2022
Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities
Merkaj S, Bahar RC, Zeevi T, Lin M, Ikuta I, Bousabarah K, Petersen G, Staib L, Payabvash S, Mongan JT, Cha S, Aboian MS. Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities. Cancers 2022, 14: 2623. PMID: 35681603, PMCID: PMC9179416, DOI: 10.3390/cancers14112623.Peer-Reviewed Original ResearchMachine learning toolsGrade predictionLearning toolsML applicationsClassifier algorithmML modelsClassification methodMedical imagingData sourcesPractices of radiologistsToolGlioma gradingNext stepWorkflowAlgorithmChallengesTechnological innovationImplementationPredictionModelLast decadeSpecific areas
2003
Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis
Papademetris X, Jackowski A, Schultz R, Staib L, Duncan J. Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis. Lecture Notes In Computer Science 2003, 2879: 788-795. DOI: 10.1007/978-3-540-39903-2_96.Peer-Reviewed Original ResearchRobust Point MatchingIntensity-based registrationLarge point setsPoint matchingGreater computational efficiencyComputational efficiencyRobust pointSuperior performancePoint setsMagnetic resonance imagesBrain registrationActivation mapsFunctional magnetic resonance imagesSuccessful applicationRegistrationResonance imagesAlgorithmMatchingSpecificationMethodologyImagesRobustnessFrameworkSpecific areasSet