2024
Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.
Hoebel K, Bridge C, Ahmed S, Akintola O, Chung C, Huang R, Johnson J, Kim A, Ly K, Chang K, Patel J, Pinho M, Batchelor T, Rosen B, Gerstner E, Kalpathy-Cramer J. Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation. Radiology Artificial Intelligence 2024, 6: e220231. PMID: 38197800, PMCID: PMC10831514, DOI: 10.1148/ryai.220231.Peer-Reviewed Original ResearchConceptsBrain tumor segmentationDeep learning algorithmsSegmentation qualityLearning algorithmsTumor segmentationBrain tumor segmentation algorithmQuantitative quality metricsTumor segmentation algorithmClinical expert evaluationSegmentation performanceAlgorithm evaluationSegmentation algorithmQuality metricsDice scoreHausdorff distanceSegmentation casesAlgorithmExperimental resultsExpert evaluationQuality evaluationMetricsSurvey article
2023
SliceProp: A Slice-Wise Bidirectional Propagation Model for Interactive 3D Medical Image Segmentation
Xu X, Lu W, Lei J, Qiu P, Shen H, Yang Y. SliceProp: A Slice-Wise Bidirectional Propagation Model for Interactive 3D Medical Image Segmentation. 2023, 00: 414-424. DOI: 10.1109/medai59581.2023.00062.Peer-Reviewed Original ResearchMedical image segmentationInteractive segmentation frameworkImage segmentationSegmentation frameworkState-of-the-art methodsMedical image segmentation methodsWorkload of annotationState-of-the-artImage segmentation algorithmImage segmentation methodImage dataManual labelingSegmentation algorithmSegmentation methodAutomatic segmentationHigher complexityPropagation modelUnreliable predictionsAnnotationSegmentsFrameworkBacktrackingBidirectional propagationAlgorithmDatasetLiverHccSeg: A publicly available multiphasic MRI dataset with liver and HCC tumor segmentations and inter-rater agreement analysis
Gross M, Arora S, Huber S, Kücükkaya A, Onofrey J. LiverHccSeg: A publicly available multiphasic MRI dataset with liver and HCC tumor segmentations and inter-rater agreement analysis. Data In Brief 2023, 51: 109662. PMID: 37869619, PMCID: PMC10587725, DOI: 10.1016/j.dib.2023.109662.Peer-Reviewed Original ResearchTumor segmentation algorithmTumor segmentationSegmentation algorithmLiver segmentationManual segmentationTumor segmentation taskHigh-quality segmentationSegmentation taskSegmentation metricsSegmentation performanceAccurate segmentationRelevant metadataSegmentation agreementSegmentationMedical imagingFeature analysisExternal dataDatasetIntra-rater variabilityAlgorithmInnovative solutions
2022
Clinical Implementation of Novel PACS-based Deep Learning Glioma Segmentation Algorithm
Merkaj S, Bousabarah K, MingDe L, Pala A, Petersen G, Jekel L, Bahar R, Tillmanns N, Malhotra A, Westerhoff M, Aboian M. Clinical Implementation of Novel PACS-based Deep Learning Glioma Segmentation Algorithm. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2022 DOI: 10.58530/2022/2744.Peer-Reviewed Original ResearchReal-time buildingAuto-segmentation algorithmTumor segmentationSegmentation algorithmBRATS datasetData generationNew segmentationData productionPrediction algorithmClinical workflowAlgorithmDatasetLaborious processHospital datasetPACSSegmentationNovel approachWorkflowImagesImplementationExpertsGenerationRetraining
2016
Power estimation for non-standardized multisite studies
Keshavan A, Paul F, Beyer MK, Zhu AH, Papinutto N, Shinohara RT, Stern W, Amann M, Bakshi R, Bischof A, Carriero A, Comabella M, Crane JC, D'Alfonso S, Demaerel P, Dubois B, Filippi M, Fleischer V, Fontaine B, Gaetano L, Goris A, Graetz C, Gröger A, Groppa S, Hafler DA, Harbo HF, Hemmer B, Jordan K, Kappos L, Kirkish G, Llufriu S, Magon S, Martinelli-Boneschi F, McCauley JL, Montalban X, Mühlau M, Pelletier D, Pattany PM, Pericak-Vance M, Cournu-Rebeix I, Rocca MA, Rovira A, Schlaeger R, Saiz A, Sprenger T, Stecco A, Uitdehaag BMJ, Villoslada P, Wattjes MP, Weiner H, Wuerfel J, Zimmer C, Zipp F, Consortium I, Hauser SL, Oksenberg JR, Henry RG. Power estimation for non-standardized multisite studies. NeuroImage 2016, 134: 281-294. PMID: 27039700, PMCID: PMC5656257, DOI: 10.1016/j.neuroimage.2016.03.051.Peer-Reviewed Original Research
2014
Volumetric brain analysis in neurosurgery: Part 1. Particle filter segmentation of brain and cerebrospinal fluid growth dynamics from MRI and CT images.
Mandell J, Langelaan J, Webb A, Schiff S. Volumetric brain analysis in neurosurgery: Part 1. Particle filter segmentation of brain and cerebrospinal fluid growth dynamics from MRI and CT images. Journal Of Neurosurgery Pediatrics 2014, 15: 113-24. PMID: 25431902, DOI: 10.3171/2014.9.peds12426.Peer-Reviewed Original ResearchConceptsEdge trackerParticle filterGround vehicle navigationBrain image analysisCT imagesMRI data setsImage segmentationSegmentation algorithmAutonomous airVehicle navigationAccurate edgesNovel algorithmManual segmentationSegmentationMR imagesBrain dataVolumetric brain analysisData setsImage analysisSemiautomatic methodImagesModality independenceHistorical dataAlgorithmMRI data
2010
Non-rigid Registration with Missing Correspondences in Preoperative and Postresection Brain Images
Chitphakdithai N, Duncan JS. Non-rigid Registration with Missing Correspondences in Preoperative and Postresection Brain Images. Lecture Notes In Computer Science 2010, 13: 367-374. PMID: 20879252, PMCID: PMC3031159, DOI: 10.1007/978-3-642-15705-9_45.Peer-Reviewed Original ResearchConceptsTypes of datasetsNon-rigid registration methodImage alignmentNon-rigid registrationMissing correspondencesSegmentation algorithmNon-rigid registration algorithmSimilarity metricCorrespondence problemValid correspondencesRegistration algorithmRegistration methodExpectation-maximization algorithmBrain imagesJoint registrationReal dataAlgorithmImagesRegistrationError kernel
2008
Detection and Segmentation of Concealed Objects in Terahertz Images
Shen X, Dietlein C, Grossman E, Popović Z, Meyer F. Detection and Segmentation of Concealed Objects in Terahertz Images. IEEE Transactions On Image Processing 2008, 17: 2465-2475. PMID: 19004716, DOI: 10.1109/tip.2008.2006662.Peer-Reviewed Original ResearchConceptsSegmentation algorithmStandard segmentation algorithmsImage segmentation algorithmArt segmentation methodsAnisotropic diffusion algorithmDedicated hardwareSegmentation methodImages of objectsDiffusion algorithmDifferent objectsPoor contrastAlgorithmHardwareImagesObjectsPassive terahertz imagingTerahertz imagesTerahertz imagingConcealed ObjectsGaussian densitySegmentationLow signalTHz imagesInherent physical propertiesRadiometric temperature
2007
LV Segmentation Through the Analysis of Radio Frequency Ultrasonic Images
Yan P, Jia CX, Sinusas A, Thiele K, O’Donnell M, Duncan JS. LV Segmentation Through the Analysis of Radio Frequency Ultrasonic Images. Lecture Notes In Computer Science 2007, 20: 233-244. PMID: 17633703, DOI: 10.1007/978-3-540-73273-0_20.Peer-Reviewed Original Research
2004
Construction of a 3D Volumetric Probabilistic Model of the Mouse Kidney from MRI
Okuda H, Shkarin P, Behar K, Duncan J, Papademetris X. Construction of a 3D Volumetric Probabilistic Model of the Mouse Kidney from MRI. Lecture Notes In Computer Science 2004, 3217: 1052-1054. DOI: 10.1007/978-3-540-30136-3_134.Peer-Reviewed Original ResearchProbabilistic volumetric modelVolumetric modelPoint matching algorithmRobust point matching algorithmLocal B-splineKidney segmentationGlobal linear transformationsSegmentation algorithmMatching algorithmFree-form deformationRegistration stepVolumetric imagesKidney imagesShape modelingProbabilistic modelForm deformationAlgorithmImagesB-splinesSegmentationUltimate goal
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