Charles Byrne mainly investigates Iterative reconstruction, Iterative method, Algorithm, Artificial intelligence and Variational inequality. He interconnects Mathematical optimization and Expectation–maximization algorithm in the investigation of issues within Iterative reconstruction. Many of his studies on Iterative method involve topics that are commonly interrelated, such as Combinatorics.
The concepts of his Combinatorics study are interwoven with issues in Multiplicative function and Eigenvalues and eigenvectors. His research in Artificial intelligence tackles topics such as Computer vision which are related to areas like Medical imaging, Hyperspectral imaging and Approximation theory. His research integrates issues of Zero, Fixed point, Hilbert space and Sequence in his study of Variational inequality.
His scientific interests lie mostly in Algorithm, Iterative reconstruction, Iterative method, Optics and Combinatorics. Charles Byrne combines subjects such as Hilbert space, Expectation–maximization algorithm, Estimator, Noise and Nonlinear system with his study of Algorithm. His biological study spans a wide range of topics, including Image resolution, Attenuation and Image quality.
His studies in Iterative method integrate themes in fields like Multiplicative function, Single-photon emission computed tomography, Maximum likelihood sequence estimation, System of linear equations and Algebraic Reconstruction Technique. His research in Optics intersects with topics in Spectral density estimation, Fourier transform and Discrete Fourier transform. The study incorporates disciplines such as Discrete mathematics, Convex function, Function, Sequence and Order in addition to Combinatorics.
Charles Byrne mainly focuses on Combinatorics, Algorithm, Function, Discrete mathematics and Applied mathematics. Charles Byrne integrates Algorithm and Subject in his studies. The various areas that Charles Byrne examines in his Function study include Iterative method and Elementary proof.
His research investigates the connection between Iterative method and topics such as Orthographic projection that intersect with issues in Euclidean space. Zero and Variational inequality is closely connected to Hilbert space in his research, which is encompassed under the umbrella topic of Discrete mathematics. In his work, Entropy maximization is strongly intertwined with Mathematical optimization, which is a subfield of Applied mathematics.
Charles Byrne spends much of his time researching Function, Iterative method, Hilbert space, Orthographic projection and Variational inequality. His work deals with themes such as Auxiliary function, Multiplicative function, Algebraic Reconstruction Technique and Minification, which intersect with Iterative method. Charles Byrne works mostly in the field of Hilbert space, limiting it down to concerns involving Zero and, occasionally, Discrete mathematics, Space, Image and Bounded function.
Charles Byrne focuses mostly in the field of Orthographic projection, narrowing it down to topics relating to Cq algorithm and, in certain cases, Combinatorics. His Algorithm research incorporates themes from Strongly monotone, Linear map and Weak convergence. His study in Applied mathematics is interdisciplinary in nature, drawing from both Mathematical optimization and Expectation–maximization algorithm.
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A unified treatment of some iterative algorithms in signal processing and image reconstruction
Charles Byrne.
Inverse Problems (2004)
Iterative oblique projection onto convex sets and the split feasibility problem
Charles Byrne.
Inverse Problems (2002)
Iterative image reconstruction algorithms based on cross-entropy minimization
C.L. Byrne.
IEEE Transactions on Image Processing (1993)
Block-iterative methods for image reconstruction from projections
C.L. Byrne.
IEEE Transactions on Image Processing (1996)
Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative methods
C.L. Byrne.
IEEE Transactions on Image Processing (1998)
The Split Common Null Point Problem
C Byrne;Y Censor;A Gibali.
arXiv: Optimization and Control (2012)
Noniterative compensation for the distance-dependent detector response and photon attenuation in SPECT imaging
S.J. Glick;B.C. Penney;M.A. King;C.L. Byrne.
IEEE Transactions on Medical Imaging (1994)
General entropy criteria for inverse problems, with applications to data compression, pattern classification, and cluster analysis
L.K. Jones;C.L. Byrne.
IEEE Transactions on Information Theory (1990)
Applied Iterative Methods
Charles L. Byrne.
(2007)
Recent developments in iterative image reconstruction for PET and SPECT.
Richard M. Leahy;Charles L. Byrne.
IEEE Transactions on Medical Imaging (2000)
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