Guobao Wang
University of California, Davis
AlgorithmParametric statisticsKernel methodBiomedical engineeringIterative reconstructionArtificial intelligenceIterative methodNoise reductionPattern recognitionPositron emission tomographyParametric ImageNuclear medicineComputer visionKernel (image processing)MathematicsComputer scienceImage qualityMedicineNoise (video)
90Publications
19H-index
1,173Citations
Publications 90
Newest
#1Will HutchcroftH-Index: 3
#2Guobao WangH-Index: 19
view all 13 authors...
In PET image reconstruction, regularization is often needed to reduce the noise in the resulting images. Patch-based image processing techniques have recently been successfully used for regularization in medical image reconstruction through a penalized likelihood framework. Re-parameterization within reconstruction is another powerful regularization technique in which the object in the scanner is re-parameterized using coefficients for spatially-extensive basis vectors. In this work, a method fo...
#1Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
#2Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
Motion compensation in PET imaging has become more and more important for obtaining high-resolution images. PET emission image and patient motion can be estimated simultaneously from gated data through a joint estimation framework. The resulting optimization problem, however, is challenging to solve. We propose an efficient algorithm for joint estimation by using the optimization transfer with the expectation maximization (EM) surrogate function. Each iteration of the algorithm consists of three...
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Apr 16, 2015 in ISBI (International Symposium on Biomedical Imaging)
#1Li Yang (UC Davis: University of California, Davis)H-Index: 4
#2Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
Last. Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
view all 3 authors...
Detecting cancerous lesion is a major clinical application in emission tomography. In previous work, we have studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by reconstructing ...
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Apr 16, 2015 in ISBI (International Symposium on Biomedical Imaging)
#1Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
#2Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
Direct estimation of physiologically or biochemically important parameters from raw projection data is challenging in dynamic positron emission tomography (PET) due to the coupling between tomographic image reconstruction and nonlinear kinetic parameter estimation. Optimization transfer algorithms have been previously developed to solve the complex optimization problem. These algorithms, however, can suffer from slow convergence rate. This paper proposes an accelerated iterative algorithm for di...
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#1Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
#2Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
Iterative image reconstruction for positron emission tomography can improve image quality by using spatial regularization. The most commonly used quadratic penalty often oversmoothes sharp edges and fine features in reconstructed images, while nonquadratic penalties can preserve edges and achieve higher contrast recovery. Existing optimization algorithms such as the expectation maximization (EM) and preconditioned conjugate gradient (PCG) algorithms work well for the quadratic penalty, but are l...
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#1Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
#2Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
Image reconstruction from low-count positron emission tomography (PET) projection data is challenging because the inverse problem is ill-posed. Prior information can be used to improve image quality. Inspired by the kernel methods in machine learning, this paper proposes a kernel based method that models PET image intensity in each pixel as a function of a set of features obtained from prior information. The kernel-based image model is incorporated into the forward model of PET projection data a...
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#1Will Hutchcroft (UC Davis: University of California, Davis)H-Index: 3
#2Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
Last. Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
view all 3 authors...
44 Objectives We study a new approach to incorporating anatomical prior information into PET reconstruction using the kernel method. This method was originally developed for dynamic PET and is readily applicable to anatomical-image aided PET image reconstruction. Methods The kernel method computes a kernel matrix from an anatomical prior image, and represents the unknown PET image as a linear combination of the kernels. The linear model is incorporated into the maximum likelihood (ML) expectatio...
#1Xuezhu Zhang (UC Davis: University of California, Davis)H-Index: 15
#2Jian Zhou (UC Davis: University of California, Davis)H-Index: 12
Last. Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
view all 7 authors...
269 Objectives Current PET scanners have an axial FOV of 15-30 cm, and a typical 18F-FDG PET whole-body scan requires an injected activity of 200-400 MBq. The EXPLORER project (EXtreme Performance Long REsearch scanneR) aims to build a 2-meter long total-body PET scanner, which provides massively increased sensitivity and possesses a range of capabilities currently unavailable for whole-body dynamic imaging especially at very low radiation doses with high temporal resolution. Here we study the f...
#1Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
#2Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
Dynamic positron emission tomography (PET) can monitor spatiotemporal distribution of radiotracer in vivo. The spatiotemporal information can be used to estimate parametric images of radiotracer kinetics that are of physiological and biochemical interests. Direct estimation of parametric images from raw projection data allows accurate noise modeling and has been shown to offer better image quality than conventional indirect methods, which reconstruct a sequence of PET images first and then perfo...
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#1Guobao Wang (UC Davis: University of California, Davis)H-Index: 19
#2Jinyi Qi (UC Davis: University of California, Davis)H-Index: 53
Direct reconstruction of kinetic parameters from raw projection data is a challenging task in molecular imaging using dynamic positron emission tomography (PET). This paper presents a new optimization transfer algorithm for penalized likelihood direct reconstruction of nonlinear parametric images that is easy to use and has a fast convergence rate. Each iteration of the proposed algorithm can be implemented in three simple steps: a frame-by-frame maximum likelihood expectation-maximization (EM)-...
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