2022
Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling
Djebra Y, Marin T, Han P, Bloch I, Fakhri G, Ma C. Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling. IEEE Transactions On Medical Imaging 2022, 42: 158-169. PMID: 36121938, PMCID: PMC10024645, DOI: 10.1109/tmi.2022.3207774.Peer-Reviewed Original ResearchConceptsSpace alignmentSampled k-space dataState-of-the-art methodsIntrinsic low-dimensional manifold structureNumerical simulation studyLow-dimensional manifold structureState-of-the-artLinear subspace modelSparsity modelModel-based frameworkSubspace modelManifold structureMathematical modelManifold modelSparse samplingImage reconstructionMRI applicationsDynamic magnetic resonance imagingSpatiotemporal signalsSpatial resolutionPerformanceSimulation studyImagesMethodSparsity
2018
Subject-specific brain tumor growth modelling via an efficient Bayesian inference framework
Chang Y, Sharp G, Li Q, Shih H, El Fakhri G, Ra J, Woo J. Subject-specific brain tumor growth modelling via an efficient Bayesian inference framework. Proceedings Of SPIE--the International Society For Optical Engineering 2018, 10574: 105742i. PMID: 30050231, PMCID: PMC6056378, DOI: 10.1117/12.2293145.Peer-Reviewed Original ResearchTumor growthOptimal treatmentExternal beam radiotherapyBrain tumor progressionBeam radiotherapyBrain tumor growthTumor growth modelTumor infiltrationTumor parametersTumor progressionEffective therapyClinical dataTherapy planningTumorIndividualized therapyTherapyTumor boundariesProliferation rateRadiotherapyNon-invasiveState-of-the-art methodsTreatmentState-of-the-artChemotherapy