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UID:0-5627@eng.ufl.edu
DTSTART;TZID=America/New_York:20230206T150000
DTEND;TZID=America/New_York:20230206T160000
DTSTAMP:20251201T181911Z
URL:https://www.eng.ufl.edu/news-events/events/bme-seminar-optimization-of
 -pet-imaging-through-deep-learning-based-image-reconstruction-and-analysis
 /
SUMMARY:BME Seminar: Optimization of PET imaging through deep learning-base
 d image reconstruction and analysis
DESCRIPTION:Kuang Gong\, Ph.D.\, Assistant Professor of Radiology at Massac
 husetts General Hospital and Harvard Medical School\nPositron Emission Tom
 ography (PET) has wide applications in cardiology\, neurology\, and oncolo
 gy studies. To enable the quantitative nature of PET imaging\, accurate co
 rrections (e.g.\, attenuation correction and motion correction) are needed
 . Due to various physical degradation factors and limited counts received\
 , the signal-to-noise ratio (SNR) and resolution of PET is low\, which com
 prises its clinical values in diagnosis\, staging and treatment monitoring
 . In this talk\, I will introduce my works of further improving PET correc
 tion and image quality through deep learning-based image reconstruction an
 d analysis.\nBio:\nKuang Gong is an Assistant Professor of Radiology at Ma
 ssachusetts General Hospital and Harvard Medical School. He received his M
 .S. degree in Statistics and Ph.D. degree in Biomedical Engineering from U
 niversity of California\, Davis in 2015 and 2018\, respectively. His areas
  of expertise include medical imaging\, deep learning\, data science\, and
  image processing. His research goal is to combine deep learning\, medical
  imaging\, and data science to further improve the diagnosis and treatment
  of various diseases\, such as Alzheimer’s disease (AD) and cancer. To a
 chieve this\, his current research is conducted in three directions: deep 
 learning-based image reconstruction and analysis\, clinical task-driven de
 ep learning\, and multi-modality information integration for precision med
 icine. He has published 32 journal papers and is the Principal Investigato
 r of research grants from NIH. He received the Bruce H. Hasegawa Young Inv
 estigator Medical Imaging Science Award from the IEEE Nuclear and Plasma S
 ciences Society in 2021 for contributions to machine learning-based PET im
 age reconstruction\, denoising and attenuation correction.
CATEGORIES:Seminars
LOCATION:Communicore Room C1-17\, 1249 Center Dr.\, Gainesville\, FL\, 3261
 0\, United States
GEO:29.640849;-82.34479
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 le\, FL\, 32610\, United States;X-APPLE-RADIUS=100;X-TITLE=Communicore Roo
 m C1-17:geo:29.640849,-82.34479
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