B
Bing Bai
Researcher at University of Southern California
Publications - 35
Citations - 911
Bing Bai is an academic researcher from University of Southern California. The author has contributed to research in topics: Imaging phantom & Iterative reconstruction. The author has an hindex of 15, co-authored 35 publications receiving 858 citations. Previous affiliations of Bing Bai include Siemens & Columbia University.
Papers
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Journal ArticleDOI
Optimization and performance evaluation of the microPET II scanner for in vivo small-animal imaging.
Yang Yongfeng,Yuan-Chuan Tai,Stefan Siegel,D.F. Newport,Bing Bai,Quanzheng Li,Richard M. Leahy,Simon R. Cherry +7 more
TL;DR: This work demonstrates that different scanner settings are necessary to optimize the NEC count rate for different-sized animals and different injected doses.
Journal ArticleDOI
Tumor quantification in clinical positron emission tomography.
TL;DR: The current status of tumor quantification methods and their applications to clinical oncology are reviewed, and factors that impede quantitative assessment and limit its accuracy and reproducibility are summarized.
Journal ArticleDOI
Magnetic resonance-guided positron emission tomography image reconstruction.
TL;DR: This article reviews research efforts over the past 20 years to develop model-based PET reconstruction methods based on the use of both Markov random field priors and joint information or entropy measures, and discusses approaches based onThe general framework for these methods is described, and their performance and longer-term potential and limitations are discussed.
Journal ArticleDOI
Model-based normalization for iterative 3D PET image reconstruction.
Bing Bai,Quanzheng Li,C H Holdsworth,Evren Asma,Yuan-Chuan Tai,Arion F. Chatziioannou,Richard M. Leahy +6 more
TL;DR: A maximum likelihood approach to joint estimation of the count-rate independent normalization factors, which is an extension of previous factored normalization methods in which separate factors for detector sensitivity, geometric response, block effects and deadtime are included.
Proceedings ArticleDOI
Positron range modeling for statistical PET image reconstruction
TL;DR: In this article, a 3D isotropic shift-invariant blur kernel is proposed to estimate the range of positrons in a homogeneous medium and a new shift-variant blurring model for positron range that accounts for spatial inhomogeneities in the positron scatter properties of the medium is proposed.