Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector - INSPIRE

DataBETA

Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector

Jul 2, 2013

10 pages

Published in:

Nucl.Instrum.Meth.A 728 (2013) 59-68

Published: 2013

e-Print:

1307.0714 [physics.ins-det]

DOI:

10.1016/j.nima.2013.06.040

View in:

ADS Abstract Service

reference search22 citations

Citations per year

Abstract: (arXiv)

Muon tomographic visualization techniques try to reconstruct a 3D image as close as possible to the real localization of the objects being probed. Statistical algorithms under test for the reconstruction of muon tomographic images in the Muon Portal Project are here discussed. Autocorrelation analysis and clustering algorithms have been employed within the context of methods based on the Point Of Closest Approach (POCA) reconstruction tool. An iterative method based on the log-likelihood approach was also implemented. Relative merits of all such methods are discussed, with reference to full Geant4 simulations of different scenarios, incorporating medium and high-Z objects inside a container.

Note:

12 pages, 8 figures

Muon tomography
Imaging algorithms
Clustering methods
Autocorrelation analysis
Maximum likelihood
EM algorithm

References(23)

Figures(31)

[1]

S. Riggi

- J.Phys. 409 (2013) 012046

[2]

The Muon Portal Collaboration Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC) N1-2

D. Lo Presti

[3]

〈〉

- http://muoni.oact.inaf.it:8080/

[4]

GEANT4 - A Simulation Toolkit

GEANT4

Collaboration

•

S. Agostinelli
(
- Genoa U.
)

et al.

- Nucl.Instrum.Meth.A 506 (2003) 250-303
•
DOI:
- 10.1016/S0168-9002(03)01368-8

[4]

K. Amako

- IEEE Trans.Nucl.Sci. NS-53 (2006) 270

[5]

Proceedings of the AIHENP’96 Workshop, Lausanne

R. Brun
,
F. Rademakers

[6]

The Large-Scale Structure of the Universe

P.J.E. Peebles

[7]

P.J.E. Peebles
,
M.J. Hauser

- Astrophys.J. 28 (1974) 19

[8]

A Survey of galaxy redshifts. 5. The Two point position and velocity correlations

- Astrophys.J. 267 (1982) 465-482
•
DOI:
- 10.1086/160884

[9]

Toward Better Ways to Measure the Galaxy Correlation Function

A.J.S. Hamilton

- Astrophys.J. 417 (1993) 19
•
DOI:
- 10.1086/173288

[10]

S.D. Landy
,
A.S. Szalay

- Astrophys.J. 412 (1993) L64

[11]

in: Proceedings of Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Portland

M. Ester

[12]

D.W. Pfitzner
,
J.K. Salmon
,
T. Sterling

- Data Min.Knowl.Discov. 1 (1997) 419

[13]

The overdensity and masses of the friends-of-friends halos and universality of the halo mass function

- Astrophys.J.Suppl. 195 (2011) 4
•
e-Print:
- 1103.0005
•
DOI:
- 10.1088/0067-0049/195/1/4

[14]

L. Schultz

- IEEE Trans.Image Process. 16 (2007) 1985

[15]

CORSIKA: A Monte Carlo code to simulate extensive air showers

D. Heck
(
- Karlsruhe, Forschungszentrum
)
,
J. Knapp
(
- Karlsruhe U., EKP
)
,
J.N. Capdevielle
(
- College de France
)
,
G. Schatz
(
- Karlsruhe, Forschungszentrum
)
,
T. Thouw
(
- Karlsruhe, Forschungszentrum
)

[16]

Application of Kalman filtering to track and vertex fitting

R. Fruhwirth
(
- Vienna, OAW
)

- Nucl.Instrum.Meth.A 262 (1987) 444-450
•
DOI:
- 10.1016/0168-9002(87)90887-4

[16]

Pattern recognition and event reconstruction in particle physics experiments

Rainer Mankel
(
- DESY
)

- Rept.Prog.Phys. 67 (2004) 553
•
e-Print:
- physics/0402039
•
DOI:
- 10.1088/0034-4885/67/4/R03

[17]

Z. Wang

- IEEE Trans.Image Process. 13 (2004) 600

[18]

〈〉

- http://www.mpich.org/

[19]

J.L. Bentley

- Communications of the ACM 18 (1975) 509

[20]

in: Proceedings of the Ninth LCI International Conference on High-Performance Clustered Computing, Urbana Illinois

J. Dolence
,
R.J. Brunner

[21]

Application of GPUs for the Calculation of Two Point Correlation Functions in Cosmology

- ASP Conf.Ser. 461 (2012) 73
•
e-Print:
- 1204.6630