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DeepLearningfor MedicalImage Analysis
TheElsevierandMICCAISociety BookSeries
Advisoryboard
StephenAylward (Kitware,UnitedStates)
DavidHawkes (UniversityCollegeLondon,UnitedKingdom)
KensakuMori (UniversityofNagoya,Japan)
AlisonNoble (UniversityofOxford,UnitedKingdom)
SoniaPujol (HarvardUniversity,UnitedStates)
DanielRueckert (ImperialCollege,UnitedKingdom)
XavierPennec (INRIASophia-Antipolis,France)
PierreJannin (UniversityofRennes,France)
Alsoavailable:
Balocco,ComputingandVisualizationforIntravascularImagingand ComputerAssistedStenting,9780128110188
Wu,MachineLearningandMedicalImaging,9780128040768
Zhou,MedicalImageRecognition,SegmentationandParsing, 9780128025819
PART1INTRODUCTION
CHAPTER1AnIntroductiontoNeuralNetworksandDeep Learning .......................................... 3
Heung-IlSuk
1.1 Introduction.........................................3
1.2 Feed-ForwardNeuralNetworks........................4
1.2.1Perceptron....................................4
1.2.2Multi-LayerNeuralNetwork.....................5
1.2.3LearninginFeed-ForwardNeuralNetworks........6
1.3 ConvolutionalNeuralNetworks........................8
1.3.1ConvolutionandPoolingLayer...................8
1.3.2ComputingGradients...........................9
1.4 DeepModels........................................11
1.4.1VanishingGradientProblem.....................11
1.4.2DeepNeuralNetworks..........................12
1.4.3DeepGenerativeModels........................14
1.5 TricksforBetterLearning.............................20
1.5.1RectifiedLinearUnit(ReLU)....................20
1.5.2Dropout......................................20
1.5.3BatchNormalization............................21
1.6 Open-SourceToolsforDeepLearning...................22 References..........................................22 Notes..............................................24
CHAPTER2AnIntroductiontoDeepConvolutionalNeural NetsforComputerVision ......................... 25 SurajSrinivas,RaviK.Sarvadevabhatla, KondaR.Mopuri,NikitaPrabhu, SrinivasS.S.KruthiventiandR.VenkateshBabu
2.1 Introduction.........................................26
2.2 ConvolutionalNeuralNetworks........................27
2.2.1BuildingBlocksofCNNs.......................27 2.2.2Depth........................................29
2.2.3LearningAlgorithm............................30 v
3.4.1AnatomyDetectionandSegmentationin3D........71
3.4.2LandmarkDetectionin2Dand3D................74
4.3.3LearningStageII:CNNBoosting.................90
4.3.4Run-TimeClassification.........................92
4.4 Results.............................................93
4.4.1ImageClassificationonSyntheticData............93
4.4.2Body-PartRecognitiononCTSlices..............95
4.5 DiscussionandFutureWork...........................99 References..........................................100
CHAPTER5AutomaticInterpretationofCarotidIntima–Media ThicknessVideosUsingConvolutionalNeural Networks .......................................... 105 NimaTajbakhsh,JaeY.Shin,R.ToddHurst, ChristopherB.KendallandJianmingLiang
5.1 Introduction.........................................106
5.2 RelatedWork........................................107
5.3 CIMTProtocol......................................109
5.4 Method.............................................109
5.4.1ConvolutionalNeuralNetworks(CNNs)...........109
5.4.2FrameSelection................................110
5.4.3ROILocalization...............................112
5.4.4Intima–MediaThicknessMeasurement............115
5.5 Experiments.........................................117
5.5.1Pre-andPost-ProcessingforFrameSelection.......118
5.5.2ConstrainedROILocalization....................118
5.5.3Intima–MediaThicknessMeasurement............121
5.5.4End-to-EndCIMTMeasurement..................123
5.6 Discussion..........................................124
5.7 Conclusion..........................................128 Acknowledgement...................................128 References..........................................128 Notes..............................................131
CHAPTER6DeepCascadedNetworksforSparselyDistributed ObjectDetectionfromMedicalImages ........... 133 HaoChen,QiDou,LequanYu,JingQin,LeiZhao, VincentC.T.Mok,DefengWang,LinShiand Pheng-AnnHeng
6.1 Introduction.........................................134
6.2 Method.............................................136
6.2.1CoarseRetrievalModel.........................136
6.2.2FineDiscriminationModel......................139
6.3 MitosisDetectionfromHistologyImages................139
6.3.1Background...................................139
6.3.2TransferLearningfromCross-Domain.............140
PART4MEDICALIMAGEREGISTRATION
CHAPTER11ScalableHighPerformanceImageRegistration FrameworkbyUnsupervisedDeepFeature RepresentationsLearning 245 ShaoyuWang,MinjeongKim,GuorongWuand DinggangShen
11.1
11.2.2LearnIntrinsicFeatureRepresentationsby UnsupervisedDeepLearning.....................250
11.2.3RegistrationUsingLearnedFeatureRepresentations.255 11.3 Experiments.........................................258
11.3.1ExperimentalResultonADNIDataset.............259
11.3.2ExperimentalResultonLONIDataset.............260
11.3.3ExperimentalResulton7.0-TMRImageDataset....263 11.4 Conclusion..........................................265
12.4 RegressionStrategy..................................276
12.4.1ParameterSpacePartitioning.....................276
12.4.2MarginalSpaceRegression......................277
12.5 FeatureExtraction....................................277
12.5.1LocalImageResidual...........................277
12.5.23-DPointsofInterest...........................279
12.6 ConvolutionalNeuralNetwork.........................280
12.6.1NetworkStructure..............................280
12.6.2TrainingData..................................281
12.6.3Solver........................................282
12.7 ExperimentsandResults..............................283
12.7.1ExperimentSetup..............................283
12.7.2Hardware&Software...........................285
12.7.3PerformanceAnalysis...........................286
12.7.4ComparisonwithState-of-the-ArtMethods.........288
12.8 Discussion..........................................292 Disclaimer..........................................294 References..........................................294
PART5COMPUTER-AIDEDDIAGNOSISANDDISEASE QUANTIFICATION
CHAPTER13ChestRadiographPathologyCategorizationvia
TransferLearning ................................. 299
IditDiamant,YanivBar,OferGeva,LiorWolf, GaliZimmerman,SivanLieberman,EliKonenand HayitGreenspan
13.1 Introduction.........................................300
13.2 ImageRepresentationSchemeswithClassical(Non-Deep) Features............................................303
13.2.1ClassicalFiltering..............................304
13.2.2Bag-of-Visual-WordsModel.....................305
13.3 ExtractingDeepFeaturesfromaPre-TrainedCNNModel..306
13.4 ExtendingtheRepresentationUsingFeatureFusionand Selection...........................................309
13.5 ExperimentsandResults..............................309
13.5.1Data.........................................309
13.5.2ExperimentalSetup.............................310
13.5.3ExperimentalResults...........................310
13.6 Conclusion..........................................315 Acknowledgements..................................317 References..........................................318
CHAPTER14DeepLearningModelsforClassifying
GustavoCarneiro,JacintoNascimentoand AndrewP.Bradley
15.5.1ParticipantDataandPreprocessing................360
PART6OTHERS
CHAPTER16DeepNetworksandMutualInformation MaximizationforCross-ModalMedicalImage Synthesis 381
RavitejaVemulapalli,HienVanNguyenand S.KevinZhou
16.1 Introduction.........................................382
16.2 SupervisedSynthesisUsingLocation-SensitiveDeep Network............................................384
16.2.1Backpropagation...............................386
16.2.2NetworkSimplification.........................387
16.2.3Experiments...................................388
16.3 UnsupervisedSynthesisUsingMutualInformation Maximization.......................................390
16.3.1GeneratingMultipleTargetModalityCandidates....392
16.3.2FullImageSynthesisUsingBestCandidates........393
16.3.3RefinementUsingCoupledSparseRepresentation...396
16.3.4ExtensiontoSupervisedSetting..................396
16.3.5Experiments...................................397
16.4 ConclusionsandFutureWork..........................401 Acknowledgements..................................401 References..........................................401 Note...............................................403
CHAPTER17NaturalLanguageProcessingforLarge-Scale MedicalImageAnalysisUsingDeepLearning .... 405 Hoo-ChangShin,LeLuandRonaldM.Summers
17.1 Introduction.........................................406
17.2 FundamentalsofNaturalLanguageProcessing ............407
17.2.1PatternMatching...............................407
17.2.2TopicModeling................................410
17.3 NeuralLanguageModels..............................411
17.3.1WordEmbeddings..............................411
17.3.2RecurrentLanguageModel......................412
17.4 MedicalLexicons....................................414
17.4.1UMLSMetathesaurus...........................414 17.4.2RadLex.......................................414
17.5 PredictingPresenceorAbsenceofFrequentDiseaseTypes.414 17.5.1MiningPresence/AbsenceofFrequentDiseaseTerms414 17.5.2PredictionResultandDiscussion.................415
17.6 Conclusion..........................................419
YanrongGuo
UniversityofNorthCarolinaatChapelHill,ChapelHill,NC,UnitedStates
Pheng-AnnHeng
TheChineseUniversityofHongKong,HongKong,China
JoachimHornegger
Friedrich-AlexanderUniversityErlangen–Nürnberg,Erlangen,Germany
R.ToddHurst
MayoClinic,Scottsdale,AZ,UnitedStates
ChristianIgel
UniversityofCopenhagen,Copenhagen,Denmark
VamsiK.Ithapu
UniversityofWisconsin–Madison,Madison,WI,UnitedStates
AndrewJanowczyk
CaseWesternReserveUniversity,Cleveland,OH,UnitedStates
SterlingC.Johnson
WilliamS.MiddletonMemorialHospital,Madison,WI,UnitedStates; UniversityofWisconsin–Madison,Madison,WI,UnitedStates
MichielKallenberg
BiomediqA/S,Copenhagen,Denmark
ChristopherB.Kendall
MayoClinic,Scottsdale,AZ,UnitedStates
MinjeongKim
UniversityofNorthCarolinaatChapelHill,ChapelHill,NC,UnitedStates
EliKonen
ShebaMedicalCenter,Tel-Hashomer,Israel
SrinivasS.S.Kruthiventi
IndianInstituteofScience,Bangalore,India
JianmingLiang
ArizonaStateUniversity,Scottsdale,AZ,UnitedStates
RuiLiao
SiemensMedicalSolutionsUSA,Inc.,Princeton,NJ,UnitedStates
SivanLieberman
ShebaMedicalCenter,Tel-Hashomer,Israel
LeLu
NationalInstitutesofHealthClinicalCenter,Bethesda,MD,UnitedStates
AnantMadabhushi
CaseWesternReserveUniversity,Cleveland,OH,UnitedStates
KennethB.Margulies
UniversityofPennsylvania,Philadelphia,PA,UnitedStates
DimitrisMetaxas
RutgersUniversity,Piscataway,NJ,UnitedStates
ShunMiao
SiemensMedicalSolutionsUSA,Inc.,Princeton,NJ,UnitedStates
VincentC.T.Mok
TheChineseUniversityofHongKong,HongKong,China
KondaR.Mopuri
IndianInstituteofScience,Bangalore,India
JacintoNascimento
InstitutoSuperiorTécnico,Lisbon,Portugal
HienVanNguyen
UberAdvancedTechnologyCenter,Pittsburgh,PA,UnitedStates
MadsNielsen
BiomediqA/S,Copenhagen,Denmark; UniversityofCopenhagen,Copenhagen,Denmark
JeffreyJ.Nirschl
UniversityofPennsylvania,Philadelphia,PA,UnitedStates
AkshayPai
BiomediqA/S,Copenhagen,Denmark; UniversityofCopenhagen,Copenhagen,Denmark
EliotG.Peyster
UniversityofPennsylvania,Philadelphia,PA,UnitedStates
NikitaPrabhu
IndianInstituteofScience,Bangalore,India
JingQin
TheHongKongPolytechnicUniversity,HongKong,China
RaviK.Sarvadevabhatla
IndianInstituteofScience,Bangalore,India
DinggangShen
UniversityofNorthCarolinaatChapelHill,ChapelHill,NC,UnitedStates
LinShi
TheChineseUniversityofHongKong,HongKong,China
Hoo-ChangShin
NationalInstitutesofHealthClinicalCenter,Bethesda,MD,UnitedStates
JaeY.Shin
ArizonaStateUniversity,Scottsdale,AZ,UnitedStates
VikasSingh
UniversityofWisconsin–Madison,Madison,WI,UnitedStates
StefanSommer
UniversityofCopenhagen,Copenhagen,Denmark
SurajSrinivas
IndianInstituteofScience,Bangalore,India
Heung-IlSuk
KoreaUniversity,Seoul,RepublicofKorea
RonaldM.Summers
NationalInstitutesofHealthClinicalCenter,Bethesda,MD,UnitedStates
NimaTajbakhsh
ArizonaStateUniversity,Scottsdale,AZ,UnitedStates
Yuan-ChingTeng
UniversityofCopenhagen,Copenhagen,Denmark
RavitejaVemulapalli
UniversityofMaryland,CollegePark,MD,UnitedStates
DefengWang
TheChineseUniversityofHongKong,HongKong,China
JaneZ.Wang
UniversityofBritishColumbia,Vancouver,BC,Canada
ShaoyuWang
UniversityofNorthCarolinaatChapelHill,ChapelHill,NC,UnitedStates; DonghuaUniversity,Shanghai,China
LiorWolf
Tel-AvivUniversity,Ramat-Aviv,Israel
GuorongWu
UniversityofNorthCarolinaatChapelHill,ChapelHill,NC,UnitedStates
YuanpuXie
UniversityofFlorida,Gainesville,FL,UnitedStates
FuyongXing
UniversityofFlorida,Gainesville,FL,UnitedStates
ZhennanYan
RutgersUniversity,Piscataway,NJ,UnitedStates
LinYang
UniversityofFlorida,Gainesville,FL,UnitedStates
LequanYu
TheChineseUniversityofHongKong,HongKong,China
AbouttheEditors
S.KevinZhou,PhD,iscurrentlyaPrincipalKeyExpertatSiemensHealthineers TechnologyCenter,leadingateamoffull-timeresearchscientistsandstudentsdedicatedtoresearchinganddevelopinginnovativesolutionsformedicalandindustrial imagingproducts.Hisresearchinterestslieincomputervisionandmachine/deep learningandtheirapplicationstomedicalimageanalysis,facerecognition,andmodeling,etc.Hehaspublishedover150bookchaptersandpeer-reviewedjournaland conferencepapers,registeredover250patentsandinventions,writtentworesearch monographs,andeditedthreebooks.Hehaswonmultipletechnology,patent,and productawards,includingtheR&D100AwardandSiemensInventoroftheYear.He isaneditorialboardmemberfortheMedicalImageAnalysisandIEEETransactions onMedicalImagingjournalsandafellowoftheAmericanInstituteofMedicaland BiologicalEngineering(AIMBE).
HayitGreenspan isaProfessorattheBiomedicalEngineeringDepartment,Faculty ofEngineering,TelAvivUniversity.ShewasavisitingProfessorattheRadiologyDepartmentofStanfordUniversity,andiscurrentlyaffiliatedwiththeInternationalComputerScienceInstitute(ICSI)atBerkeley.Dr.Greenspan’sresearch focusesonimagemodelingandanalysis,deeplearning,andcontent-basedimage retrieval.ResearchprojectsincludebrainMRIresearch(structuralandDTI),CT andX-rayimageanalysis–automateddetectiontosegmentationandcharacterization.Dr.Greenspanhasover150publicationsinleadinginternationaljournalsand conferenceproceedings.Shehasreceivedseveralawardsandisacoauthoronseveralpatents.Dr.Greenspanisamemberofseveraljournalandconferenceprogram committees,includingSPIEMedicalImaging,IEEE_ISBI,andMICCAI.Sheisan AssociateEditorfortheIEEETransactionsonMedicalImaging(TMI)journal.Recently,inMay2016,shewastheleadguesteditorforanIEEE-TMIspecialissueon “DeepLearninginMedicalImaging.”
DinggangShen isaProfessorofRadiologyattheBiomedicalResearchImaging Center(BRIC),andComputerScience,andBiomedicalEngineeringDepartmentsin theUniversityofNorthCarolinaatChapelHill(UNC-CH).Heiscurrentlydirecting theCenterforImageInformaticsandAnalysis,theImageDisplay,Enhancement,and Analysis(IDEA)LabintheDepartmentofRadiology,andalsothemedicalimage analysiscoreintheBRIC.Hewasatenure-trackassistantprofessorattheUniversityofPennsylvania(UPenn),andafacultymemberatJohnsHopkinsUniversity. Dr.Shen’sresearchinterestsincludemedicalimageanalysis,computervision,and patternrecognition.Hehaspublishedmorethan700papersininternationaljournals andconferenceproceedings.Heservesasaneditorialboardmemberforsixinternationaljournals.HehasservedontheBoardofDirectorsofTheMedicalImage ComputingandComputerAssistedIntervention(MICCAI)Societyin2012–2015.
Introduction
1 PART
