2020
Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer
Stark S, Wang C, Savic LJ, Letzen B, Schobert I, Miszczuk M, Murali N, Oestmann P, Gebauer B, Lin M, Duncan J, Schlachter T, Chapiro J. Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer. Scientific Reports 2020, 10: 18026. PMID: 33093524, PMCID: PMC7582153, DOI: 10.1038/s41598-020-75120-7.Peer-Reviewed Original ResearchConceptsConventional transarterial chemoembolizationLipiodol depositionTransarterial chemoembolizationLiver cancerPeripheral depositionLipiodol depositsTherapeutic efficacyNecrotic tumor areasBaseline MRITherapy optionsTumor responseTreatment responseTumor volumeLiver lesionsLipiodolH postTumor areaH-CTHounsfield unitsBiomarkersChemoembolizationHigh rateTumorsCancerImproved response
2018
Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI
Li X, Dvornek NC, Zhuang J, Ventola P, Duncan JS. Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI. Lecture Notes In Computer Science 2018, 11072: 206-214. PMID: 32984865, PMCID: PMC7519581, DOI: 10.1007/978-3-030-00931-1_24.Peer-Reviewed Original ResearchDeep neural networksFunctional magnetic resonance imagingBrain functional magnetic resonance imagingAutism spectrum disorderComputer visionDeep learningDNN classifierMagnetic resonance imagingCorrupt imagesNeural networkSaliency featuresClassification scenariosNeurological functionControl subjectsComplex neurodevelopmental disorderEarly diagnosisComputational decisionReliable biomarkersResonance imagingBiomarker interpretationBiomarkersDetected biomarkersNeurodevelopmental disordersBrain featuresClassifier