2024
Point-supervised Brain Tumor Segmentation with Box-prompted Medical Segment Anything Model
Liu X, Woo J, Ma C, Ouyang J, Fakhri G. Point-supervised Brain Tumor Segmentation with Box-prompted Medical Segment Anything Model. 2011 IEEE Nuclear Science Symposium Conference Record 2024, 00: 1-1. PMID: 39445308, PMCID: PMC11497479, DOI: 10.1109/nss/mic/rtsd57108.2024.10656071.Peer-Reviewed Original ResearchSubject-aware PET Denoising with Contrastive Adversarial Domain Generalization
Liu X, Marin T, Eslahi S, Tiss A, Chemli Y, Johson K, Fakhri G, Ouyang J. Subject-aware PET Denoising with Contrastive Adversarial Domain Generalization. 2011 IEEE Nuclear Science Symposium Conference Record 2024, 00: 1-1. PMID: 39445307, PMCID: PMC11497478, DOI: 10.1109/nss/mic/rtsd57108.2024.10656150.Peer-Reviewed Original ResearchDomain generalizationDenoising performanceDenoising moduleDeep learningSubject-independent mannerSubject-invariant featuresSuperior denoising performanceAdversarial learning frameworkSubject-related informationConventional UNetBottleneck featuresTrustworthy systemsLearning frameworkDL modelsDL model performanceDenoisingNoise realizationsNegative samplesList-mode dataImage volumesModel performancePerformancePerformance of positron emission tomographyUNetFraction of eventsCross noise level PET denoising with continuous adversarial domain generalization
Liu X, Eslahi S, Marin T, Tiss A, Chemli Y, Huang Y, Johnson K, Fakhri G, Ouyang J. Cross noise level PET denoising with continuous adversarial domain generalization. Physics In Medicine And Biology 2024, 69: 085001. PMID: 38484401, PMCID: PMC11195012, DOI: 10.1088/1361-6560/ad341a.Peer-Reviewed Original ResearchDomain generalization techniqueDomain generalizationDenoising performanceSuperior denoising performanceLatent feature representationGeneral techniqueDistribution shiftsAdversarial trainingDenoised imageFeature representationDomain labelsDistribution divergenceNoise levelDeep learningImage spaceDenoisingPerformance degradationCore ideaNoise realizationsCD methodNoiseImage volumesPerformanceImagesPSNR
2021
Impact of reconstruction parameters on lesion detection and localization in joint ictal/inter-ictal SPECT reconstruction
Onwanna J, Chantadisai M, Tepmongkol S, Fahey F, Ouyang J, Rakvongthai Y. Impact of reconstruction parameters on lesion detection and localization in joint ictal/inter-ictal SPECT reconstruction. Annals Of Nuclear Medicine 2021, 36: 24-32. PMID: 34559366, DOI: 10.1007/s12149-021-01680-x.Peer-Reviewed Original ResearchConceptsLocalization receiver operating characteristicsDetection performanceSubtraction methodJoint methodOptimization iterationsLesion detection performanceSPECT reconstructionEpileptic focus localizationLocalization receiver operating characteristic curvesDifferential imagingInter-ictalLesion detectionIterationPhantom dataConventional subtraction methodPerformanceImagesPatient datasetsReconstruction parametersImpact of reconstruction parametersFocus localizationSubtractionDetectionSPECT dataJoint reconstruction