2022
Dual-domain self-supervised learning for accelerated non-Cartesian MRI reconstruction
Zhou B, Schlemper J, Dey N, Mohseni Salehi SS, Sheth K, Liu C, Duncan JS, Sofka M. Dual-domain self-supervised learning for accelerated non-Cartesian MRI reconstruction. Medical Image Analysis 2022, 81: 102538. PMID: 35926336, DOI: 10.1016/j.media.2022.102538.Peer-Reviewed Original ResearchConceptsNon-Cartesian MRI reconstructionMRI reconstructionUndersampled dataPrevious baseline methodsSelf-supervised approachSelf-supervised learningHigh-quality reconstructionReconstruction networkAppearance consistencyDataset demonstrateBaseline methodsImage domainDisjoint partitionsSupervised trainingPractical adoptionReconstruction accuracyDomain partitionImproved image qualityImage qualityDDSSSampling patternK-spaceExperimental resultsNetworkMotion robustness
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