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 ResearchMeSH KeywordsCarcinoma, HepatocellularHumansLiver NeoplasmsMachine LearningMagnetic Resonance ImagingNeoplasm Recurrence, LocalRetrospective StudiesDeep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application
Shi L, Zhang J, Toyonaga T, Shao D, Onofrey J, Lu Y. Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application. Physics In Medicine And Biology 2023, 68: 035014. PMID: 36584395, DOI: 10.1088/1361-6560/acaf49.Peer-Reviewed Original Research
2020
Magnetic resonance image connectivity analysis provides evidence of central nervous system mode of action for parasacral transcutaneous electro neural stimulation - A pilot study
Netto JMB, Scheinost D, Onofrey JA, Franco I. Magnetic resonance image connectivity analysis provides evidence of central nervous system mode of action for parasacral transcutaneous electro neural stimulation - A pilot study. Journal Of Pediatric Urology 2020, 16: 536-542. PMID: 32873504, DOI: 10.1016/j.jpurol.2020.08.002.Peer-Reviewed Original ResearchMeSH KeywordsAdultBrainHumansMagnetic Resonance ImagingPilot ProjectsTranscutaneous Electric Nerve StimulationUrinary Bladder, OveractiveConceptsDorsal lateral prefrontal cortexAnterior cingulate cortexOveractive bladderFunctional connectivityPrefrontal cortexUrinary tract symptomsSacral nerve stimulatorCommon treatment modalityRight scapular regionACC functional connectivityResting-state conditionsMechanism of actionTract symptomsMotor thresholdCentral effectsACC connectivityNerve stimulatorSacral levelTreatment modalitiesFunctional connectivity dataMechanism of effectivenessAdult volunteersFrontal lobeSubcortical regionsCingulate cortex
2017
Learning Non-rigid Deformations for Robust, Constrained Point-based Registration in Image-Guided MR-TRUS Prostate Intervention
Onofrey JA, Staib LH, Sarkar S, Venkataraman R, Nawaf CB, Sprenkle PC, Papademetris X. Learning Non-rigid Deformations for Robust, Constrained Point-based Registration in Image-Guided MR-TRUS Prostate Intervention. Medical Image Analysis 2017, 39: 29-43. PMID: 28431275, PMCID: PMC5514316, DOI: 10.1016/j.media.2017.04.001.Peer-Reviewed Original Research
2015
Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients
Onofrey JA, Staib LH, Papademetris X. Learning intervention-induced deformations for non-rigid MR-CT registration and electrode localization in epilepsy patients. NeuroImage Clinical 2015, 10: 291-301. PMID: 26900569, PMCID: PMC4724039, DOI: 10.1016/j.nicl.2015.12.001.Peer-Reviewed Original ResearchSegmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration
Onofrey JA, Staib LH, Papademetris X. Segmenting the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration. Lecture Notes In Computer Science 2015, 24: 662-674. PMID: 26221711, PMCID: PMC5266617, DOI: 10.1007/978-3-319-19992-4_52.Peer-Reviewed Original Research
2013
Learning Nonrigid Deformations for Constrained Multi-modal Image Registration
Onofrey JA, Staib LH, Papademetris X. Learning Nonrigid Deformations for Constrained Multi-modal Image Registration. Lecture Notes In Computer Science 2013, 16: 171-178. PMID: 24505758, PMCID: PMC4044829, DOI: 10.1007/978-3-642-40760-4_22.Peer-Reviewed Original Research