20.8.4.2 Tomographic Image Reconstruction, Random Projections, Unknown Projections

Chapter Contents (Back)
Reconstruction. Tomography.

Lauren, P.D.[Peter D.], Nandhakumar, N.,
Estimating the Viewing Parameters of Random, Noisy Projections of Asymmetric Objects for Tomographic Reconstruction,
PAMI(19), No. 5, May 1997, pp. 417-430.
IEEE DOI 9705
BibRef
Earlier:
Recovering the Viewing Parameter of Random, Translated and Noisy Projections of Asymmetric Objects,
CVPR96(885-890).
IEEE DOI BibRef
Earlier:
Computing the View Orientations of Random Projections of Asymmetric Objects,
CVPR92(71-76).
IEEE DOI BibRef
And:
Determination of the Relative Orientation of Projections of Asymmetric Objects,
ICPR92(I:285-288).
IEEE DOI BibRef

Payot, E., Preteux, F.J., Trousset, Y., Guillemaud, R.,
Generalized Support Constraint for 3-Dimensional Reconstruction from Incomplete Fourier Spectra,
JEI(6), No. 4, October 1997, pp. 426-438. 9807
BibRef

Basu, S., Bresler, Y.,
Uniqueness of Tomography with Unknown View Angles,
IP(9), No. 6, June 2000, pp. 1094-1106.
IEEE DOI 0006
BibRef

Basu, S., Bresler, Y.,
Feasibility of Tomography with Unknown View Angles,
IP(9), No. 6, June 2000, pp. 1107-1122.
IEEE DOI 0006
BibRef
Earlier: ICIP98(II: 15-19).
IEEE DOI 9810
BibRef

Coifman, R.R., Shkolnisky, Y., Sigworth, F.J., Singer, A.,
Graph Laplacian Tomography From Unknown Random Projections,
IP(17), No. 10, October 2008, pp. 1891-1899.
IEEE DOI 0809
BibRef

Singer, A., Wu, H.T.,
Two-Dimensional Tomography from Noisy Projections Taken at Unknown Random Directions,
SIIMS(6), No. 1, 2013, pp. 136-175.
DOI Link 1304
BibRef

Borg, L., Frikel, J., Jørgensen, J., Quinto, E.T.,
Analyzing Reconstruction Artifacts from Arbitrary Incomplete X-ray CT Data,
SIIMS(11), No. 4, 2018, pp. 2786-2814.
DOI Link 1901
BibRef

Fu, J., Dong, J., Zhao, F.,
A Deep Learning Reconstruction Framework for Differential Phase-Contrast Computed Tomography With Incomplete Data,
IP(29), 2020, pp. 2190-2202.
IEEE DOI 2001
Image reconstruction, Computed tomography, Deep learning, Neural networks, Feature extraction, Absorption, reconstruction algorithms BibRef


Wang, L., Zhao, Z.,
Two-Dimensional Tomography from Noisy Projection Tilt Series Taken at Unknown View Angles with Non-Uniform Distributi,
ICIP19(1242-1246)
IEEE DOI 1910
Tomography, unknown view angle, moment features, non-convex optimization, ADMM BibRef

Malhotra, E., Rajwade, A.,
Tomographic reconstruction from projections with unknown view angles exploiting moment-based relationships,
ICIP16(1759-1763)
IEEE DOI 1610
Estimation BibRef

Phan, M.S.[Minh Son], Baudrier, E.[Etienne], Mazo, L.[Loic], Tajine, M.[Mohamed],
Estimation of angular difference between tomographic projections taken at unknown directions in 3D,
ICIP15(73-77)
IEEE DOI 1512
BibRef
Earlier:
Angular difference measure between tomographic projections taken at unknown directions in 2D,
ICIP14(1738-1742)
IEEE DOI 1502
Euclidean distance. Estimation BibRef

Chartrand, R.[Rick],
Nonconvex compressive sensing and reconstruction of gradient-sparse images: Random vs. tomographic Fourier sampling,
ICIP08(2624-2627).
IEEE DOI 0810
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Tomographic Image Reconstruction, Radon Transform .


Last update:Nov 1, 2021 at 09:26:50