2023
Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning
Kucukkaya A, Zeevi T, Chai N, Raju R, Haider S, Elbanan M, Petukhova-Greenstein A, Lin M, Onofrey J, Nowak M, Cooper K, Thomas E, Santana J, Gebauer B, Mulligan D, Staib L, Batra R, Chapiro J. Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning. Scientific Reports 2023, 13: 7579. PMID: 37165035, PMCID: PMC10172370, DOI: 10.1038/s41598-023-34439-7.Peer-Reviewed Original Research
1999
A New Approach to 3D Sulcal Ribbon Finding from MR Images
Zeng X, Staib L, Schultz R, Tagare H, Win L, Duncan J. A New Approach to 3D Sulcal Ribbon Finding from MR Images. Lecture Notes In Computer Science 1999, 1679: 148-157. DOI: 10.1007/10704282_16.Peer-Reviewed Original ResearchGeneral segmentation methodsMR brain imagesDistance functionLittle manual interventionDeformable surface modelSegmentation workSegmentation methodManual interventionNew approachBrain imagesContour modelCortex segmentationDynamic programmingLevel setsNatural followImagesMR imagesControl problemSurface modelSegmentationQuantitative resultsProgrammingSegmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation
Zeng X, Staib L, Schultz R, Duncan J. Segmentation and measurement of the cortex from 3-D MR images using coupled-surfaces propagation. IEEE Transactions On Medical Imaging 1999, 18: 927-937. PMID: 10628952, DOI: 10.1109/42.811276.Peer-Reviewed Original ResearchConceptsImage-derived informationEasy initializationAutomatic segmentationEfficient segmentationMR imagesChallenging problemFinal representationManual segmentationThree-dimensional MR imagesSegmentationComputational efficiencyOutermost thin layerSuch problemsImagesTight couplingNew approachConvoluted natureRepresentationGeometric measurementsInitializationImplementationSulcal foldsBrain anatomyInformationConstraints
1998
Segmentation and measurement of the cortex from 3D MR images
Zeng X, Staib L, Schultz R, Duncan J. Segmentation and measurement of the cortex from 3D MR images. Lecture Notes In Computer Science 1998, 1496: 519-530. DOI: 10.1007/bfb0056237.Peer-Reviewed Original ResearchReal 3D MR imagesImage-derived informationEasy initializationAutomatic segmentationEfficient segmentationMR imagesChallenging problemFinal representationManual segmentationSegmentationComputational efficiencyOutermost thin layerImagesTight couplingNew approachConvoluted natureRepresentationGeometric measurementsInitializationSurface propagationImplementationBrain anatomyInformationConstraintsMethod