Handbook of Medical Image Processing and Analysis Academic Press Series in Biomedical Engineering; 2. Ed.

970 Pages·2009·75.95 MB·English

by  Isaac Bankman

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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.