2024
Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation
Zhou Y, Chen T, Hou J, Xie H, Dvornek N, Zhou S, Wilson D, Duncan J, Liu C, Zhou B. Cascaded Multi-path Shortcut Diffusion Model for Medical Image Translation. Medical Image Analysis 2024, 98: 103300. PMID: 39226710, PMCID: PMC11979896, DOI: 10.1016/j.media.2024.103300.Peer-Reviewed Original ResearchGenerative adversarial networkMedical image translationImage translationState-of-the-art methodsImage-to-image translationMedical image datasetsImage translation tasksImage-to-imageState-of-the-artMedical image processingHigh-quality translationsUncertainty estimationCascaded pipelineAdversarial networkImage datasetsSub-tasksTranslation qualityTranslation performanceTranslation tasksImage processingTranslation resultsDM methodPrior imageRobust performanceExperimental resultsA deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression
Lee W, Zhuo Y, Marin T, Han P, Chi D, El Fakhri G, Ma C. A deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/0259.Peer-Reviewed Original ResearchDeep learning-based methodsLearning-based methodsU-Net structureSignal removalIn vivo MRSI dataNeural networkU-NetMRSI dataImage reconstructionSuperior performanceData processingRobust performanceHankel matrixNetworkNuisance signalsConventional methodsPerformanceMRSI signalsSignalMethodRemove nuisance signalsRemovalHankel
2020
A Comparison between Mouse, In Silico, and Robot Odor Plume Navigation Reveals Advantages of Mouse Odor Tracking
Gumaste A, Coronas-Samano G, Hengenius J, Axman R, Connor EG, Baker KL, Ermentrout B, Crimaldi JP, Verhagen JV. A Comparison between Mouse, In Silico, and Robot Odor Plume Navigation Reveals Advantages of Mouse Odor Tracking. ENeuro 2020, 7: eneuro.0212-19.2019. PMID: 31924732, PMCID: PMC7004486, DOI: 10.1523/eneuro.0212-19.2019.Peer-Reviewed Original ResearchConceptsOdor localizationArduino RobotMinimal algorithmLow complexityTemporal modelNavigationOdor sourceLocalization of odorsComplexityRobust performanceAlgorithmChaotic environmentOdor-based navigationSame environmentEnvironmental complexityEnvironmentRobotPerformanceFast movementsArduinoComplex strategiesSuccessful performanceChaotic natureModel
2014
Limits of Feedback Control in Bacterial Chemotaxis
Dufour YS, Fu X, Hernandez-Nunez L, Emonet T. Limits of Feedback Control in Bacterial Chemotaxis. PLOS Computational Biology 2014, 10: e1003694. PMID: 24967937, PMCID: PMC4072517, DOI: 10.1371/journal.pcbi.1003694.Peer-Reviewed Original ResearchConceptsFeedback controlIntegral feedback controlOperational regimesOptimal operational regimeComplex statisticsDrift velocityRobust performanceFuture inputsAdaptation rateProper information transferChemotactic driftAnalytical modelInput signalOptimal regimeActuatorsSteep gradientsProper couplingWide rangeChemotactic performanceRegimeBifurcation
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