2022
Brain Tumor Imaging: Applications of Artificial Intelligence
Afridi M, Jain A, Aboian M, Payabvash S. Brain Tumor Imaging: Applications of Artificial Intelligence. Seminars In Ultrasound CT And MRI 2022, 43: 153-169. PMID: 35339256, PMCID: PMC8961005, DOI: 10.1053/j.sult.2022.02.005.Peer-Reviewed Original ResearchConceptsArtificial intelligenceDeep learning systemDeep learning-based artificial intelligenceMachine learningImage processingLearning systemIntelligencePopular fieldDecision-making processPredictive modelRadiomic featuresNeuro-oncologyDecision-making protocolClinical decision-making protocolsMachineClinical decision-making processLearningBrain tumor imagingFeaturesClassificationImaging featuresProcessingTreatment responseMolecular classificationProtocol
2020
A Fully Automated Method for Segmenting Arteries and Quantifying Vessel Radii on Magnetic Resonance Angiography Images of Varying Projection Thickness
Avadiappan S, Payabvash S, Morrison MA, Jakary A, Hess CP, Lupo JM. A Fully Automated Method for Segmenting Arteries and Quantifying Vessel Radii on Magnetic Resonance Angiography Images of Varying Projection Thickness. Frontiers In Neuroscience 2020, 14: 537. PMID: 32612496, PMCID: PMC7308498, DOI: 10.3389/fnins.2020.00537.Peer-Reviewed Original ResearchAutomatic segmentationManual segmentationDice similarity coefficientEntire 3D volumeSegmentation of vesselsMagnetic resonance angiography imagesSegmentation accuracyImage processingSegmentation algorithmSynthetic datasetsF-scoreRobust segmentationDifferent noise levelsNovel algorithmSegmentationFrangi filterPrior methodsJaccard indexNoisy conditionsLow contrastMRA datasetsDatasetAutomated methodSimilarity coefficientAlgorithm