Author : Jingwei Lu
Publisher :
ISBN 13 :
Total Pages : 152 pages
Book Rating : 4.:/5 (11 download)
Book Synopsis Multi-dimensional Extension of the Alternating Minimization Algorithm in X-ray Computed Tomography by : Jingwei Lu
Download or read book Multi-dimensional Extension of the Alternating Minimization Algorithm in X-ray Computed Tomography written by Jingwei Lu and published by . This book was released on 2019 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: X-ray computed tomography (CT) is an important and effective tool in medical and industrialimaging applications. The state-of-the-art methods to reconstruct CT images have hadgreat development but also face challenges. This dissertation derives novel algorithms toreduce bias and metal artifacts in a wide variety of imaging modalities and increase performancein low-dose scenarios.The most widely available CT systems still use the single-energy CT (SECT), which isgood at showing the anatomic structure of the patient body. However, in SECT imagereconstruction, energy-related information is lost. In applications like radiation treatmentplanning and dose prediction, accurate energy-related information is needed. Spectral CThas shown the potential to extract energy-related information.Dual-energy CT (DECT) is the first successful implementation of spectral CT. By using twodifferent spectra, the energy-related information can be exported by reconstructing basis-materialimages. A sinogram-based decomposition method has shown good performance inclinical applications. However, when the x-ray dose level is low, the sinogram-based decompositionmethods generate biased estimates. The bias increases rapidly when the dose leveldecreases. The bias comes from the ill-posed statistical model in the sinogram-decompositionmethod. To eliminate the bias in low-dose cases, a joint statistical image reconstruction(JSIR) method using the dual-energy alternating minimization (DEAM) algorithm is proposed.By correcting the ill-posed statistical model, a relative error as high as 15% in thesinogram-based decomposition method can be reduced to less than 1% with DEAM, whichis an approximately unbiased estimation.Photon counting CT (PCCT) is an emerging CT technique that also can resolve the energyinformation. By using photon-counting detectors (PCD), PCCT keeps track of the energyof every photon received. Though PCDs have an entirely different physical performancefrom the energy-integrating detectors used in DECT, the problem of biased estimation withthe sinogram-decomposition method remains. Based on DEAM, a multi-energy alternatingminimization (MEAM) algorithm for PCCT is proposed. In the simulation experiments,MEAM can effectively reduce bias by more than 90%.Metal artifacts have been a concern since x-ray CT came into medical imaging. When thereexist dense or metal materials in the scanned object, the image quality may suffer severeartifacts. The auxiliary sinogram alternating minimization (ASAM) algorithm is proposedto take advantages of two major categories of methods to deal with metal artifacts: thepre-processing method and statistical image reconstruction. With a phantom experiment, ithas been shown that ASAM has better metal-artifact reduction performance compared withthe current methods.A significant challenge in security imaging is that due to the large geometry and powerconsumption, low photon statistics are detected. The detected photons suffer high noise andheavy artifacts. Image-domain regularized iterative reconstruction algorithms can reducethe noise but also result in biased reconstruction. A wavelet-domain penalty is introducedwhich does not bring in bias and can effectively eliminate steaking artifacts. By combiningthe image-domain and wavelet-domain penalty, the image quality can be further improved.When the wavelet penalty is used, a concern is that no empirical way, like in the image-domainpenalty, is available to determine the penalty weight. Laplace variational automaticrelevance determination (Lap-VARD) method is proposed to reconstruct the image andoptimal penalty weight choice at the same time.