2024
Towards mitigating uncann(eye)ness in face swaps via gaze-centric loss terms
Wilson E, Shic F, Jörg S, Jain E. Towards mitigating uncann(eye)ness in face swaps via gaze-centric loss terms. Computers & Graphics 2024, 119: 103888. DOI: 10.1016/j.cag.2024.103888.Peer-Reviewed Original Research
2023
Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey
Ghosh A, Urry C, Mishra A, Perreault-Levasseur L, Natarajan P, Sanders D, Nagai D, Tian C, Cappelluti N, Kartaltepe J, Powell M, Rau A, Treister E. Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey. The Astrophysical Journal 2023, 953: 134. DOI: 10.3847/1538-4357/acd546.Peer-Reviewed Original ResearchSource codeMachine-learning algorithmsMachine-learning frameworkData setsTransfer learningEstimation networkPrevious stateProfile fitting algorithmReal dataNancy Grace Roman Space TelescopeRoman Space TelescopeLarge imaging surveysAlgorithmFitting algorithmUncertainty quantificationSimulations of galaxiesBayesian posteriorPosterior distributionExternal cataloguesFirst trainingSpace TelescopeGalaxy bulgesLight ratioSignificant improvementGalaxies
2022
Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network
Guo X, Zhou B, Pigg D, Spottiswoode B, Casey ME, Liu C, Dvornek NC. Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network. Medical Image Analysis 2022, 80: 102524. PMID: 35797734, PMCID: PMC10923189, DOI: 10.1016/j.media.2022.102524.Peer-Reviewed Original ResearchConceptsConvolutional neural networkNeural networkConvolutional long short-term memory (ConvLSTM) layersDeep learning-based frameworkConvolutional long short-term memoryLong short-term memory layersDeep learning baselinesLong short-term memoryDynamic temporal featuresLearning-based frameworkDeep learning approachShort-term memory layersTracer distribution changeMotion estimation networkMotion prediction errorInference timeEstimation networkLearning baselinesNon-rigid registration methodLearning approachMotion correction methodMemory layerShort-term memoryTemporal featuresRegistration method
2021
MDPET: A Unified Motion Correction and Denoising Adversarial Network for Low-Dose Gated PET
Zhou B, Tsai YJ, Chen X, Duncan JS, Liu C. MDPET: A Unified Motion Correction and Denoising Adversarial Network for Low-Dose Gated PET. IEEE Transactions On Medical Imaging 2021, 40: 3154-3164. PMID: 33909561, PMCID: PMC8588635, DOI: 10.1109/tmi.2021.3076191.Peer-Reviewed Original ResearchConceptsMotion estimationPyramid networkAdversarial networkAccurate motion estimationMotion correctionLow-noise reconstructionGated positron emission tomographyMotion correction methodMotion estimation networkGated PET dataEstimation networkRecurrent layersDenoising NetworkRespiratory motion blurringExperimental resultsLow-noise imagesMotion blurringNoise levelCorrection methodNetworkPET reconstructionPrevious methodsImage qualityImagesEstimation
2020
Simultaneous Denoising and Motion Estimation for Low-Dose Gated PET Using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning
Zhou B, Tsai Y, Liu C. Simultaneous Denoising and Motion Estimation for Low-Dose Gated PET Using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning. Lecture Notes In Computer Science 2020, 12267: 743-752. DOI: 10.1007/978-3-030-59728-3_72.Peer-Reviewed Original ResearchMotion estimationMotion estimation networkRobust motion estimationMotion correction methodRespiratory motion blurringEstimation networkNoise ratioMotion correctionMotion blurringImage volumesCorrection methodCorrection stepMotion vectorsGateSimultaneous denoisingImage qualityEstimationAdversarial network
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