45SESSION 3 : Imaging of Cell Population Dynamics and AI PredictionSESSION 4 : AI for Brain Imaging１．EverythingasCodeDavid Van ValenCaliforniaInstituteofTechnology２．AnInteractiveDeepLearning-basedApproachRevealsMitochondrialCristaeTopologiesYusuke HirabayashiTheUniversityofTokyo３．EstablishmentofCellular‘Dynalogy’–anAI-basedNovelResearchTrendforUnderstandingtheLifeActivityBasedonTheirDynamicNatureMasaru IshiiOsakaUniversity４．NetworkCellMeasurementsviaMultimodalBarcodedDropletsSadao OtaTheUniversityofTokyo５．Super-resolutionImagingofTranscriptioninLivingCellsIbrahim CisséMPIofImmunobiologyandEpigenetics１．ChallengesandResourcesforMakingBigNeuroscienceDataOpen,FAIRandAIReadyMaryann E. MartoneUCSD２．iPSCDataScience:CellularDissectionofPolygenicityUncoveringthePolygenicArchitectureofAlzheimer’sDiseaseHaruhisa InoueKyotoUniversity３．NeuronalSignalsRegulatingEmotionandMemoryKozo KaibuchiFujitaHealthUniversity４．Label-freeImagingofIntracellularDynamicsCombinedwithMulti-omicsApproachforInducedPluripotentStemCellsYohei HayashiRIKEN
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