Dr. Alexander I. Katsevich
Professor at Univ of Central Florida
SPIE Involvement:
Author | Instructor
Publications (12)

Proceedings Article | 28 May 2019 Paper
Seongjin Yoon, Alexander Katsevich, Michael Frenkel, Peter Munro, Pascal Paysan, Dieter Seghers, Adam Strzelecki
Proceedings Volume 11072, 110720E (2019) https://doi.org/10.1117/12.2534879
KEYWORDS: Motion estimation, Abdomen, Optical flow, Reconstruction algorithms, Imaging systems, Detection and tracking algorithms, Computed tomography, Chest, Image quality

Proceedings Article | 28 May 2019 Paper
Alexander Katsevich, Seongjin Yoon, Michael Frenkel, Ed Morton, William Thompson
Proceedings Volume 11072, 110720G (2019) https://doi.org/10.1117/12.2534878
KEYWORDS: Reconstruction algorithms, Scanners, Sensors, Visibility, Computed tomography, Detection and tracking algorithms, X-ray computed tomography, Image quality, Integration

Proceedings Article | 28 May 2019 Paper
William Thompson, Edward Morton, Alexander Katsevich, Seongjin Yoon, Michael Frenkel
Proceedings Volume 11072, 110721W (2019) https://doi.org/10.1117/12.2534855
KEYWORDS: Reconstruction algorithms, CT reconstruction, Digital filtering, Scanners, Data acquisition, Image quality, Detection and tracking algorithms, Algorithms

Proceedings Article | 14 May 2019 Presentation
Proceedings Volume 10999, 109990V (2019) https://doi.org/10.1117/12.2518575
KEYWORDS: X-ray diffraction, Tomography, Imaging systems, X-ray computed tomography, Reconstruction algorithms, Diffraction, X-rays, Medical imaging, Image filtering, Real time imaging

Proceedings Article | 19 March 2014 Paper
Bibo Shi, Gene Katsevich, Be-Shan Chiang, Alexander Katsevich, Alexander Zamyatin
Proceedings Volume 9033, 90332E (2014) https://doi.org/10.1117/12.2043559
KEYWORDS: Image registration, Motion estimation, Image quality, Computed tomography, Arteries, Motion models, Reconstruction algorithms, X-ray computed tomography, Radon, Tolerancing

Showing 5 of 12 publications
Course Instructor
SC939: Exact Cone Beam Reconstruction: Theory and Practice
This course provides attendees with basic working knowledge of the fundamentals of exact image reconstruction in cone beam CT. The course starts with the general theory, then we discuss various approaches to obtaining inversion formulae, and then we consider specific trajectories, such as helical and circle plus a curve. We include a discussion of implementation techniques, analysis of detector requirements and data usage. We will also discuss image quality of exact Katsevich-type (shift-invariant filtered-backprojection structure) reconstruction. Course outline: • Foundations of three-dimensional image reconstruction theory in computed tomography - Radon transform, cone beam transform, Grangeat's formula • General reconstruction scheme - intersections of the source trajectory with Radon planes, weight function n, inversion of the cone beam transform • Approaches to obtaining reconstruction formulae, including the Zou-Pan approach - Reconstruction on chords; Gelfand-Graev formula; Pack-Noo approach - Reconstruction on M-lines; and other approaches • Trajectory-specific choice of the weight function for optimal reconstruction performance, both helical (1-PI, 3-PI, and Fractional-PI) and generalized circle-plus trajectories (open circle + line, and closed circle + curve) • Implementation details including filtering lines rebinning and detector requirements • Image quality
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