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Enhao Gong

EnhaoGongisaPhDstudentinelectricalengineeringatStanford,whereheisadvisedbyJohnPauly(electricalengineering)andGregZaharchuk(radiology),andthefounderandresearcheratSubtleMedical,heispushingtheperformanceofdeeplearningmethodstoboosttheefficiencyandvalueformedicalimaging.Hisresearchfocusesonapplyingmachinelearning,deeplearning,andoptimizationformedicalimagingreconstructionandprocessing.Recently,EnhaohasbeenworkingtobridgedeeplearningmethodswithMRIreconstruction,suchasenhancingimagequalitywithdeeplearningandmulticontrastinformation,solvingquantitativeimaging(water-fatseparation,QSM,parametermapping)usingdeeplearningframeworks,andusinggenerativeadversarialnetworks(GANs)forcompressedsensingMRI.

http://www.zcmsonline.com/index.php/zkzj/111439.html

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Enhao Gong is a PhD student in electrical engineering at Stanford, where he is advised by John Pauly (electrical engineering) and Greg Zaharchuk (radiology), and the founder and researcher at Subtle Medical, he is pushing the performance of deep learning methods to boost the efficiency and value for medical imaging. His research focuses on applying machine learning, deep learning, and optimization for medical imaging reconstruction and processing. Recently, Enhao has been working to bridge deep learning methods with MRI reconstruction, such as enhancing image quality with deep learning and multicontrast information, solving quantitative imaging (water-fat separation, QSM, parameter mapping) using deep learning frameworks, and using generative adversarial networks (GANs) for compressed sensing MRI.

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