2020
Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification
Zhang F, Dvornek N, Yang J, Chapiro J, Duncan J. Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification. IEEE Transactions On Medical Imaging 2020, 39: 3331-3342. PMID: 32356739, PMCID: PMC7606489, DOI: 10.1109/tmi.2020.2990625.Peer-Reviewed Original ResearchConceptsConvolutional neural networkNeural networkClassification taskProbability calibrationTissue classification tasksImage representationBaseline methodsPublic datasetsModel performanceRandom forest modelNetworkBetter performanceForest modelDatasetClassificationTaskCT imagesImagesOriginal model outputMR imagesModel outputInstitutional datasetPerformanceEmbeddingOutput
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