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Computational Anatomy Based on Whole Body Imaging: Basic Principles of Computer-Assisted Diagnosis a


What Is Computational Anatomy?Needs, Seeds, and Solutions Around Medical Imaging: History and PerspectivesNeeds in Medical Education and Clinical PracticeFrom the Viewpoint of Medical EducationFrom the Viewpoint of Diagnostic RadiologyFrom the Viewpoint of Therapeutic RadiologyFrom the Viewpoint of SurgerySeeds and Solutions in Science, Technology, and EngineeringWhole-Body Computational AnatomyImpact of Whole-Body ImagingToward Complete Medical Image UnderstandingClassification CompletenessSpatial CompletenessCompleteness as CorrectnessBook OrganizationReferencesFundamental Theories and TechniquesFrom Anatomy to Computational Anatomy Hidekata Hontani and Yasushi HiranoIntroductionSimple ExamplesOutline of ASMRequired TechniquesShape representationConstruction of Statistical Shape ModelMesh-to-Mesh RegistrationMesh-to-Volume registrationVolume-to-Volume RegistrationVolume-to-Volume RegistrationParameterization-to-Parameterization RegistrationPopulation-Based OptimizationLocal Image Feature DetectionStatistical InferenceMathematical Foundation Hidekata Hontani and Yasushi HiranoSignal ProcessingDigital ImagesLinear OperationConvolutionCross CorrelationFourier Series ExpansionDifferentiation of Discrete SignalsFundamental TransformationsCoordinate TransformationLinear SubspaceAffine TransformationSingular Value DecompositionPrincipal Component AnalysisProbability and Statistics: Foundations of CASum Rule and Product Rule of ProbabilityExpectation and VarianceGaussian DistributionFoundations of Pattern RecognitionBayes Decision TheoryClassifier DesignPerformance Evaluationn-Fold Cross ValidationBootstrap MethodExamples of ClassifiersDecision TreeSupport Vector Machine (SVM)Random ForestArtificial Neural Network (ANN)BoostingComputational Anatomical Model Hidekata Hontani, Yasushi Hirano, Xiao Dong, Akinobu Shimiz, and Shohei HanaokaModels for SegmentationGeometrical RepresentationRepresentation Using Functions of VoxelsRepresentation Using Parametric FunctionsCurvesSurfacesRegistration Required Before Measurement or AnalysisImage Features and LandmarksAnatomical LandmarksKeypointsEdges and RidgesDiffeomorphism FrameworksLDDMM Framework for RegistrationGeneral SettingLDDMM Diffeomorphic RegistrationGeometry of LDDMM RegistrationSVF FrameworkStatistical Analysis on Shape ManifoldLongitudinal Shape Data AnalysisTrajectory EstimationTrajectory ComparisonSpatiotemporal Atlas ConstructionApplications and Future WorksComputational Anatomy and RegistrationProbabilistic AtlasSSMsSSM with Level-Set RepresentationSSM with NURBS Surface RepresentationSSM with PDM (Subspace Representation)SSM with Point Distribution Model (MRF Representation)Multi-atlasCA-Based SegmentationProbabilistic Atlas-Based SegmentationActive Shape ModelLevel Set with CAGraph-Cuts with CAEnsemble Learning with CAMultiple Organs, Anomaly, and LesionsMultiple OrgansAnatomical AnomalyDefinitionExamples of Normal VariantsStatistical Modeling of Normal VariantsReferencesUnderstanding Medical Images Based on Computational Anatomy ModelsIntroductionBoneSkeletal MuscleAnatomical Modeling of Skeletal MusclesMuscle Distribution ModelSSMLymph NodesOverview of Lymph Node Segmentation on Medical ImagesOverview of Lymph Node Segmentation from Abdominal CT ImagesPreprocessingBlob-Like Structure EnhancementLymph Node Candidate Region DetectionFalse-Positive Region ReductionExamples of Lymph Node Detection on Abdominal CT ImagesBrain, Head, Neck, and EyeComputational NeuroanatomyVoxel-Based Morphometry (VBM)MRIprocessing (spatial normalization and segmentation)Statistical analysisDeformation-Based and Tensor-Based MorphometryBrain Image DatabaseWhite MatterBrain and White Matter AnatomyDiffusion MRI: A Tool for White Matter Anatomy InferenceTractography Techniques(1). Seed point configuration(2) . Diffusion tensor calculation(3) . Short step movement(4) . Iteration of trackingClinical ApplicationsNeurosurgical Planning and Intraoperative NavigationAcute InfarctionPerspectivesBrain CTOral/Maxillofacial AnatomyFundus OculiIntroductionRetinal OCTThoracic OrgansBronchus and VesselsOverviewRegion-Growing-Based MethodAnatomical LabelingPulmonary Blood VesselsOverviewSimple ThresholdingLine Enhancement FilterLevel Set-Based ApproachLung and PleuraBreastUltrasound Imaging: Classification Methods for MassesSSMs of Breast Ultrasound ImagesMammographyBreast MRICardiacMorphologic and Functional Modeling of the HeartCoronary ArteriesAbdomenLiverPancreasSpleenKidneysDigestive Tract SegmentationStomachIntestineMultiple Abdominal OrgansBasic Unit for Modeling Multiple Organs: Prediction-Based CA Models WeMulti-organ Computational Anatomy Modeling: Organ Correlation GraphAbdominal Aorta SegmentationAbdominal Aorta and Anatomical ModelsAbdominal Blood Vessel SegmentationAnatomical Labeling of Abdominal Blood VesselsReferencesApplied Technologies and SystemsApplication and Systematization of CAComputer-Assisted DiagnosisDetectionLung Nodule DetectionIntroductionGeneric Scheme in CADe Systems for Lung CancerLesion Detection in the Abdominal RegionLocal Intensity Structure AnalysisRadial Difference FilterQuantification and ClassificationLung Cancer Prognostication Using CT Image-Based FeaturesCT Value Histogram-Based Classification FrameworkStatistical AnalysisExperiments and ResultsConclusionMiscellaneousNonrigid Image Registration for Detecting Temporal Changes on Thoracic MDCT ImagesIntroductionMethodsPreprocessingGlobal MatchingLocal Matching Based on the 3D Voxel Matching TechniqueExperimental ResultsDiscussion and ConclusionPerspectiveComputer-Aided Surgery and TherapyPreoperative SupportLaparoscopic Surgery SimulationExample of Laparoscopic Surgery Simulation SystemOrgan Segmentation and LabelingVirtual PneumoperitoneumIntraoperative SupportTrackingSensor-Based TrackingImage-Based TrackingIntraoperative Assistance Information Image DisplaySynchronized DisplayReference Image DisplayRespectiveFeasibility of Intelligent Image Analysis with CA in High-Precision Radiation Treatment PlanningIntroductionAutomated Delineation of Target Regions for Radiation Treatment PlanningAutopsy Imaging (Ai)Past, Present, and Future of Autopsy ImagingThe Nature of Autopsy Imaging (Ai)The History of AiPresent StatusCategories of Causes of DeathThe Future of AiExtension of Ai ApplicationsPremortem vs. Postmortem Body Imaging and Computational Anatomy of LiverIntroductionChanges in Liver MorphologyComparisons Between an SSM of an In Vivo Liver and That of a Postmortem LiverMaterials, Performance Indices, and SSMsResults and DiscussionComputational Anatomy and Segmentation of Postmortem LiverIntroductionPostmortem Liver SSMs Using Synthesized Postmortem LabelsPostmortem Liver Segmentation Algorithm with an SSMMethodResults and DiscussionPostmortem Lung SegmentationIntroductionMethodologyRough Location Estimation of the LungGraph Cut-Based Fine Segmentation of the LungResults and DiscussionPerspectivePostmortem Liver SSM and Liver SegmentationPostmortem Lung SSM and Lung SegmentationMiscellaneous Future TopicsReferencesPerspectives
 
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