Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Ken David Sauer"'
Autor:
Charles A. Bouman, Amirkoushyar Ziabari, Ken David Sauer, Dong Hye Ye, Jean-Baptiste Thibault, Somesh Srivastava
Publikováno v:
ACSSC
While Model Based Iterative Reconstruction (MBIR) of CT scans has been shown to have better image quality than Filtered Back Projection (FBP), its use has been limited by its high computational cost. More recently, deep convolutional neural networks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b74e08579e5e869d2ed5ffb21d4445d
https://doi.org/10.1109/acssc.2018.8645364
https://doi.org/10.1109/acssc.2018.8645364
Publikováno v:
ICASSP
Model-Based Iterative Reconstruction (MBIR) has shown promising results in clinical studies as they allow significant dose reduction during CT scans while maintaining the diagnostic image quality. MBIR improves the image quality over analytical recon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::847d7f2e8ac36e25fcbf042dcf900584
https://doi.org/10.1109/icassp.2018.8461408
https://doi.org/10.1109/icassp.2018.8461408
Autor:
Jean-Baptiste Thibault, Ruoqiao Zhang, Debashish Pal, Charles A. Bouman, Dong Hye Ye, Ken David Sauer
Markov random fields (MRFs) have been widely used as prior models in various inverse problems such as tomographic reconstruction. While MRFs provide a simple and often effective way to model the spatial dependencies in images, they suffer from the fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f36c942da0f199a482d931976792f3a8
http://arxiv.org/abs/1605.04006
http://arxiv.org/abs/1605.04006
Publikováno v:
Physics in Medicine and Biology. 51:77-93
Fully 3D PET data are often rebinned into 2D data sets in order to avoid computationally intensive fully 3D reconstruction. Then, conventional 2D reconstruction techniques are employed to obtain images from the rebinned data. In a common scenario, 2D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5b44fa44545913ace894eaa4a07eea6
https://doi.org/10.1088/0031-9155/51/1/006
https://doi.org/10.1088/0031-9155/51/1/006
Publikováno v:
IEEE Transactions on Medical Imaging. 24:636-650
Our goal in this paper is the estimation of kinetic model parameters for each voxel corresponding to a dense three-dimensional (3-D) positron emission tomography (PET) image. Typically, the activity images are first reconstructed from PET sinogram fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ecaa70704ad4f3c0510ec7403e9fcd87
https://doi.org/10.1109/tmi.2005.845317
https://doi.org/10.1109/tmi.2005.845317
Publikováno v:
Scopus-Elsevier
High sensitivity 3-D PET data is often rebinned into 2-D data sets in order to reduce the computation time of reconstructions. The need to precorrect the 3-D data for attenuation, accidentals, scatter, and deadtime effects before rebinning along with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::636ba724bd0d5f8e49524c3108a77d66
https://doi.org/10.1109/tns.2003.817943
https://doi.org/10.1109/tns.2003.817943
Autor:
Charles A. Bouman, Ken David Sauer
Publikováno v:
IEEE Transactions on Signal Processing. 41:534-548
A method for Bayesian reconstruction which relies on updates of single pixel values, rather than the entire image, at each iteration is presented. The technique is similar to Gauss-Seidel (GS) iteration for the solution of differential equations on f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d63563413b17bf5a21eaff6611e76ca3
https://doi.org/10.1109/78.193196
https://doi.org/10.1109/78.193196
Publikováno v:
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. 9(10)
Bayesian tomographic reconstruction algorithms generally require the efficient optimization of a functional of many variables. In this setting, as well as in many other optimization tasks, functional substitution (FS) has been widely applied to simpl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60387d5d2b9d09fe8145c60d29dbaa6c
https://pubmed.ncbi.nlm.nih.gov/18262913
https://pubmed.ncbi.nlm.nih.gov/18262913
Most statistical reconstruction methods for emission tomography are designed for data modeled as conditionally independent Poisson variates. In reality, due to scanner detectors, electronics and data processing, correlations are introduced into the d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f7b01df38f7a44f0f3611ea7066ea30
https://europepmc.org/articles/PMC2597017/
https://europepmc.org/articles/PMC2597017/
Publikováno v:
Computational Imaging
Statistical reconstruction methods show great promise for improving resolution, and reducing noise and artifacts in helical X-ray CT. In fact, statistical reconstruction seems to be particularly valuable in maintaining reconstructed image quality whe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5fe888b991712c8c3555563a52631a1
https://doi.org/10.1117/12.716796
https://doi.org/10.1117/12.716796