Results 41 to 50 of about 260,393 (187)

Image reconstruction in fluorescence molecular tomography with sparsity-initialized maximum-likelihood expectation maximization [PDF]

, 2018
We present a reconstruction method involving maximum-likelihood expectation maximization (MLEM) to model Poisson noise as applied to fluorescence molecular tomography (FMT). MLEM is initialized with the output from a sparse reconstruction-based approach,
Jha, Abhinav K, Rahmim, Arman, Wong, Dean F, Zhu, Yansong   +3 more
core   +3 more sources

PET reconstruction artifact can be minimized by using sinogram correction and filtered back-projection technique

Indian Journal of Radiology and Imaging, 2014
Filtered Back-Projection (FBP) has become an outdated image reconstruction technique in new-generation positron emission tomography (PET)/computed tomography (CT) scanners.
Ashish Kumar Jha, Nilendu C Purandare, Sneha Shah, Archi Agrawal, Ameya D Puranik, Venkatesh Rangarajan   +5 more
doaj   +1 more source

Is Iterative Reconstruction Ready for MDCT? [PDF]

Journal of the American College of Radiology, 2009
Although the very first computed tomographic scanners used the iterative algebraic reconstruction technique, the filtered back-projection (FBP) method soon became the gold standard for computed tomographic reconstruction. Image quality has dramatically improved over the past 30 years thanks to advances in x-ray tubes, detector technologies, and overall
Jingyan, Xu, Mahadevappa, Mahesh, Benjamin M W, Tsui   +2 more
openaire   +2 more sources

Comparing Deep Learning Frameworks for Photoacoustic Tomography Image Reconstruction

Photoacoustics, 2021
Conventional reconstruction methods for photoacoustic images are not suitable for the scenario of sparse sensing and geometrical limitation. To overcome these challenges and enhance the quality of reconstruction, several learning-based methods have ...
Ko-Tsung Hsu, Steven Guan, Parag V. Chitnis   +2 more
doaj   +1 more source

Family Constraining of Iterative Algorithms

, 2013
In constraining iterative processes, the algorithmic operator of the iterative process is pre-multiplied by a constraining operator at each iterative step.
Censor, Yair, Pantelimon, Ioana, Popa, Constantin   +2 more
core   +1 more source

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

, 2012
Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging ...
Alexander A Oraevsky, Barrett H H, Elbau P, Kun Wang, Kunyansky L A, Mark A Anastasio, Pan X, Richard Su, Wang L V, Wernick M N   +9 more
core   +1 more source

Maximum-likelihood absorption tomography

, 2002
Maximum-likelihood methods are applied to the problem of absorption tomography. The reconstruction is done with the help of an iterative algorithm. We show how the statistics of the illuminating beam can be incorporated into the reconstruction.
, Cser L., Dempster A. P., J Řeháček, Kak A. C., Kendall M. G., M Strobl, M Zawisky, Mair B. A., Schillinger B., Shepp L. A., Vardi Y., W Treimer, Z Hradil   +13 more
core   +1 more source

Iterative initial condition reconstruction

Physical Review D, 2017
Motivated by recent developments in perturbative calculations of the nonlinear evolution of large-scale structure, we present an iterative algorithm to reconstruct the initial conditions in a given volume starting from the dark matter distribution in real space.
Schmittfull, Marcel, Baldauf, Tobias, Zaldarriaga, Matias   +2 more
openaire   +3 more sources

Bandlimited Frequency-Constrained Iterative Methods

Remote Sensing
Variable aperture sampling reconstruction matrices have a history of being computationally intensive due to the need to compute a full matrix inverse. In the field of remote sensing, several spaceborne radiometers and scatterometers, which have irregular
Harrison Garrett, David G. Long
doaj   +1 more source

Iterative projective reconstruction from multiple views [PDF]

Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662), 2002
We propose an iterative method for the recovery of the projective structure and motion from multiple images. It has been recently noted that by scaling the measurement matrix by the true projective depths, recovery of the structure and motion is possible by factorization.
Shyjan Mahamud, Hebert, Martial
openaire   +1 more source