Handbook of Medical Image Processing and Analysis Academic Press Series in Biomedical Engineering; 2. Ed. PDF
Preview Handbook of Medical Image Processing and Analysis Academic Press Series in Biomedical Engineering; 2. Ed.
AcademicPressisanimprintofElsevier 30CorporateDrive,Suite400,Burlington,MA01803,USA 525BStreet,Suite1900,SanDiego,California92101-4495,USA 84Theobald’sRoad,LondonWC1X8RR,UK (cid:3) Thisbookisprintedonacid-freepaper. ∞ Copyright©2009,ElsevierInc.Allrightsreserved. Copyrightexceptions: Chapters43and48areinthepublicdomainandnotsubjecttoElsevier’scopyright. Chapters54,55,and56arereprintedfromthefirstedition,copyright©2000AcademicPress. Nopartofthispublicationmaybereproducedortransmittedinanyformorby anymeans,electronicormechanical,includingphotocopy,recording,orany informationstorageandretrievalsystem,withoutpermissioninwritingfromthe publisher. PermissionsmaybesoughtdirectlyfromElsevier’sScience&TechnologyRights DepartmentinOxford,UK:phone:(+44)1865843830,fax:(+44)1865853333, E-mail:[email protected] viatheElsevierhomepage(http://elsevier.com),byselecting“Support&Contact” then“CopyrightandPermission”andthen“ObtainingPermissions.” LibraryofCongressCataloging-in-PublicationData Applicationsubmitted BritishLibraryCataloguing-in-PublicationData AcataloguerecordforthisbookisavailablefromtheBritishLibrary. ISBN:978-0-12-373904-9 ForinformationonallAcademicPresspublications visitourWebsiteatwww.books.elsevier.com PrintedintheUnitedStatesofAmerica 09 10 11 12 13 14 15 16 5 4 3 2 1 Typesettedby: diacriTech,India. Foreword Thedevelopmentofmedicalimagingoverthepastfourdecades employed broadly through many applications using all of the has been truly revolutionary. For example,in cardiology spe- digitalimagingmodalities.Andfinally,thewidespreadavailabil- cializedthree-dimensionalmotionestimationalgorithmsallow ityofmedicalimagesindigitalformathasspurredthesearchfor myocardialmotionandstrainmeasurementsusingtaggedcar- efficientandeffectiveimagecompressionandcommunication diacmagneticresonanceimaging.Inmammography,shapeand methods. textureanalysistechniquesareusedtofacilitatethediagnosisof Advancing the frontiers of medical imaging requires the breastcancerandassessitsrisk.Three-dimensionalvolumetric knowledge and application of the latest image manipulation visualizationofCTandMRIdataofthespine,internalorgans methods.InHandbookofMedicalImageProcessingandAnalysis, and the brain has become the standard for routine patient Dr. Bankman has assembled a comprehensive summary of diagnosticcare. the state-of-the-art in image processing and analysis tools for What is perhaps most remarkable about these advances in diagnostic and therapeutic applications of medical imaging. medicalimagingisthefactthatthechallengeshaverequiredsig- Chapterscoverabroadspectrumoftopicspresentedbyauthors nificantinnovationincomputationaltechniquesfornearlyall who are highly expert in their respective fields. For all those aspectsofimageprocessinginvariousfields.Theuseofmulti- who are working in this exciting field, the Handbook should pleimagingmodalitiesonasinglepatient,forexampleMRIand becomeastandardreferencetextinmedicalimaging. PET, requires sophisticated algorithms for image registration and pattern matching. Automated recognition and diagnosis WilliamR.Brody require image segmentation,quantification and enhancement President,JohnsHopkins tools.Algorithmsforimagesegmentationandvisualizationare University xvi Contributors M.StellaAtkins EdmundY.S.Chao JohnJ.Elias SchoolofComputingScience DepartmentofOrthopaedicSurgery BiomechanicsLaboratory SimonFraserUniversity JohnsHopkinsUniversity MedicalEducationand Burnaby,BCV5A1S6,Canada Chapter20 ResearchInstituteofColorado Chapter11 Chapter20 PamelaCosman NicholasAyache JoanE.Fetter DepartmentofElectricalandComputer AsclepiosResearchProject AppliedPhysicsLaboratory Engineering INRIASophiaAntipolis,France JohnsHopkinsUniversity UniversityofCaliforniaatSanDiego Chapters18,34 Laurel,MD20723 LaJolla,CA92093-0407 Chapter49 IsaacN.Bankman Chapters54,55,56 KurtW.Fleischer AppliedPhysicsLaboratory JohnsHopkinsUniversity FabriceCrivello PixarAnimationStudios Laurel,MD20723 Grouped’ImagerieNeurofonctionelle(GIN) Richmond,CA94804 Chapter15 UniversitédeCaen Chapter13 GIPCyceron PeterT.Fox AlanH.Barr 14074CaenCedex,France ResearchImagingCenter ComputerGraphicsLaboratory Chapter31 UniversityofTexasHealthScienceCenterat DepartmentofComputerScience SanAntonio DivisionofEngineeringandAppliedScience MagnusDahlbom SanAntonio,TX78232 CaliforniaInstituteofTechnology DivisionofNuclearMedicine Chapter38 Pasadena,CA91125 DepartmentofMolecularandMedical Chapter13 Pharmacology FrankJ.Frassica JamesC.Bezdek UCLASchoolofMedicine DepartmentofOrthopaedicSurgery LosAngeles,CA90095-6942 JohnsHopkinsUniversity ComputerScienceDepartment Chapter30 Chapter20 UniversityofWestFlorida Pensacola,FL32514 AlbertoF.Goldszal Chapter6 ChristosDavatzikos ImagingSciencesProgram,ClinicalCenter UniversityofPennsylvania NationalInstitutesofHealth ThierryBlu Chapter17 Bethesda,MD20892 SwissFederalInstituteofTechnology-Lausanne Chapter12 EPFL/DMT/IOA/BiomedicalImagingGroup DominikR.Dersch CH-1015Lausanne,Switzerland RobertGray CruxCybernetics Chapter28 Sydney,Australia StanfordUniversity NormanF.Boyd Chapter7 PaloAlto,CA Chapters54,55,56 DivisionofClinicalEpidemiologyandBiostatistics OntarioCancerInstitute QuentinE.Dolecek EricGrimson Toronto,ON,Canada AppliedPhysicsLaboratory ArtificalIntelligenceLaboratory Chapter23 JohnsHopkinsUniversity MassachusettsInstituteofTechnology Laurel,MD20723 Cambridge,MA02139 JeffreyW.Byng Chapter49 Chapter42 HealthImaging EastmanKodakCompany NobuhikoHata JamesS.Duncan Toronto,ON,Canada SurgicalPlanningLaboratory ImageProcessingandAnalysisGroup Chapter21 DepartmentofRadiology DepartmentsofDiagnosticRadiologyand Brigham&Women’sHospital TobiasC.Cahoon ElectricalEngineering HarvardMedicalSchool YaleUniversity ComputerScienceDepartment Boston,MA02115 NewHaven,CT06520-8042 UniversityofWestFlorida Chapters6,21 Chapter9 Pensacola,FL32514 Chapter6 DavidJ.Hawkes WilliamF.Eddy RadiologicalSciences AmitChakraborty DepartmentofStatistics King’sCollegeLondon SiemensCorporateResearch CarnegieMellonUniversity Guy’sHospital Princeton,NJ08540 Pittsburgh,PA15213 LondonSE19RT,UnitedKingdom Chapter9 Chapter40 Chapter37 xvii xviii Contributors DerekL.G.Hill MarcJoliot JackL.Lancaster RadiologicalSciences Grouped’ImagerieNeurofonctionelle(GIN) ResearchImagingCenter King’sCollegeLondon UniversitédeCaen UniversityofTexasHealthScienceCenterat Guy’sHospital GIPCyceron SanAntonio LondonSE19RT,UnitedKingdom 14074CaenCedex,France SanAntonio,TX78232 Chapter37 Chapter31 Chapter38 RobertL.Holland ArieE.Kaufman YardenLivnat AppliedPhysicsLaboratory DepartmentofComputerScience CenterforScientificComputingandImaging JohnsHopkinsUniversity StateUniversityofNewYorkatStonyBrook DepartmentofComputerScience Laurel,MD20723 StonyBrook,NY11794-4400 UniversityofUtah Chapter49 Chapter46 SaltLakeCity,UT84112 Chapter47 Sung-Cheng(Henry)Huang WilliamS.Kerwin DivisionofNuclearMedicine UniversityofWashington Shyh-LiangLou DepartmentofMolecularandMedical DepartmentofRadiology LaboratoryforRadiologicalInformatics Pharmacology Seattle,WA98159 DepartmentofRadiology UCLASchoolofMedicine Chapter26 UniversityofCaliforniaatSanFrancisco LosAngeles,CA90095-6942 SanFrancisco,CA94903 Chapter30 RonKikinis Chapter50 DepartmentofRadiology H.K.Huang HarvardMedicalSchool BlairT.Mackiewich DepartmentofRadiology Brigham&Women’sHospital SchoolofComputingScience ChildrensHospitalofLosAngeles/University BostonMA,USA SimonFraserUniversity ofSouthernCalifornia Chapters2,21,42 Burnaby,BCV5A1S6,Canada LosAngeles,CA90027 Chapter11 Chapter57 RobertKnowlton EpilepsyCenter BernardMazoyer WalterHuda UniversityofAlabamaSchoolofMedicine Grouped’ImagerieNeurofonctionelle(GIN) Director,RadiologicalPhysics Birmingham,AL35205 UniversitédeCaen DepartmentofRadiology Chapter41 GIPCyceron SUNYUpstateMedicalUniversity 14074CaenCedex,France Syracuse,NY13210 HansKnutsson Chapter31 Chapter3 DepartmentofElectricalEngineering LinköpingUniversity TimMcInerney NozomuInoue ComputerVisionLaboratory DepartmentofComputerScience DepartmentofOrthopaedicSurgery Linköping,Sweden RyersonUniversity JohnsHopkinsUniversity Chapter2 Toronto,ONM5S3H5,Canada Chapter20 Chapter8 JensKordelle PeterJezzard KlinikundPoliklinikfürOrthopädie MichaelB.Millis FMRIBCentre undOrthopädischeChirurgie DepartmentofOrthopaedicSurgery DepartmentofClinicalNeurology UniversitätsklinikumGiessen Children’sHospital UniversityofOxford Germany Boston,MA02115 UnitedKingdom Chapter21 Chapter21 Chapter29 VassiliA.Kovalev YuleiJiang CentreforVision,SpeechandSignal RichardOlshen DepartmentofRadiology Processing,UniversityofSurrey StanfordUniversity TheUniversityofChicago GuildfordGU27XH PaloAlto,CA Chicago,IL60637 UnitedKingdom Chapters54,55,56 Chapter24 Chapter14,16 NaelF.Osman RogerJohnson DavidH.Laidlaw CenterforImagingScience BiodesignInstitute ComputerScienceDepartment DepartmentofRadiology ArizonaStateUniversity BrownUniversity JohnsHopkinsUniversity Chapter19 Providence,RI02912 Baltimore,MD21287 Chapter13 Chapter26 ChristopherR.Johnson CenterforScientificComputingandImaging AndrewLaine RamanB.Paranjape DepartmentofComputerScience DepartmentofBiomedicalEngineering ElectronicSystemsEngineering UniversityofUtah ColumbiaUniversity UniversityofRegina SaltLakeCity,UT84112 NewYork,NY10027 Regina,SASKS4S0A2,Canada Chapter47 Chapter3 Chapter1,53 Contributors xix StevenG.Parker RichardA.Robb PaulM.Thompson CenterforScientificComputingandImaging Director,BiomedicalImagingResource DepartmentofNeurology DepartmentofComputerScience MayoFoundation LabofNeuro-ImagingandBrainMapping UniversityofUtah Rochester,MN55905 Division SaltLakeCity,UT84112 Chapter45 UCLASchoolofMedicine Chapter47 LosAngeles,CA90095-1769 JadwigaRogowska Chapters39,43 SotirisPavlopoulos McLeanBrainImagingCenter InstituteofCommunicationandComputer HarvardMedicalSchool ArthurW.Toga Systems Belmont,MA02478 DepartmentofNeurology NationalTechnicalUniversityofAthens Chapter5 LabofNeuro-ImagingandBrainMapping Athens157-73,Greece Division Chapter15 RobertT.Schultz UCLASchoolofMedicine YaleUniversityChildStudyCenter LosAngeles,CA90095-1769 XavierPennec NewHaven,CT06520 Chapters39,43 AsclepiosResearchProject Chapter9 INRIASophiaAntipolis,France NathalieTzourio-Mazoyer Chapter18,34 MeiyappanSolaiyappan Grouped’ImagerieNeurofonctionelle(GIN) DepartmentofRadiology UniversitédeCaen MariaPetrou JohnsHopkinsUniversitySchoolofMedicine GIPCyceron CommunicationsandSignalProcessingGroup Baltimore,MD21210 14074CaenCedex,France ElectricalandElectronicEngineering Chapter44 Chapter28 ImperialCollege,LondonSW72AZ UnitedKingdom ThomasS.Spisz MichaelUnser Chapter14,16 SwissFederalInstituteofTechnology-Lausanne AppliedPhysicsLaboratory EPFL/DMT/IOA/BiomedicalImagingGroup JohnsHopkinsUniversity DzungL.Pham CH-1015Lausanne,Switzerland Laurel,MD20723 LaboratoryofMedicalImageComputing Chapter28 Chapter53 DepartmentofRadiology&RadiologicalScience JohnsHopkinsUniversity MarcelVanHerk LawrenceH.Staib Chapter12 RadiotherapyDepartment ImageProcessingandAnalysisGroup TheNetherlandsCancerInstitute DepartmentsofDiagnosticRadiologyand EwaPietka 1066CXAmsterdam,TheNetherlands ElectricalEngineering SilesianUniversityofTechnology Chapter32 YaleUniversity DivisionofBiomedicalElectronics NewHaven,CT06520-8042 PL.44-101Gliwice,Poland FrankVietze Chapter9 Chapter51 InstitutfürRadiologischeDiagnostik Ludwig-Maximilians-UniversitätMünchen RonaldM.Summers JerryL.Prince KlinikumInnenstadt DiagnosticRadiologyDepartment CenterforImagingScience 80336München,Germany WarrenGrantMagnusonClinicalCenter DepartmentofElectricalandComputer Chapter7 NationalInstitutesofHealth Engineering JohnsHopkinsUniversity Bethesda,MD20892-1182 JunWang Chapter48 Baltimore,MD21218 Collabria Chapters10,26 MenloPark,CA MelanieA.Sutton Chapter57 WeiQian ComputerScienceDepartment DepartmentofElectricalandComputer UniversityofWestFlorida Carl-FredrikWestin Engineering Pensacola,FL32514 SurgicalPlanningLaboratory Director:MedicalImagingandBioinformatics Chapter6,52 HarvardMedicalSchool Program Brigham&Women’sHospital DemetriTerzopoulos CollegeofEngineering Boston,MA02115 UniversityofTexas DepartmentofComputerScience Chapter2 Chapter4 UniversityofCalifornia LosAngeles,CA90095,USA AxelWismüller OsmanRatib Chapter8 UniversityofRochester DepartmentofRadiology NewYork UniversityHospitalofGeneva PhilippeThévenaz Chapter7 Chapter25 ÉcolepolytechniquefedéraledeLausanne Chapter28 AlbertWong JensA.Richolt LaboratoryforRadiologicalInformatics OrthopaedicUniversityClinic Jean-PhilippeThirion DepartmentofRadiology “Friedrichsheim” INRIASophia-ProjectEpidaure UniversityofCaliforniaatSanFrancisco D-60528Frankfurt,Germany 06902SophiaAntipolisCedex,France SanFrancisco,CA94903 Chapter21 Chapter34 Chapter50 xx Contributors RogerP.Woods DepartmentofMedicalImaging XiaolanZeng DivisionofBrainMapping andMedicalBiophysics ImageProcessingandAnalysisGroup DepartmentofNeurology UniversityofToronto DepartmentsofDiagnosticRadiologyand NeuropsychiatricInstitute Toronto,ONM4N3M5,Canada ElectricalEngineering UCLASchoolofMedicine Chapter23 YaleUniversity LosAngeles,CA90095-7085 StephenP.Yanek NewHaven,CT06520-8042 Chapters32,33,36 Chapter9 AppliedPhysicsLaboratory ChenyangXu JohnsHopkinsUniversity BinZheng SiemensCorporateResearch Laurel,MD20723 RadiologicalImagingDivision 755CollegeRoadEast,Princeton,NJ08540 Chapter49 UniversityofPittsburgh Chapter10 TerenceK.Young Pittsburgh,PA15261 MartinJ.Yaffe MobilExploration&ProducingTechnicalCenter Chapter22 ImagingResearchProgram Dallas,TX75265-0232 SunnybrookHealthSciencesCentre Chapter40 Preface The discoveries of seminal physical phenomena such as Thisseparation,whichisgenerallyeffortlessandswiftforthe X-rays,ultrasound,radioactivity,andmagneticresonance,and human visual system, can become a considerable challenge the development of imaging instruments that harness them in algorithm development. In many cases the segmentation have provided some of the most effective diagnostic tools in approachdictatestheoutcomeoftheentireanalysis,sincemea- medicine. The medical imaging community is now able to surementsandotherprocessingstepsarebasedonsegmented probeintothestructure,function,andpathologyofthehuman regions. Segmentation algorithms operate on the intensity or bodywithadiversityofimagingsystems.Thesesystemsarealso texture variations of the image using techniques that include usedforplanningtreatmentandsurgery,aswellasforimaging thresholding,region growing,deformable templates,and pat- in biology. Data sets in two, three, or more dimensions con- ternrecognitiontechniquessuchasneuralnetworksandfuzzy vey increasingly vast and detailed information for clinical or clustering.Hybridsegmentationandvolumetricsegmentation researchapplications.Thisinformationhastobeinterpretedin are also addressed in this section that includes ten chapters. atimelyandaccuratemannertobenefithealthcare.Theexam- Eightchaptershavebeenupdatedtoreflectrecentapplications, inationisqualitativeinsomecases,quantitativeinothers;some developmentsinglobalshapeconstraintsandmultigridgradi- imagesneedtoberegisteredwitheachotherorwithtemplates, entvectorflowindeformabletemplates,ageneralframework manymustbecompressedandarchived.Toassistvisualinter- forunsupervisedclassification,andboundarydistanceestima- pretation of medical images, the international imaging com- tioninvolumetricsegmentation.Chapter14inthissectionis munityhasdevelopednumerousautomatedtechniqueswhich newtothesecondedition,andpresentstheuseofhigherorder have their merits, limitations, and realm of application. This momentsofintensitydistributionstosegmenttissuetypesthat Handbookpresentsconceptsanddigitaltechniquesforprocess- thehumanvisualsystemmaynoteasilydistinguish. ingandanalyzingmedicalimagesaftertheyhavebeengenerated ordigitized.Itisorganizedintosixsectionsthatcorrespondto III Quantification thefundamentalclassesofalgorithms:enhancement,segmen- tation,quantification,registration,visualization,andasection Quantification algorithms are applied to segmented struc- thatcoverscompression,storage,andcommunication. tures to extract the essential diagnostic information such as shape, size, texture, angle, and motion. Because the types of I Enhancement measurement and tissue vary considerably, numerous tech- niquesthataddressspecificapplicationshavebeendeveloped. Enhancement algorithms are used to reduce image noise and The fourteen chapters in this section cover shape and tex- increasethecontrastofstructuresofinterest.Inimageswhere ture quantification in two- and three-dimensional data, the the distinction between normal and abnormal tissue is sub- useofshapetransformationstocharacterizestructures,arterial tle,accurateinterpretationmaybecomedifficultifnoiselevels treemorphometry,image-basedtechniquesformusculoskeletal are relatively high. In many cases,enhancement improves the biomechanics, image analysis in mammography, and quan- quality of the image and facilitates diagnosis. Enhancement tification of cardiac function. In applications where different techniques are generally used to provide a clearer image for kindsoftissuemustbeclassified,theeffectivenessofquantifi- a human observer, but they can also form a preprocessing cation depends significantly on the selection of database and step for subsequent automated analysis. The four chapters in image features, as discussed in this section. A comprehensive this section present diverse techniques for image enhance- chaptercoversthechoicesandpitfallsof imageinterpolation, ment including linear, nonlinear, fixed, adaptive, pixel-based, a technique included in many automated systems and used or multi-scale methods. In the second edition,three chapters particularlyinregistration.Sevenof thesechaptershavebeen havebeenupdatedwithnewimages,anapplicationofenhance- updatedwithadditionaltopicsincludingspecializedfiltersfor menttoMRangiography,andtheuseofFourierdescriptorsin texture quantification, application of three-dimensional tex- mammogramimageenhancement. ture analysis on schizophrenic brain images,developments in feature extraction and validation,analysis of digital mammo- II Segmentation grams,presentationofcomputeranalysisresultstoradiologists, advancesintrackingandencodingtaggedcardiacMRIimages, Segmentation is the stage where a significant commitment and a unified formulation for piecewise-polynomial synthesis is made during automated analysis by delineating structures functionsinimageinterpolation.Twonewchaptershavebeen of interest and discriminating them from background tissue. added: Chapter 18 presents a review of macroscopic models xxi xxii Preface of tumor growth for oncological image analysis, Chapter 27 modelingofmultidimensionaldata,aswellasrelatedquantita- addresses quantification of the cell nucleus in fluorescently tiveevaluationtools.Fastsurfaceextractiontechniques,volume labeledimagesincytology. visualization, and virtual endoscopy are discussed in detail, and applications are illustrated in two and three dimensions. All five chapters in this section have been updated with new IV Registration figures, considerably expanded material in volume rendering andvolumevisualization,andadditionaltopicsonendoscopy, Registrationoftwoimagesofthesamepartofthebodyisessen- including flight path planning, unfolding, registration, and tial for many applications where the correspondence between lesiondetection.Manyrecentapplicationsof visualizationare the two images conveys the desired information. These two illustrated, including surgical separation of conjoined twins, images can be produced by different modalities, for example multi-channel and multi-modal data, and three-dimensional CTandMRI,canbetakenfromthesamepatientwiththesame virtualcolonoscopy. instrument at different times, or can belong to two different subjects.Comparisonofacquiredimageswithdigitalanatomic atlastemplatesalsorequiresregistrationalgorithms.Thesealgo- VI Compression,Storage,and rithmsmustaccountforthedistortionsbetweenthetwoimages, Communication whichmaybecausedbydifferencesbetweentheimagingmeth- ods,theirartifacts,softtissueelasticity,andvariabilityamong Compression,storage,andcommunicationof medicalimages subjects.Thissectionexplainsthephysicalandbiologicalfac- arerelatedfunctionsforwhichdemandhasrecentlyincreased tors that introduce distortions, presents various linear and significantly. Medical images need to be stored in an efficient nonlinearregistrationalgorithms,describestheTalairachspace andconvenientmannerforsubsequentretrieval.Inmanycases forbrainregistration,andaddressesinterpolationissuesinher- images have to be shared among multiple sites,and commu- entinregistration.Chaptersthatdescribeclinicalapplications nication of images requires compression,specialized formats, and brain atlases illustrate the current and potential contri- and standards. Lossless image compression techniques ensure butions of registration techniques in medicine. This section that all the original information will remain in the image containsfifteenchapterssevenofwhichhavebeenupdatedwith aftercompressionbuttheydonotreducetheamountof data newtopicssuchasMaxwelltermandeddycurrentseffectson considerably. Lossy compression techniques can produce sig- distortionsinMRI,recentfindingsontheanatomicvariability nificant savings in storage but eliminate some information ofthebrain,quaternionsforrepresentingrigid-bodyrotations, from the image. This section covers fundamental concepts methodsforaveraginglineartransformations,developmentsin in medical image compression, storage and communication, estimating registration errors using landmark based fiducials, and introduces related standards such as JPEG,DICOM,and theuseof ridgesasregistrationfeatures,anddevelopmentsin HL-7. Picture archiving and communication systems (PACS) resamplingofregisteredimages. are described and techniques for preprocessing images before storage are discussed. Three chapters address lossy compres- V Visualization sion issues and one introduces an efficient three-dimensional imagecompressiontechniquebasedonthewavelettransform. Visualization is a relatively new area that is contributing sig- Among the nine chapters in this section, the first three have nificantly to medicine and biology. While automated systems been updated and two are new chapters in the second edi- are good at making precise quantitative measurements, the tion.Theupdatedchaptersincludenewtopicssuchasstructure complete examination of medical images is accomplished by reporting in PACS, compliance with the Health Insurance the visual system and experience of the human observer. The Portability and Accountability Act, electronic health record, fieldof visualizationincludesgraphicshardwareandsoftware PACSintelemedicine,andimagebackgroundtrendreduction. specifically designed to facilitate visual inspection of med- Chapter 52,new to this edition,presents trends and issues in ical and biological data. In some cases such as volumetric imagingandcommunicationinmedicalandpublichealthset- data, visualization techniques are essential to enable effective tings.Chapter53,alsonew,addressesmobileagentsystemsfor visualinspection.Thissectionstartswiththeevolutionofvisu- retrieval of images from Digital Medical Image Libraries,and alization techniques and presents the fundamental concepts discusses strategies for dynamic mammogram retrieval from andalgorithmsusedforrendering,display,manipulation,and web-basedlibraries. TomyparentsReneeandHenriBankman,twoexcellentphysicianswhodiagnosed andtreatedthousands,andinspiredthenextgeneration.
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