A combined reconstruction-classification method for diffuse optical tomography

Physics in Medicine and Biology

Volumn 54, Issue 21, 2009, Pages 6457-6476

  Hiltunen, P ^a   Prince, S J D ^b   Arridge, S ^b  

^a AALTO UNIVERSITY   (Finland)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN FRAMEWORKS; CLASSIFICATION METHODS; CURRENT ESTIMATES; DIFFUSE OPTICAL TOMOGRAPHY; EXPECTATION MAXIMIZATION; ILL-POSED INVERSE PROBLEM; MIXTURE MODEL; MIXTURE OF GAUSSIANS; MODEL PARAMETERS; OPTICAL PARAMETER; OPTIMIZATION SCHEME; PHANTOM MEASUREMENTS; PRIOR DISTRIBUTION; PROBABILISTIC CLASSIFICATION; RECONSTRUCTED IMAGE; RECONSTRUCTION ALGORITHMS; SPATIAL ACCURACY; TEST CASE; TIKHONOV REGULARIZATION;

ALGORITHMS; INVERSE PROBLEMS; OPTICAL TOMOGRAPHY; OPTICAL VARIABLES CONTROL; PARAMETER ESTIMATION; PIXELS; REPAIR;

IMAGE RECONSTRUCTION;

ARTICLE; BAYES THEOREM; CONTROLLED STUDY; IMAGE ENHANCEMENT; IMAGE QUALITY; IMAGE RECONSTRUCTION; MATHEMATICAL COMPUTING; OPTICAL TOMOGRAPHY; PRIORITY JOURNAL;

ALGORITHMS; BAYES THEOREM; COMPUTER SIMULATION; FUZZY LOGIC; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, STATISTICAL; NORMAL DISTRIBUTION; PHANTOMS, IMAGING; PROBABILITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SOFTWARE; TOMOGRAPHY, OPTICAL;

EID: 70449135254     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/54/21/002     Document Type: Article

References (46)

1. Arridge S R 1999 Optical tomography in medical imaging Inverse Problems 15 R41-93
2. Arridge S R, Dorn O, Kaipio J P, Kolehmainen V, Schweiger M, Tarvainen T, Vauhkonen M and Zacharopoulos A 2006 Reconstruction of subdomain boundaries of piecewise constant coefficients of the radiative transport equation from optical tomography data Inverse Problems 22 2175-98
3. Arridge S R, Dorn O, Kolehmainen V, Schweiger M and Zacharopoulos A 2008 Parameter and structure reconstruction in optical tomography Proc. of 6th Int. Conf. on Inverse Problems in Engineering: Theory and Practice J Phys.: Conf. Ser. 125 012001
4. Arridge S R, Kaipio J, Kolehmainen, V Schweiger M, Somersalo E, Tarvainen T and Vauhkonen M 2006 Approximation errors and model reduction with an application in optical diffusion tomography Inverse Problems 22 175-96
5. Arridge S R, Schweiger M, Hiraoka M and Delpy D T 1993 A finite element approach for modeling photon transport in tissue Med. Phys. 20 299-309
6. Bezdek L 1981 Pattern Recognition with Fuzzy Objective Function Algorithm (New York: Plenum)
7. Bishop C M 2006 Pattern Recognition and Machine Learning (Information Science and Statistics) (Berlin: Springer)
8. Cootes T F, Hill A, Taylor C J and Haslam J 1994 Use of active shape models for locating structures in medical images Image Vis. Comput. 25 355-66
9. Dempster A, Laird N and Rubin D 1977 Maximum likelihood from incomplete data via the EM algorithm J. R. Stat. Soc. B 39 1-38
10. Domke J, Karapurkar A and Aloimonos Y 2008 Who killed the directed model? IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR 2008) (24-26 June 2008, Anchorage, AL, USA)
11. Douiri A, Schweiger M, Riley J and Arridge S R 2007 Anisotropic diffusion regularisation methods for diffuse optical tomography using edge prior information Meas. Sci. Technol. 18 87-95
12. Duda R and Hart P 1973 Pattern Classification and Scene Analysis (New York: Wiley)
13. Feng X, Williams C and Felderhof S 2002 Combining belief networks and neural networks for scene segmentation IEEE Trans. Pattern Anal. Mach. Intell. 24 467-83
14. Freeman W T, Pasztor E C and Carmichael O T 2000 Learning low-level vision Int. J. Comput. Vision 40 25-47
15. Fukunaga K 1972 Introduction to Statistical Pattern Recognition (New York: Academic)
16. Gelman A, Carlin J B, Stern H S and Rubin D B 2004 Bayesian Data Analysis (Boca Raton, FL: Chapman and Hall/CRC)
17. Gibson A, Hebden J and Arridge S R 2005 Recent advances in diffuse optical tomography Phys. Med. Biol. 50 R1-43
18. Guven M, Yazici B, Intes X and Chance B 2005 Diffuse optical tomography with a priori anatomical information Phys. Med. Biol. 50 2837-58 (Pubitemid 40771015)
19. Hansen P C and O'Leary D P 1993 The use of the L-curve in the regularization of discrete ill-posed problems SIAM J. Sci. Comput. 14 1487-503
20. Hiltunen P, Calvetti D and Somersalo E 2008 An adaptive smoothness regularization algorithm for optical tomography Opt. Express 16 19957-77
21. Hsiao I-T, Rangarajan A and Gindi G 1998 Joint-MAP reconstruction/ segmentation for transmission tomography using mixture-models as priors Proc. IEEE Nuclear Science Symp. and Medical Imaging Conf. vol 3 pp 1689-93
22. Hsiao I-T, Rangarajan A and Gindi G 2002 Joint-MAP Bayesian tomographic reconstruction with a gamma-mixture prior IEEE Trans. Image Process. A 11 1466-77
23. Kaipio J and Somersalo E 2004 Statistical and Computational Inverse Problems (Berlin: Springer)
24. Kass M, Witkin A and Terzopoulos D 1987 Snakes: active contour models Int. J. Comput. Vis. 1 321-31
25. Kolehmainen V, Arridge S R, Lionheart W R B, Vauhkonen M and Kaipio J P 1999 Recovery of region boundaries of piecewise constant coefficients of an elliptic PDE from boundary data Inverse Problems 15 1375-91
26. Kolehmainen V, Arridge S R, Vauhkonen M and Kaipio J P 2000a Simultaneous reconstruction of internal tissue region boundaries and coefficients in optical diffusion tomography Phys. Med. Biol. 45 3267-83
27. Kolehmainen V, Vauhkonen M, Kaipio J P and Arridge S R 2000b Recovery of piecewise constant coefficients in optical diffusion tomography Opt. Express 7 468-80
28. Mackay D J C 2002 Information Theory, Inference & Learning Algorithms (Cambridge: Cambridge University Press)
29. Moga A and Gabbouj M 1997 Parallel image component labeling with watershed transformation IEEE Trans. Pattern. Anal. Mach. Intell. 19 441-50
30. Neal R M 2000 Markov chain sampling methods for Dirichlet process mixture models J. Comput. Graph. Stat. 9 249-65
31. Nissilä I et al 2006 Comparison between a time-domain and a frequency-domain system for optical tomography J. Biomed. Opt. 11 064015
32. Otsu N 1979 A threshold selection method from gray-level histograms IEEE Trans. Syst. Man Cybern. 9 62-6
33. Paulsen K D and Jiang H 1996 Enhanced frequency-domain optical image reconstruction in tissues through total variation minimization Appl. Opt. 35 3447-58
34. Rettman M, Han X and Prince J L 2002 Automated sulcal segmentation using watersheds on the cortical surface NeuroImage 15 329-44
35. Roth S and Black M J 2005 Fields of experts: a framework for learning image priors Proc. IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR '05) (20-26 June 2005) vol 2 pp 860-7
36. Sahoo P, Soltani S, Wong A K C and Chen Y C 1988 Survey of thresholding techniques Comput. Vis. Graph. Image Process. 41 233-60
37. Schweiger M and Arridge S R 1997 The finite element model for the propagation of light in scattering media: frequency domain case Med. Phys. 24 895-902
38. Schweiger M and Arridge S R 2008 Toast reconstruction package http://web4.cs.ucl.ac.uk/research/vis/toast/
39. Schweiger M, Arridge S R, Dorn O, Zacharopoulos A and Kolehmainen V 2006 Reconstructing absorption and diffusion shape profiles in optical tomography using a level set technique Opt. Lett. 31 471-3
40. Schweiger M, Arridge S R, Hiraoka M and Delpy D T 1995 The finite element model for the propagation of light in scattering media: boundary and source conditions Med. Phys. 22 1779-92
41. Schweiger M, Arridge S R and Nissilä I 2005 Gauss-Newton method for image reconstruction in diffuse optical tomography Phys. Med. Biol. 50 2365-86
42. Schweiger M, Dorn O and Arridge S R 2008 3-d shape and contrast reconstruction in optical tomography with level sets Proc. 4th AIP Int. Conf. and the 1st Congress of the IPIA J. Phys.: Conf. Ser. 124 012043
43. Staib L and Duncan J 1992 Boundary finding with parametrically deformable models IEEE Trans. Pattern Anal. Mach. Intell. 14 1061-75 (Pubitemid 23594855)
44. Vogel C R 2002 Computational Methods for Inverse Problems (Philadelphia, PA: SIAM)
45. Warrell J, Prince S J D and Moore A 2009 Epitomized priors for multi-labeling problems CVPR 2009
46. Zacharopoulos A, Arridge S R, Dorn O, Kolehmainen V and Sikora J 2006 Three dimensional reconstruction of shape and piecewise constant region values for optical tomography using spherical harmonic parameterisation and a boundary element method Inverse Problems 22 1509-32