2024
Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning
Pak D, Liu M, Kim T, Liang L, Caballero A, Onofrey J, Ahn S, Xu Y, McKay R, Sun W, Gleason R, Duncan J. Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning. IEEE Transactions On Medical Imaging 2024, 43: 203-215. PMID: 37432807, PMCID: PMC10764002, DOI: 10.1109/tmi.2023.3294128.Peer-Reviewed Original ResearchConceptsFinite element analysisDeep learning methodsSpatial accuracyElement analysisDeep learningStress estimationLearning methodsSimulation accuracyDeployment simulationHigh spatial accuracyThin structuresMesh generationVolumetric meshingDeformation energyGeometry modelingVolumetric meshMesh qualityElement qualitySimultaneous optimizationMain noveltyBiomechanics studiesMeshModeling characteristicsAccuracyDownstream analysis
2020
A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation
Liang Y, Muhammad W, Hart GR, Nartowt BJ, Chen ZJ, Yu JB, Roberts KB, Duncan JS, Deng J. A general-purpose Monte Carlo particle transport code based on inverse transform sampling for radiotherapy dose calculation. Scientific Reports 2020, 10: 9808. PMID: 32555530, PMCID: PMC7300009, DOI: 10.1038/s41598-020-66844-7.Peer-Reviewed Original ResearchConceptsPhoton transportBoundary crossing algorithmMonte Carlo particle transport codeMonte Carlo methodTransport simulationsAcceptance-rejection samplingRadiotherapy dose calculationsPhoto-electric effectParticle transport codeEGSnrc simulationsCarlo methodBremsstrahlung eventsInelastic scatteringPair productionRayleigh scatteringThread divergenceMC simulationsTransport codeMC codeHistory schemeParticle transportCrossing algorithmInverseElectron transportSimulation accuracy