Precise Segmentation of Multiple Organs in CT Volumes Using Learning-Based Approach and Information Theory
Lu C, Zheng Y, Birkbeck N, Zhang J, Kohlberger T, Tietjen C, Boettger T, Duncan JS, Zhou SK. Precise Segmentation of Multiple Organs in CT Volumes Using Learning-Based Approach and Information Theory. Lecture Notes In Computer Science 2012, 15: 462-469. PMID: 23286081, DOI: 10.1007/978-3-642-33418-4_57.Peer-Reviewed Original ResearchConceptsMarginal Space LearningCT volumesChallenging segmentation problemInformation-theoretic schemesLearning-based approachComputer-aided diagnosisExcellent segmentation accuracyRobust boundary detectionInformation theoryPelvic organ segmentationSteerable featuresChallenging datasetArt solutionsOrgan segmentationSegmentation problemSpace learningSegmentation performanceSegmentation accuracyPrecise segmentationBoundary detectionJensen-Shannon divergenceTheoretic schemeInference processDiverse sourcesPrevious state