2025
Efficient few-shot medical image segmentation via self-supervised variational autoencoder
Zhou Y, Zhou F, Xi F, Liu Y, Peng Y, Carlson D, Tu L. Efficient few-shot medical image segmentation via self-supervised variational autoencoder. Medical Image Analysis 2025, 104: 103637. PMID: 40449308, DOI: 10.1016/j.media.2025.103637.Peer-Reviewed Original ResearchConceptsFew-shot medical image segmentationMedical image segmentationUnlabeled imagesVariational autoencoderImage segmentationMulti-modality medical image datasetEnd-to-end modelDice scoreFully-supervised methodsMedical image datasetsSelf-supervised learningImproving feature extractionEnd-to-endSecond-best methodSegmentation taskFeature extractionImage datasetsData augmentationSource codePrevent overfittingTraining dataReconstruction taskStructural priorsSegmentation qualityLabeled atlases
2023
Dual-Domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-Angle Reconstruction of Low-Dose Cardiac SPECT
Chen X, Zhou B, Xie H, Guo X, Liu Q, Sinusas A, Liu C. Dual-Domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-Angle Reconstruction of Low-Dose Cardiac SPECT. Lecture Notes In Computer Science 2023, 14307: 49-59. DOI: 10.1007/978-3-031-44917-8_5.Peer-Reviewed Original ResearchIterative networkAuxiliary modulesJoint denoisingLow reconstruction accuracySource codeData consistencyNetwork performanceAblation studiesReconstruction accuracyCardiac SPECTConsistency moduleHardware expensePrediction accuracyAngle reconstructionNetworkDenoisingImage noiseAngle projectionsModuleADC moduleAccuracyReconstructionImagesMPI dataCodeMorphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey
Ghosh A, Urry C, Mishra A, Perreault-Levasseur L, Natarajan P, Sanders D, Nagai D, Tian C, Cappelluti N, Kartaltepe J, Powell M, Rau A, Treister E. Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey. The Astrophysical Journal 2023, 953: 134. DOI: 10.3847/1538-4357/acd546.Peer-Reviewed Original ResearchSource codeMachine-learning algorithmsMachine-learning frameworkData setsTransfer learningEstimation networkPrevious stateProfile fitting algorithmReal dataNancy Grace Roman Space TelescopeRoman Space TelescopeLarge imaging surveysAlgorithmFitting algorithmUncertainty quantificationSimulations of galaxiesBayesian posteriorPosterior distributionExternal cataloguesFirst trainingSpace TelescopeGalaxy bulgesLight ratioSignificant improvementGalaxiesCross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available
Dadashkarimi J, Karbasi A, Liang Q, Rosenblatt M, Noble S, Foster M, Rodriguez R, Adkinson B, Ye J, Sun H, Camp C, Farruggia M, Tejavibulya L, Dai W, Jiang R, Pollatou A, Scheinost D. Cross Atlas Remapping via Optimal Transport (CAROT): Creating connectomes for different atlases when raw data is not available. Medical Image Analysis 2023, 88: 102864. PMID: 37352650, PMCID: PMC10526726, DOI: 10.1016/j.media.2023.102864.Peer-Reviewed Original ResearchConceptsDifferent atlasesRaw data accessWeb applicationData accessOpen source dataSource codePatient privacyOptimal transportRaw dataStorage concernsLarge-scale data collection effortsOriginal counterpartsExtensive setData collection effortsProcessing effortPredictive modelNeuroimaging dataDownstream analysisPrivacyAtlasesCollection effortsComputationalTime seriesDatasetConnectomeDuSFE: Dual-Channel Squeeze-Fusion-Excitation co-attention for cross-modality registration of cardiac SPECT and CT
Chen X, Zhou B, Xie H, Guo X, Zhang J, Duncan J, Miller E, Sinusas A, Onofrey J, Liu C. DuSFE: Dual-Channel Squeeze-Fusion-Excitation co-attention for cross-modality registration of cardiac SPECT and CT. Medical Image Analysis 2023, 88: 102840. PMID: 37216735, PMCID: PMC10524650, DOI: 10.1016/j.media.2023.102840.Peer-Reviewed Original ResearchConceptsCross-modality registrationConvolutional layersCo-attention mechanismMultiple convolutional layersCo-attention moduleDifferent convolutional layersMedical image registrationInput data streamDeep learning strategiesLow registration errorIntensity-based registration methodCardiac SPECTΜ-mapsDeep learningFeature fusionData streamsInput imageSource codeFeature mapsNeural networkImage registrationSpatial featuresRegistration performanceRegistration methodInput informationAIONER: all-in-one scheme-based biomedical named entity recognition using deep learning
Luo L, Wei C, Lai P, Leaman R, Chen Q, Lu Z. AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning. Bioinformatics 2023, 39: btad310. PMID: 37171899, PMCID: PMC10212279, DOI: 10.1093/bioinformatics/btad310.Peer-Reviewed Original ResearchConceptsDeep learningEntity recognitionTraining dataEntity typesLabeling training dataNatural language textText mining tasksSignificant domain expertiseMulti-task learningMining tasksInformation extractionBioNER taskDomain expertiseBiomedical entitiesIndependent tasksSource codeBenchmark tasksLanguage textBiomedical textArt approachesAccurate annotationExternal dataData scarcityTaskLearning
2022
Assigning species information to corresponding genes by a sequence labeling framework
Luo L, Wei C, Lai P, Chen Q, Islamaj R, Lu Z. Assigning species information to corresponding genes by a sequence labeling framework. Database 2022, 2022: baac090. PMID: 36227127, PMCID: PMC9558450, DOI: 10.1093/database/baac090.Peer-Reviewed Original ResearchConceptsNovel deep learning-based frameworkDeep learning-based frameworkLearning-based frameworkText mining algorithmsSequence labeling taskGene normalization taskSequence labeling frameworkBinary classification frameworkSource codeBaseline methodsNormalization taskClassification frameworkLabeling taskLabeling frameworkAutomatic assignmentHigh-performance methodHeuristic rulesGene mentionsBenchmarking resultsDatabase URLDatabase recordsAssignment taskDual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CT
Chen X, Zhou B, Xie H, Guo X, Zhang J, Sinusas A, Onofrey J, Liu C. Dual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CT. Lecture Notes In Computer Science 2022, 13436: 46-55. DOI: 10.1007/978-3-031-16446-0_5.Peer-Reviewed Original ResearchConvolutional neural networkCross-modality registrationFeature fusionPrevious convolutional neural networkEarly feature fusionCross-modality informationMultiple convolutional layersMedical image registrationLow registration errorCardiac SPECTConvolutional layersCNN moduleImage featuresLate fusionSource codeNeural networkExcitation moduleInput modalitiesImage registrationSpatial featuresMultiple modalitiesRegistration errorPrevious methodsRigid registrationNetworkNODeJ: an ImageJ plugin for 3D segmentation of nuclear objects
Dubos T, Poulet A, Thomson G, Péry E, Chausse F, Tatout C, Desset S, van Wolfswinkel JC, Jacob Y. NODeJ: an ImageJ plugin for 3D segmentation of nuclear objects. BMC Bioinformatics 2022, 23: 216. PMID: 35668354, PMCID: PMC9169307, DOI: 10.1186/s12859-022-04743-6.Peer-Reviewed Original ResearchConceptsImageJ pluginCommand-line optionsChromatin organizationThree-dimensional imaging technologyArabidopsis thaliana nucleiDNA FISH experimentsNodeJSSource codePublic datasetsProgram segmentsReduced processing timePluginProcessing timeAbiotic stressesHeterochromatin domainsLaplacian convolutionFISH experimentsSubnuclear structuresCellular processesHigh-throughput analysisPlant systemsProcessing methodsDiverse setImaging technologyImagesMedTator: a serverless annotation tool for corpus development
He H, Fu S, Wang L, Liu S, Wen A, Liu H. MedTator: a serverless annotation tool for corpus development. Bioinformatics 2022, 38: 1776-1778. PMID: 34983060, PMCID: PMC10060696, DOI: 10.1093/bioinformatics/btab880.Peer-Reviewed Original ResearchConceptsAnnotation toolInteractive user interfaceApache 2.0 licenseDocument annotationUser interfaceAnnotation taskSource codeAdvanced featuresDifficulty of useAnnotation corpusCorpus developmentCorpus annotationCore stepsSupplementary dataVariety of needsAnnotationClinical research applicationsSummarizationResearch applicationsToolConsiderable timeTaskBioinformaticsTutorialCode
2021
CNVpytor: a tool for copy number variation detection and analysis from read depth and allele imbalance in whole-genome sequencing
Suvakov M, Panda A, Diesh C, Holmes I, Abyzov A. CNVpytor: a tool for copy number variation detection and analysis from read depth and allele imbalance in whole-genome sequencing. GigaScience 2021, 10: giab074. PMID: 34817058, PMCID: PMC8612020, DOI: 10.1093/gigascience/giab074.Peer-Reviewed Original ResearchUltrafast homomorphic encryption models enable secure outsourcing of genotype imputation
Kim M, Harmanci A, Bossuat J, Carpov S, Cheon J, Chillotti I, Cho W, Froelicher D, Gama N, Georgieva M, Hong S, Hubaux J, Kim D, Lauter K, Ma Y, Ohno-Machado L, Sofia H, Son Y, Song Y, Troncoso-Pastoriza J, Jiang X. Ultrafast homomorphic encryption models enable secure outsourcing of genotype imputation. Cell Systems 2021, 12: 1108-1120.e4. PMID: 34464590, PMCID: PMC9898842, DOI: 10.1016/j.cels.2021.07.010.Peer-Reviewed Original ResearchConceptsHomomorphic encryption techniqueResource-intensive computationsSecure outsourcingGenomic data analysisData securityEncryption modelEncryption techniquePrivacy concernsSource codeMemory requirementsGenetic data analysisData analysisComparable accuracyFundamental stepGenotype imputationImputationDownloadSecurityOutsourcingComputationCodeServicesRequirementsAccuracyMethodBenchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track
Kuo T, Bath T, Ma S, Pattengale N, Yang M, Cao Y, Hudson C, Kim J, Post K, Xiong L, Ohno-Machado L. Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track. International Journal Of Medical Informatics 2021, 154: 104559. PMID: 34474309, PMCID: PMC9933142, DOI: 10.1016/j.ijmedinf.2021.104559.Peer-Reviewed Original ResearchConceptsSecure genome analysis competitionData retrieval queriesBlockchain-based methodData sharing methodReal-world problemsQuery indexType of sharingRetrieval queriesBlockchain technologyLedger technologySource codeBlockchain utilizationBlockchain strategyHealthcare applicationsInteraction recordsSharing methodTest datasetSharing recordsBiomedical research applicationsConsortium resourcesNew platformPatient recordsBlockchainQueriesTechnologyChemsearch: collaborative compound libraries with structure-aware browsing
Gaffney S, Smaga S, Schepartz A, Townsend J. Chemsearch: collaborative compound libraries with structure-aware browsing. Bioinformatics Advances 2021, 1: vbab008. PMID: 36700113, PMCID: PMC9710581, DOI: 10.1093/bioadv/vbab008.Peer-Reviewed Original ResearchAccess controlServer applicationsWeb applicationDocker imageSource codeData storageEasy navigationRapid deploymentData filesCompound librariesCompounds of interestChemical compound librariesBrowsingLibraryNavigationSimilar compoundsDeploymentFilesApplicationsStructural propertiesImagesCompoundsImplementationCodeDocuments
2020
COSIFER: a Python package for the consensus inference of molecular interaction networks
Manica M, Bunne C, Mathis R, Cadow J, Ahsen M, Stolovitzky G, Martínez M. COSIFER: a Python package for the consensus inference of molecular interaction networks. Bioinformatics 2020, 37: 2070-2072. PMID: 33241320, PMCID: PMC8337002, DOI: 10.1093/bioinformatics/btaa942.Peer-Reviewed Original ResearchConceptsAdvent of high-throughput technologiesNetwork inferenceMolecular interaction networksHigh-throughput dataHigh-throughput technologiesState-of-the-artSupplementary dataExpression dataInteraction networkPython source codeInference servicesState-of-the-art methodologiesWeb servicesSource codeMolecular networksWeb-based platformRegulatory apparatusBioinformaticsPython packageConsensus strategyNetworkRobust networkInference methodsInferenceIndividual methodsA MATLAB tool for computing the spherical harmonic fractal dimension of the cerebral cortex
de Miras J, Martínez-Lledó G, Orwig W, Sepulcre J. A MATLAB tool for computing the spherical harmonic fractal dimension of the cerebral cortex. Computer Physics Communications 2020, 254: 107381. DOI: 10.1016/j.cpc.2020.107381.Peer-Reviewed Original ResearchGNU General Public License version 3 Programming languageC++ Nature of problemCPC Library linkLocal fractal dimension mapProblems of softwareNature of problemBox-counting algorithmGraphical user interfaceMATLAB source codeMATLAB programLibrary linkProgram filesSource codeUser interfaceOBJ formatCommand lineFD computationMATLAB toolFD algorithmSoftware suiteCortical surface vertexReconstructed surfaceAlgorithmSurface verticesMATLABNAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses
Wang S, Li W, Hu L, Cheng J, Yang H, Liu Y. NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses. Nucleic Acids Research 2020, 48: e83-e83. PMID: 32526036, PMCID: PMC7641313, DOI: 10.1093/nar/gkaa498.Peer-Reviewed Original Research
2019
GEM-NET: Lessons in Multi-Institution Teamwork Using Collaboration Software
Gaffney SG, Ad O, Smaga S, Schepartz A, Townsend JP. GEM-NET: Lessons in Multi-Institution Teamwork Using Collaboration Software. ACS Central Science 2019, 5: 1159-1169. PMID: 31404233, PMCID: PMC6661976, DOI: 10.1021/acscentsci.9b00111.Peer-Reviewed Original ResearchSoftware infrastructureMulti-institution teamOpen source codeCollaboration softwareCode editingData sharingSource codeTask managementCustom applicationsCollaborative documentInfrastructureCommunicationMultiple fieldsInternal communicationUsersUniversity campusSchedulingSecuritySharingSoftwareTeamCodeImplementationDocumentsGoal
2018
TQuest, A Web-Based Platform to Enable Precision Medicine by Linking a Tumor’s Genetic Defects to Therapeutic Options
Gershkovich P, Platt J, Knopf J, Tasoulis MK, Shi W, Pusztai L, Hatzis C. TQuest, A Web-Based Platform to Enable Precision Medicine by Linking a Tumor’s Genetic Defects to Therapeutic Options. JCO Clinical Cancer Informatics 2018, 2: 1-13. PMID: 30652574, DOI: 10.1200/cci.17.00120.Peer-Reviewed Original ResearchConceptsData acquisition layerFull-text indexAcquisition layerUser interfaceData layersPrototype web applicationWeb-based platformWeb applicationRelevance scoresSearch enginesSource codeSoftware toolsSearch resultsInterventional clinical trialsLabel dataClinical trialsTherapeutic optionsPlatformUS FoodMolecular abnormalitiesMetastatic breast cancerPotential therapeutic optionPotential treatment optionTumor DNA sequencingWeb-based modules
2017
A free, open-source tool for identifying urban agglomerations using polygon data
Day J, Chen Y, Ellis P, Roberts M. A free, open-source tool for identifying urban agglomerations using polygon data. Environment Systems And Decisions 2017, 37: 68-87. DOI: 10.1007/s10669-017-9623-z.Peer-Reviewed Original Research
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