 λ s appled to b so that a new shape wll be smlar to those n the tranng set, where λ s the th largest egenvalue. Fnally the shape model s updated n the shape spae and n the mage spae aordng to Eq. (1) and Eq. (2) respetvely. he proedure of mathng pont deteton and parameter update s terated untl the shape model X s onverged. he orgnal ASM s mproved n two aspets to elmnate the nfluene of the msplaed mathng ponts: addng the self-adjustng weght and exluson of the outlyng ponts. hese two modfatons make the algorthm more favorable for the ases of weak edges. Weght fator s added to Eq. (3), n Eτ = ( Y X ) W ( Y X ) (5) = 1 where Y and X are the postons of the th mathng pont and the th model pont n the mage spae respetvely, and W s the weght fator. he transform for algnment s performed twe n eah teraton: one wth the ntalzed weght W and one wth the adjusted W. he ntalzaton of followng. 1 W = Y s deteted dretly Y s updated by X W s expressed as the Y s estmated by nearby mathng ponts (6 ) W s set to zero to elmnate the effet of Y when Y annot be deteted and the nearby mathng ponts annot be deteted ether. W s adjusted as the followng, whh s a negatve feedbak. 1 E < 5 W = 5 / E 5 E 15 (7) 1/ E E > 15 where E s the Euldean dstane between the mathng pont Y and the updated landmark ponts X. he pose parameter τ n the teraton s fnally obtaned by mnmzng Eq. (5) wth the adjusted weght fator. Another modfaton s exludng outlyng ponts n the update of the shape parameter b. In eah teraton, the shape parameter b s obtaned n the same way as the orgnal ASM frst. A mathng pont s onsdered to be an outlyng pont or msplaed mathng pont when E between the mathng pont Y and the updated landmark pont X s larger than a onstant value. hose outlyng ponts wll not be used n obtanng shape parameter b, ~ b = Φ ( ~ y ~ x) (8) where n m s the number of the outlyng ponts, t ~ 2 ( n ) t ~ 2( n ) ~, 2( n n ), nm b R R, y R nm Φ x R m. ~ y, ~ ~ Φ, x orrespond to y, Φ and x n Eq. (4). he fnal shape model s estmated from Eq. (1) by reonstrutng the shape model n 2n-D spae wth the same parameter b obtaned from Eq. (8) Foveal oordnate system establshment he loatons of lesons are as mportant as ther sze and number to ophthalmologsts [21]. A polar fundus oordnate system s establshed based on the fovea loalzaton to desrbe the spatal loatons of the features n fundus mages. he fovea s the darkest part n most fundus mages, whle t s not obvous n some mages due to hgh llumnaton or beng overed by the lesons. It s stuated about 2DD (DD = dsk dameter) temporal to the opt dsk n fundus mages [1]. he man ourses of blood vessels are extrated by the modfed ASM ntrodued n seton 2.2. hey are represented by thrty landmark ponts (see Fg. 4(a)). Eght landmark sets are utlzed to derve PDM and the frst four egenvetors are hosen. Observng the man ourses of blood vessels, ts shape s roughly a parabol urve. he extraton result s ftted to a parabola for the future loalzaton of fovea. A generalzed parabola an be desrbed as: [( x x )snθ + ( y y ) osθ ] 2 = 2 p[( x x ) osθ ( y y ) snθ ] (9) Proeedngs of the Nnth IEEE Internatonal Conferene on Computer Vson (ICCV 2003) 2-Volume Set

4 where p/2 s the foal length, ( x, y ) s the vertex, and θ s the rotaton of the dretrx. Four parameters ( p, x, y, θ ) need to be estmated. he deas of Hough transform and lnear least square fttng are ombned n the urve fttng. he rotaton θ s quantzed to elmnate the nonlnear relatonshp between parameters. he vertex an be approxmated at half opt dsk radus nasal to opt dsk, thus the parabol fttng s smplfed as estmatng the only varable p by the least square fttng. he anddate regon of fovea s defned as a rle area. Its enter s loated at 2DD from the dsk enter along the man axs of the ftted parabola and ts radus s set as 1DD. he pxels wth the lowest ntensty n the anddate regon are seleted, the sum of whh s the area of opt dsk, beause the fovea s about the same sze as opt dsk [1]. hese pxels are lustered by the sngle pass method [18]. he mean ntensty of eah luster s alulated and the lowest two are ompared. As the fovea s not obvous n some mages, the omparson s to avod mstakng the perpheral area, where the llumnaton s relatvely dark, as fovea. When the dfferene s obvous and the number of pxels n the luster s greater than 1/6 dsk area, the foveal enter s loated by the entrod of the luster wth the lowest mean ntensty, otherwse t s estmated at the enter of the anddate regon. A polar oordnate system entered on the fovea s seleted n our work aordng to the EDRS report [21]. A fundus mage s dvded nto 10 sub-felds by three fovea-entered rles wth the rad of 1 3 DD, 1DD, and 2DD respetvely. he 10 sub-felds are defned as: (1) entral sub-feld wthn the nner rle; (2) four nner sub-felds between the nner and mddle rles; (3) four outer sub-felds between the mddle and outer rles; (4) far temporal sub-feld temporal to the outer rle Exudate deteton Luv s seleted as the sutable olor spae for exudate deteton [22]. As the llumnaton n fundus mages s not homogeneous, a fundus mage s dvded nto sxty-four sub-mages. Exudate deteton s performed n eah submage. he olor dfferene of an objet an be defned as: 2 2 D(, = ( L(, Lr ) + ( u(, u r ) (10) where L (, and u (, are the olors of pxel (, n the omponent L and u respetvely. L r and u r are the referene olors of the objet. he referene olor s determned as the gravty enter of the objet [22]. Mean squared Wener flter s performed to remove nose. A ombned method of regon growng and edge deteton, whh nludes seed seleton, edge deteton and growng rtera, s employed here to detet the exudates. It s noted that some loal mnma are from the retnal bakground sne the retnal bakground s uneven. Loal mnma below a ertan threshold are hosen as the seeds. he edges n a sub-mage are deteted by the Canny edge detetor. As some weak edges stll annot be deteted, other features are examned besdes hekng f the regon has reahed an edge. hree rtera are employed: (a) he gradent of the pxel s lower than a threshold 1 ; (b) he dfferene between the pxel value and the mean value of the regon s lower than a threshold 2 ; () he dfferene between the pxel value and the value of the seed s lower than a threshold Results and dsusson Eghty-nne olor fundus mages were obtaned. hrty-fve mages were provded by the Sngapore Natonal Eye Center (SNEC). hrty are from another hosptal. Another eghteen were aptured by us, and the other sx were downloaded from the Internet. All the mages were reszed to pxels and saved as 24- bt Btmap. An example of the proessng result s llustrated n Fg. 2. he ds loalzaton algorthm was tested by all the eghty-nne mages. he thrty-fve mages from SNEC were used as the testng mages for the other proposed algorthms, as verfaton from ophthalmologsts s only avalable for ths bath of mages. he suess rates aheved are 99%, 94%, and 100% for dsk loalzaton, dsk boundary deteton, and fovea loalzaton respetvely. he senstvty and spefty for exudate deteton are 100% and 71% orrespondngly. he detals of the result are explaned as the followngs. Opt dsk Fgure 2. An example of proessng result 3.1. Dsk loalzaton Fundus oordnates Fovea Exudates Proeedngs of the Nnth IEEE Internatonal Conferene on Computer Vson (ICCV 2003) 2-Volume Set

5 Even though the ten tranng mages are all obtaned from the mages provded by SNEC, satsfatory results ould be aheved when the testng mage are from other soures. he proposed algorthm faled n only one of the testng mages, beause there s a large area of lesons around the opt dsk n that mage and there s no suh ase n the tranng set. More onstrants suh as hekng the onvergene of the blood vessel network ould be added to valdate the loalzaton of opt dsk. he suess rate of opt dsk loatng proess s thus 99% based on the eghty-nne mages tested. Fg. 4 shows an example of the deteted vessel ourses and the parabola fttng result. he fovea s deteted dretly by the entrod of the darkest luster n twentyone of the testng mages. It s estmated n the other fourteen mages. he loalzaton of the fovea s wthn the regon of fovea n all these thrty-fve mages. But the loalzaton devates slghtly from the apparent enter n three of the mages when evaluated by the human eyes. he loalzaton of fovea s estmated n all of these three mages. he reason of the devaton s that the estmaton may not be prese Dsk boundary deteton he auray of the obtaned shape s evaluated by omparson wth a referene shape labeled manually. Mean absolute dstane (MAD) [23] s hosen here to ndate the dfferene of the two shapes. An example s shown n Fg. 3. he boundares obtaned by the orgnal ASM and the modfed ASM are represented by the dots n the fgure. It an be seen that the boundary at the upper part annot be deteted orretly by the orgnal ASM. However, the modfed ASM ould obtan a more sutable result. hrty-fve mages were tested. he modfed ASM deteted the dsk boundary suessfully n thrty-three mages, whle the orgnal ASM faled n seven of them. In the twenty-sx mages where both methods sueeded, the modfed ASM also aheved better or at least as good as the results of ASM. he modfed ASM needs less teratons n all the mages exept two ases. he omparson shows that the modfed ASM an gve more robust result than the orgnal ASM espeally when there are several msplaed mathng ponts and also onverges faster. (a) Result of vessel extraton (b) Result of parabola fttng Fgure 4. he deteted vessel and parabola fttng 3.4. Exudate deteton In the thrty-fve testng mages, seven mages were dentfed to have no exudate by ophthalmologsts. he presene of exudates was suessfully deteted n all the twenty-eght mages. However, exudates were deteted by our algorthm n two mages n whh no exudate s present. he senstvty and spefty s 100% and 71% respetvely. Fg. 5 shows two examples of exudate deteton. he deteted exudates are represented by the whte olor n the fgure, where foveal fundus oordnates are overlad. hough the total number and area of exudates n Fg. 5(a) are both larger than the exudates n Fg. 5(b), the exudates n Fg. 5(b) have more harm to the vson than those n Fg. 5(a). he exudates wthn the nner rle wll affet the vson of patents more than the exudates n other loatons. hs onluson has been verfed by the ophthalmologsts. hus the dstrbuton of exudates needs to be analyzed to ndate the severty of the retnal dseases. (a) Result by ASM (b) Result by the modfed ASM Fgure 3. Boundary deteted by the ASM and the modfed ASM. x ndates the referene shape Foveal oordnate system establshment (a) (b) Proeedngs of the Nnth IEEE Internatonal Conferene on Computer Vson (ICCV 2003) 2-Volume Set

6 Fgure 5. Examples of exudate deteton 4. Conluson he algorthms to extrat features automatally and robustly n olor fundus mages were proposed n ths paper. PCA s employed to loate opt dsk; A modfed ASM s proposed n the shape deteton of opt dsk; A fundus oordnate system s establshed based on the fovea loalzaton; An approah to detet exudates by the ombned regon growng and edge deteton s proposed. he suess rates of dsk loalzaton, dsk boundary deteton, and fovea loalzaton are 99%, 94%, and 100% respetvely. he senstvty and spefty of the exudate deteton are 100% and 71% orrespondngly. he suess of the proposed algorthms an be attrbuted to the utlzaton of the model-based methods. he satsfatory feature deteton ould make the automat analyzng system beome more relable. he generalzaton of the models ould be mproved when larger data soure s avalable. Further tests should be arred out on the proposed algorthms to make them ultmately aeptable for lnal purposes. 5. Referenes [1] H. W. Larsen, he Oular Fundus: a Color Atlas, Munksgaard, Copenhagen, 1976, pp [2] S. amura, Y. Okamoto and K. Yanashma, Zerorossng nterval orreton n trakng eye-fundus blood vessels, Pattern Reognton, Vol. 21, No. 3, 1988, pp [3] Z. Lu, O. Chutatape and S. M. Krshnan, Automat mage analyss of fundus photograph, Proeedngs of the Internatonal Conferene of the IEEE Engneerng n Medne and Bology Soety, Vol. 2, 1997, pp [4] C. Snthanayothn, J. F. Boye, H. L. Cook and. H. Wllamson, Automated loaton of the opt dsk, fovea, and retnal blood vessels from dgtal olour fundus mages, Brtsh Journal of Ophthalmology, Vol. 83, No. 8, 1999, pp [5] G. Zahlmann, B. Kohner, I. Ug, D. Shuhmann, B. Lesenfeld, A. Wegner, M. Obermaer and M. Mertz, Hybrd fuzzy mage proessng for stuaton assessment, IEEE Engneerng n Medne and Bology, 2000, pp [6] K. Akta and H. Kuga, A omputer method of understandng oular fundus mages, Pattern Reognton, Vol. 15, No. 6, 1982, pp [7] M. Lalonde, M. Beauleu and L. Gagnon, Fast and robust opt dsk deteton usng pyramdal deomposton and Hausdorff-based template mathng, IEEE ransatons on Medal Imagng, Vol. 20, No. 11, 2001, pp [8] S. Lee and L. M. Brady, Integratng stereo and photometr stereo to montor the development of glauoma, Proeedngs of the Brtsh Mahne Vson Conferene, 1990, pp [9] D.. Morrs and C. Donnson, Identfyng the neuroretnal rm boundary usng dynam ontours, Image and Vson Computng, Vol. 17, 1999, pp [10] F. Mendels, C. Heneghan and J. P. hran, Identfaton of the opt dsk boundary n retnal mages usng atve ontours, Proeedngs of the Irsh Mahne Vson and Image Proessng Conferene, 1999, pp [11] N. P. Ward, S. omlnson and C. J. aylor, Image analyss of fundus photographs. he deteton and measurement of exudates assoated wth dabet retnopathy, Ophthalmology, Vol. 96, 1989, pp [12] R. Phllps, J. Forrester, P. Sharp, Automated deteton and quantfaton of retnal exudates, Graefe s Arhve for Clnal and Expermental Ophthalmology, Vol. 231, 1993, pp [13] H. L and O. Chutatape, Fundus mage features extraton, Proeedngs of the 22nd Annual Internatonal Conferene of the IEEE Engneerng n Medne and Bology Soety, Vol. 4, 2000, pp [14] G. G. Gardner, D. Keatng,. H. Wllamson, and A.. Ellott, Automat deteton of dabet retnopathy usng an artfal neural network: A sreenng tool, Brtsh Journal of Ophthalmology, Vol. 80, No. 11, 1996, pp [15] H. Wang, W. Hsu, K. G. Goh, and M. L. Lee, An effetve approah to detet lesons n olor retnal mages, Proeedngs of IEEE Computer Soety Conferene on Computer Vson and Pattern Reognton, 2000, pp [16] M. urk and A. Pentland, Egenfaes for reognton, Journal of Cogntve Neurosene, Vol. 3, No. 1, 1991, pp [17] H. L, O. Chutatape, Automat deteton and boundary estmaton of the opt dsk n retnal mages usng a modelbased approah, Journal of Eletron Imagng, Vol. 12, No. 1, 2003, pp [18] D. R. Hll, A vetor lusterng tehnque, Mehanzed Informaton Storage, Retreval and Dssemnaton, North- Holland, Amsterdam, [19]. F. Cootes, C. J. aylor, D. H. Cooper and J. Graham, Atve shape models-her tranng and applaton, Computer Vson and Image Understandng, vol. 61, No. 1, 1995, pp [20] H. L, O. Chutatape, Boundary deteton of opt dsk by a modfed ASM method, Pattern Reognton, Vol. 36, No. 9, 2003, pp [21] EDRS Report Number 10, Gradng dabet retnopathy from stereosop olor fundus photographs - An extenson of the modfed Arle house lassfaton, Ophthalmology, Vol. 98, 1991, pp [22] G. Luo, O. Chutatape, H. L and S. M. Krshnan, Abnormalty deteton n automated mass sreenng system of dabet retnopathy, Proeedngs of 14th IEEE Symposum on Computer-Based Medal Systems, 2001, pp [23] V. Chalana, D.. Lnker, D. R. Haynor and Y. Km, A multple atve ontour model for arda boundary deteton on ehoardograph sequenes, IEEE ransatons on Medal Imagng, Vol. 15, No. 3, 1996, pp Proeedngs of the Nnth IEEE Internatonal Conferene on Computer Vson (ICCV 2003) 2-Volume Set