Unsupervised decomposition of low-intensity low-dimensional multi-spectral fluorescent images for tumour demarcation

Medical Image Analysis

Volumn 13, Issue 3, 2009, Pages 507-518

  Kopriva, I ^a   Persin A ^a  

^a RUDER BO KOVI INSTITUTE   (Croatia)

Author keywords

Ill conditioned static linear mixture models; Multi channel medical imaging; Multi spectral imaging; Tumour demarcation; Unsupervised decomposition

Indexed keywords

ILL-CONDITIONED STATIC LINEAR MIXTURE MODELS; MULTI-CHANNEL MEDICAL IMAGING; MULTI-SPECTRAL IMAGING; TUMOUR DEMARCATION; UNSUPERVISED DECOMPOSITION;

FLUORESCENCE; INDEPENDENT COMPONENT ANALYSIS; MEDICAL IMAGING; MIXTURES; OPTOELECTRONIC DEVICES; RADAR TARGET RECOGNITION;

TUMORS;

ALGORITHM; ARTICLE; BASAL CELL CARCINOMA; FLUORESCENCE IMAGING; HUMAN; IMAGE PROCESSING; IMAGING SYSTEM; INDEPENDENT COMPONENT ANALYSIS; PRIORITY JOURNAL; SPECTROSCOPY; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY, FLUORESCENCE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SKIN NEOPLASMS; SPECTROMETRY, FLUORESCENCE;

EID: 65349111354     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2009.02.002     Document Type: Article

References (47)

1. Adams J.B., Smith M.O., and Gillespie A.R. Image spectroscopy: interpretation based on spectral mixture analysis. In: Pieters C.M., and Englert P.A. (Eds). Remote Geochemical Analysis: Elemental and Mineralogical Composition (1993), Cambridge University Press, Cambridge, Massachusetts
2. Bäumler W., Abels C., and Szeimies R.M. Fluorescence diagnosis and photodynamic therapy in dermatology. Med. Laser Appl. 18 (2003) 47-56
3. Bell A., and Sejnowski T.J. An information maximization approach to blind separation and blind deconvolution. Neural Comput. 7 (1995) 1129-1159
4. Belouchrani A., Abed-Meraim K., Cardoso J.F., and Moulines E. A blind source separation technique based on second order statistics. IEEE Trans. Signal Process. 45 (1997) 434-444
5. Cardoso J.F., and Soulomniac A. Blind beamforming for non-Gaussian signals. Proc. IEE F 140 (1993) 362-370
6. Chang C.I., and Du Q. Estimation of number of spectrally distinct signal sources in hyperspectral imagery. IEEE Trans. Geosci. Remote Sens. 42 (2004) 608-619
7. Choi S., Cichocki A., and Amari S. Flexible independent component analysis. J. VLSI Signal Process. 26 1-2 (2000) 25-38
8. Cichocki A. General component analysis and blind source separation methods for analyzing multichannel brain signals. In: J Wenger M., and Schuster C. (Eds). Statistical and Process Models of Cognitive Aging, Notre Dame Series on Quantitative Methods (2007), Erlbaum, Mahwah, NJ
9. Cichocki A., and Amari S. Adaptive Blind Signal and Image Processing (2002), John Wiley, New York
10. Cichocki A., and Georgiev P. Blind source separation algorithms with matrix constraints. IEICE Trans. Fund. Electron. Commun. Comput. Sci. E86-A (2003) 513-522
11. Cichocki A., Zdunek R., and Amari S. Nonnegative matrix and tensor factorization. IEEE Signal Proc. Mag. 25 (2008) 142-145
12. Du Q., and Kopriva I. Automated target detection and discrimination using constrained kurtosis maximization. IEEE Geosci. Remote Sens. Lett. 5 (2008) 38-42
13. Du Q., Kopriva I., and Szu H. Independent component analysis for classifying multispectral images with dimensionality limitation. Int. J. Inf. Acq. 1 (2004) 201-216
14. Du Q., Kopriva I., and Szu H. Independent component analysis for hyperspectral remote sensing. Opt. Eng. 45 017008 (2006) 1-13
15. Ericson M.B., Sandberg C., Gudmundson F., Rosén A., Larkö O., and Wennberg A.M. Fluorescence contrast and threshold limit: implications for photodynamic diagnosis of basal cell carcinoma. J. Photochem. Photobio. B: Biol. 69 (2003) 121-127
16. Fischer F., Dickson E.F., Pottier R.H., and Wieland H. An affordable, portable fluorescence imaging device for skin lesion detection using a dual wavelength approach for image contrast enhancement and aminolaevulinic acid-induced protoporphyrin IX, part I: design, spectral and spatial characteristics. Lasers Med. Sci. 16 (2001) 199-206
17. Fukunaga K., and Olsen D.R. An algorithm for finding intrinsic dimensionality of data. IEEE Trans. Comput. C 20 (1971) 176-183
18. Hasegawa S., Yang M., Chishima T., Miyagi Y., Shimada H., Moossa A.R., and Hoffman R.M. In vivo tumor delivery of the green fluorescent protein gene to report future occurence of metastasis. Cancer Gene Therapy 10 (2000) 1336-1340
19. Hoffman R.M. Green fluorescent protein imaging of tumor growth, metastasis, and angiogenesis in mouse models. The Lancet Oncology 3 (2002) 546-556
20. Hyvärinen, A., 1998. Independent component analysis for time-dependent stochastic processes. In: Proceedings of the International Conference on Artificial Neural Networks (ICANN'98), Skovde, Sweden, pp. 541-546.
21. Hyvärinen A., Karhunen J., and Oja E. Independent Component Analysis (2001), Wiley Interscience, New York
22. Jutten C., and Herault J. Blind separation of sources, part I: an adaptive algorithm based on neuromimetic architecture. Signal Process. 24 (1991) 1-10
23. Koenig F., Knittel J., and Stepp H. Diagnostic cancer in vivo. Science 292 (2001) 1401-1403
24. Kopriva I. Approach to blind image deconvolution by multiscale subband decomposition and independent component analysis. J. Opt. Soc. Am. A 24 (2007) 973-983
25. Kopriva I., and Seršić D. Wavelet packets approach to blind separation of statistically dependent sources. Neurocomputing 71 (2008) 1642-1655
26. Lee D.D., and Seung S.H. Learning the parts of objects by non-negative matrix factorization. Nature 401 (1999) 788-791
27. Malinowski E.R. Theory of error in factor analysis. Anal. Chem. 49 (1977) 606-612
28. Malinowski E.R. Determination of the number of factors and experimental error in a data matrix. Anal. Chem. 49 (1977) 612-617
29. McCullagh P. Elementary theory of cumulants in tensor methods in statistics (1995), Chapman and Hall, London pp. 24-46
30. Mendel J.M. Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications. Proc. IEEE 79 (1991) 278-305
31. Molgedey L., and Schuster H.G. Separation of mixture of independent signals using time delayed correlations. Phys. Rev. Lett. 72 (1994) 3634-3636
32. Orfanidis S.J. Optimum Signal Processing - An Introduction. second ed (1988), MacMillan Publishing Comp., New York
33. Pham D.T. Blind separation of mixtures of independent sources through a quasimaximum likelihood approach. IEEE Trans. Signal Process. 45 (1997) 1712-1725
34. Pham, D.T., 2003. Fast algorithm for estimating mutual information, entropies and score functions. In: Proceedings of the Fourth International Conference on Independent Component Analysis and Blind Signal Separation (ICA'2003), Nara, Japan, pp.17-22.
35. Principe, J.C., Xu, D., 1999. Information theoretic learning using Reny's quadratic entropy. In: Proceedings of the First International Conference on Independent Component Analysis and Blind Signal Separation (ICA'99), Aussois, France, pp. 407-412.
36. Principe J.C., Xu D., and Fisher J.W. Information-Theoretic Learning in Unsupervised Adaptive Filtering-Volume I Blind Source Separation (2000), J. Wiley (pp. 265-319)
37. Ren H., and Chang Ch.-I. A generalized orthogonal subspace projection approach to unsupervised multispectral image classification. IEEE Trans. Geosci. Remote Sens. 38 (2000) 2515-2528
38. Schwartz S., Zibulevsky M., and Schechner Y.Y. ICA using kernel entropy estimation with NlogN complexity. Lect. Notes Comput. Sci. 3195 (2004) 422-429
39. Scott M.A., Hopper C., Sahota A., Springett R., Mcllroy B.W., Bown S.G., and MacRobert A.J. Fluorescence photo diagnostics and photo bleaching studies of cancerous lesions using ratio imaging and spectroscopic techniques. Lasers Med. Sci. 15 (2000) 63-72
40. Settle J.J., and Drake N.A. Linear mixing and estimation of ground cover proportions. Int. J. Remote Sens. 14 (1993) 1159-1177
41. Silverman B.W. Kernel density estimation using the fast Fourier transform. Appl. Stat. 31 (1982) 93-99
42. Stone J.V. Blind source separation using temporal predictability. Neural Comput. 13 (2001) 1559-1574
43. Tréhin R., Figueiredo J.L., Pittet M.J., Weisslender R., Josephson L., and Mahmood U. Fluorescent nanoparticle uptake for brain tumour visualization. Neoplasia 4 (2006) 302-311
44. Wang J., and Chang C.I. Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis. IEEE Trans. Geosci. Remote Sens. 44 (2006) 1586-1600
45. Xue, Y., Wang, Y., Yang, J., 2008. Independent component analysis based on gradient equation and kernel density estimation. Neurocomputing. doi: 10.1016/j.neucom.2008.08.014.
46. Zdunek R., and Cichocki A. Nonnegative matrix factorization with constrained second-order optimization. Signal Process. 87 (2007) 1904-1916
47. Ziehe, A., Muller, K.R., Nolte, G., Mackert, B.M., Curio, G., 1998. TDSEP-an efficient algorithm for blind separation using time structure. In: Proceedings of the International Conference on Artificial Neural Networks (ICANN'98), Skovde, Sweden, pp. 675-680.