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Geometric Methods in Bio-Medical Image Processing (Paperback, Softcover reprint of the original 1st ed. 2002)
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Geometric Methods in Bio-Medical Image Processing (Paperback, Softcover reprint of the original 1st ed. 2002)
Series: Mathematics and Visualization
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Itgivesmegreatpleasuretoeditthisbook. Thegenesisofthisbookgoes
backtotheconferenceheldattheUniversityofBolognainJune1999,on
collaborativeworkbetweentheUniversityofCaliforniaatBerkeleyandthe
UniversityofBologna. Theoriginalideawastoinvitesomespeakersatthe
conferencetosubmitarticlestothebook. Thescopeofthebookwaslater-
hancedand,inthepresentform,itisacompilationofsomeoftherecentwork
usinggeometricpartialdi?erentialequationsandthelevelsetmethodology
inmedicalandbiomedicalimageanalysis.
Thesynopsisofthebookisasfollows:Inthe?rstchapter,R. Malladi andJ.
A. Sethianpointtotheoriginsoftheuseoflevelsetmethodsand
geometricPDEsforsegmentation,andpresentfastmethodsforshapes-
mentationinbothmedicalandbiomedicalimageapplications. InChapter
2,C. OrtizdeSolorzano,R. Malladi,andS. J. Lockettdescribeabodyof
workthatwasdoneoverthepastcoupleofyearsattheLawrenceBerkeley
NationalLaboratoryonapplicationsoflevelsetmethodsinthestudyand
understandingofconfocalmicroscopeimagery. TheworkinChapter3byA.
Sarti,C. Lamberti,andR. Malladiaddressestheproblemofunderstanding
di?culttimevaryingechocardiographicimagery. Thisworkpresentsvarious
levelsetmodelsthataredesignedto?tavarietyofimagingsituations,i. e.
timevarying2D,3D,andtimevarying3D. InChapter4,L. VeseandT. F.
Chanpresentasegmentationmodelwithoutedgesandalsoshowextensions
totheMumford-Shahmodel. Thismodelisparticularlypowerfulincertain
applicationswhencomparisonsbetweennormalandabnormalsubjectsis-
quired. Next,inChapter5,A. EladandR. Kimmelusethefastmarching
methodontriangulateddomaintobuildatechniquetounfoldthecortexand
mapitontoasphere. Thistechniqueismotivatedinpartbynewadvances
infMRIbasedneuroimaging. InChapter6,T. DeschampsandL. D. Cohen
presentaminimalpathbasedmethodofgroupingconnectedcomponentsand
showcleverapplicationsinvesseldetectionin3Dmedicaldata. Finally,in
Chapter7,A. Sarti,K. Mikula,F. Sgallari,andC. Lamberti,describean-
linearmodelfor?lteringtimevarying3Dmedicaldataandshowimpressive
resultsinbothultrasoundandechoimages.
IoweadebtofgratitudetoClaudioLambertiandAlessandroSartifor
invitingmetoBologna,andlogisticalsupportfortheconference. Ithank
thecontributingauthorsfortheirenthusiasmand?exibility,theSpringer
mathematicseditorMartinPetersforhisoptimismandpatience,andJ. A.
Sethianforhisunfailingsupport,goodhumor,andguidancethroughthe
years. Berkeley,California R. Malladi October,2001 Contents 1
FastMethodsforShapeExtractioninMedicaland BiomedicalImaging...1 R.
Malladi,J. A. Sethian 1. 1Introduction...1 1.
2TheFastMarchingMethod...3 1. 3ShapeRecoveryfromMedicalImages...6
1. 4Results...10 References...13 2
AGeometricModelforImageAnalysisinCytology...19 C.
OrtizdeSolorzano,R. Malladi,,S. J. Lockett 2. 1Introduction...19 2.
2GeometricModelforImageAnalysis...20 2. 3SegmentationofNuclei...22
2. 4SegmentationofNucleiandCellsUsingMembrane-RelatedProtein
Markers...31 2. 5Conclusions...37 References...38 3
LevelSetModelsforAnalysisof2Dand3D EchocardiographicData...43 A.
Sarti,C. Lamberti,R. Malladi 3. 1Introduction...43 3.
2TheGeometricEvolutionEquation...45 3. 3TheShock-TypeFiltering...46
3. 4ShapeExtraction...49 3. 52DEchocardiography...52 3.
62D+timeEchocardiography...53 3. 73DEchocardiography...56 3.
83D+timeEchocardiography...58 3. 9Conclusions...59 References...61
4 ActiveContourandSegmentationModelsusing
GeometricPDE'sforMedicalImaging...63 T. F. Chan,L. A. Vese 4.
1Introduction...63 4. 2DescriptionoftheModels...64 4.
3ApplicationstoBio-MedicalImages...68 4. 4ConcludingRemarks...68
References...7 0 VIII Contents 5
SphericalFlatteningoftheCortexSurface...77 A. Elad(Elbaz),R. Kimmel
5. 1Introduction...77 5.
2FastMarchingMethodonTriangulatedDomains...80 5.
3Multi-DimensionalScaling...80 5. 4CortexUnfolding...84 5.
5Conclusions...86 References...86 6
GroupingConnectedComponentsusingMinimalPath Techniques...91 T.
Deschamps,L. D. Cohen 6. 1Introduction...91 6.
2MinimalPathsin2Dand3D...93 6.
3FindingContoursfromaSetofConnectedComponentsR...96 k 6.
4FindingaSetofPathsina3DImage...102 6. 5Conclusion...103
References...104 7 NonlinearMultiscaleAnalysisModelsforFilteringof
3D+TimeBiomedicalImages...107 A. Sarti,K. Mikula,F. Sgallari,C.
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