2022
Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries
Tillmanns N, Lum AE, Cassinelli G, Merkaj S, Verma T, Zeevi T, Staib L, Subramanian H, Bahar RC, Brim W, Lost J, Jekel L, Brackett A, Payabvash S, Ikuta I, Lin M, Bousabarah K, Johnson MH, Cui J, Malhotra A, Omuro A, Turowski B, Aboian MS. Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries. Neuro-Oncology Advances 2022, 4: vdac093. PMID: 36071926, PMCID: PMC9446682, DOI: 10.1093/noajnl/vdac093.Peer-Reviewed Original ResearchGlioma segmentationResearch algorithmSegmentation of gliomasHigh accuracy resultsML algorithmsApplicable machineAccuracy resultsTCIA datasetSegmentationAlgorithmMachinePatient dataSystematic literature reviewOverfittingData extractionDatasetBratDatabaseRecent advancesResearch literatureLimitationsExtractionCurrent research literatureMethod
2010
Integrated Segmentation and Nonrigid Registration for Application in Prostate Image-Guided Radiotherapy
Lu C, Chelikani S, Chen Z, Papademetris X, Staib LH, Duncan JS. Integrated Segmentation and Nonrigid Registration for Application in Prostate Image-Guided Radiotherapy. Lecture Notes In Computer Science 2010, 13: 53-60. PMID: 20879214, DOI: 10.1007/978-3-642-15705-9_7.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsHumansImaging, Three-DimensionalMaleProstatic NeoplasmsRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedRadiotherapy, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueSystems IntegrationTomography, X-Ray ComputedConceptsManual segmentationAutomatic segmentationImportant treatment parametersNonrigid registrationImage-guided radiotherapy systemReal patient dataNon-rigid registrationIntegrated SegmentationRegistration partRadiotherapy linear acceleratorSegmentationTreatment imagesImage qualityCone-beam CTTreatment parametersImagesPromising resultsPatient dataKey anatomical structuresLinear acceleratorRegistrationPrevious workRadiotherapy system
2008
A Constrained Non-rigid Registration Algorithm for Use in Prostate Image-Guided Radiotherapy
Greene W, Chelikani S, Purushothaman K, Chen Z, Knisely J, Staib L, Papademetris X, Duncan J. A Constrained Non-rigid Registration Algorithm for Use in Prostate Image-Guided Radiotherapy. Lecture Notes In Computer Science 2008, 11: 780-788. PMID: 18979817, PMCID: PMC2790815, DOI: 10.1007/978-3-540-85988-8_93.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceHumansImaging, Three-DimensionalMalePattern Recognition, AutomatedProstatic NeoplasmsRadiographic Image EnhancementRadiographic Image Interpretation, Computer-AssistedRadiotherapy, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueTomography, X-Ray ComputedConceptsTreatment planProstate image-guided radiotherapyOriginal treatment planRadiation dosageImage-guided radiotherapyTreatment daysRadiotherapy treatment plansCritical organsDifferent patientsPatient dataDifferent treatment daysBladderRectumProstateFemurBone motionCT imagesDosageReal patient dataPatientsRadiotherapy
2003
Entropy-Based Dual-Portal-to-3-DCT Registration Incorporating Pixel Correlation
Bansal R, Staib LH, Chen Z, Rangarajan A, Knisely J, Nath R, Duncan JS. Entropy-Based Dual-Portal-to-3-DCT Registration Incorporating Pixel Correlation. IEEE Transactions On Medical Imaging 2003, 22: 29. PMID: 12703758, DOI: 10.1109/tmi.2002.806430.Peer-Reviewed Original ResearchConceptsRegistration frameworkImage dataMutual information-based registration algorithmRegistration parametersPortal imagesUltrasound image dataReal patient dataTomography image dataImage pixelsPixel correlationRegistration algorithmPatient setup verificationSegmentationPixel intensityMarkov random processInitial versionTransformation parametersAppropriate entropyImagesAlgorithmPatient dataFrameworkCT imagesLine processSetup verification
1999
Entropy-Based, Multiple-Portal-to-3DCT Registration for Prostate Radiotherapy Using Iteratively Estimated Segmentation
Bansal R, Staib L, Chen Z, Rangarajan A, Knisely J, Nath R, Duncan J. Entropy-Based, Multiple-Portal-to-3DCT Registration for Prostate Radiotherapy Using Iteratively Estimated Segmentation. Lecture Notes In Computer Science 1999, 1679: 567-578. DOI: 10.1007/10704282_61.Peer-Reviewed Original ResearchPatient setup verificationPortal imagesReal patient dataSingle portal imagePose parametersCT data setsRegistration frameworkRegistration parametersSetup verificationDifferent initializationsAlgorithmMultiple portalsIterative fashionData setsTransformation parametersAppropriate entropyImagesCT dataPatient dataVerificationNoise conditionsFrameworkSegmentationAccurate estimationInitialization