Featured Publications
Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation
Avesta A, Hossain S, Lin M, Aboian M, Krumholz H, Aneja S. Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation. Bioengineering 2023, 10: 181. PMID: 36829675, PMCID: PMC9952534, DOI: 10.3390/bioengineering10020181.Peer-Reviewed Original ResearchLimited training dataDice scoreComputational memoryTraining dataBrain imagesDeep-learning methodsHigher Dice scoresSegmentation accuracyAuto-segmentation modelComputational speedPerformance metricsOne-sliceAuto-SegmentationBetter performanceConsecutive slicesImagesDeploymentLowest Dice scoresMemoryPerformanceTrainingMetricsModelAccuracyDataComparing Detection Schemes for Adversarial Images against Deep Learning Models for Cancer Imaging
Joel M, Avesta A, Yang D, Zhou J, Omuro A, Herbst R, Krumholz H, Aneja S. Comparing Detection Schemes for Adversarial Images against Deep Learning Models for Cancer Imaging. Cancers 2023, 15: 1548. PMID: 36900339, PMCID: PMC10000732, DOI: 10.3390/cancers15051548.Peer-Reviewed Original ResearchAdversarial imagesDeep learning modelsDL modelsDetection modelLearning modelConvolutional neural networkDetection schemeAdversarial detectionDefense techniquesMachine learningMedical imagesAdversarial perturbationsInput imageAdversarial trainingNeural networkArt performanceMagnetic resonance imagingGradient descentPixel valuesHigh accuracyImagesBrain magnetic resonance imagingAbsence of malignancyClassificationScheme3D Capsule Networks for Brain Image Segmentation
Avesta A, Hui Y, Aboian M, Duncan J, Krumholz H, Aneja S. 3D Capsule Networks for Brain Image Segmentation. American Journal Of Neuroradiology 2023, 44: 562-568. PMID: 37080721, PMCID: PMC10171390, DOI: 10.3174/ajnr.a7845.Peer-Reviewed Original Research
2018
Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation?
Thompson RF, Valdes G, Fuller CD, Carpenter CM, Morin O, Aneja S, Lindsay WD, Aerts HJWL, Agrimson B, Deville C, Rosenthal SA, Yu JB, Thomas CR. Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation? Radiotherapy And Oncology 2018, 129: 421-426. PMID: 29907338, PMCID: PMC9620952, DOI: 10.1016/j.radonc.2018.05.030.Peer-Reviewed Original ResearchConceptsArtificial intelligenceFuture of AIRole of AIImpact of AIAutonomous transportationMedical imagesFacial recognitionIntelligenceDisruptive transformationIndustrial revolutionCurrent stateKey topicsInterventional natureImagesLarge spectrumRecognitionTechnologyComplex interpretationProcessingDisruptive forcesDiagnostic radiologyHealthcare