We derive formulations of the four exact helical Katsevich algorithms in the native cylindrical detector geometry, which allow efficient implementation in modern computed tomography scanners with wide cone beam aperture. Also, we discuss some aspects of numerical implementation.
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http://dx.doi.org/10.1109/tmi.2006.876159 | DOI Listing |
Biometrics
December 2023
School of Mathematics and Statistics, University of Sydney, New South Wales, Australia.
Recently, Barber and Candès laid the theoretical foundation for a general framework for false discovery rate (FDR) control based on the notion of "knockoffs." A closely related FDR control methodology has long been employed in the analysis of mass spectrometry data, referred to there as "target-decoy competition" (TDC). However, any approach that aims to control the FDR, which is defined as the expected value of the false discovery proportion (FDP), suffers from a problem.
View Article and Find Full Text PDFZ Med Phys
August 2024
Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland; Geneva Neuroscience Center, Geneva University, Geneva, Switzerland; Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark.
Purpose: The most common detector material in the PC CT system, cannot achieve the best performance at a relatively higher photon flux rate. In the reconstruction view, the most commonly used filtered back projection, is not able to provide sufficient reconstructed image quality in spectral computed tomography (CT). Developing a triple-source saddle-curve cone-beam photon counting CT image reconstruction method can improve the temporal resolution.
View Article and Find Full Text PDFBiometrika
June 2022
Department of Statistics & Data Science, Carnegie Mellon University, 132H Baker Hall, Pittsburgh, Pennsylvania 15213, U.S.A.
We consider the problem of conditional independence testing: given a response and covariates , we test the null hypothesis that . The conditional randomization test was recently proposed as a way to use distributional information about to exactly and nonasymptotically control Type-I error using any test statistic in any dimensionality without assuming anything about . This flexibility, in principle, allows one to derive powerful test statistics from complex prediction algorithms while maintaining statistical validity.
View Article and Find Full Text PDFJ Xray Sci Technol
March 2022
Shenzhen Key Laboratory of Advanced Machine Learning and Applications, Shenzhen University, Shenzhen, Guangdong, China.
In this paper, we present an arc based fan-beam computed tomography (CT) reconstruction algorithm by applying Katsevich's helical CT image reconstruction formula to 2D fan-beam CT scanning data. Specifically, we propose a new weighting function to deal with the redundant data. Our weighting function ϖ(x_,λ) is an average of two characteristic functions, where each characteristic function indicates whether the projection data of the scanning angle contributes to the intensity of the pixel x_.
View Article and Find Full Text PDFNat Commun
February 2020
Departments of Biomedical Data Science and of Statistics, Stanford University, Stanford, CA, 94305, USA.
In the statistical analysis of genome-wide association data, it is challenging to precisely localize the variants that affect complex traits, due to linkage disequilibrium, and to maximize power while limiting spurious findings. Here we report on KnockoffZoom: a flexible method that localizes causal variants at multiple resolutions by testing the conditional associations of genetic segments of decreasing width, while provably controlling the false discovery rate. Our method utilizes artificial genotypes as negative controls and is equally valid for quantitative and binary phenotypes, without requiring any assumptions about their genetic architectures.
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