Title

Semantic Sparse Representation of Disease Patterns

Journal title

International Journal of Electronics and Telecommunications

Yearbook

2010

Volume

vol. 56

Issue

No 3

Authors

Przelaskowski, Artur

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences Committee of Electronics and Telecommunications

Date

2010

Identifier

DOI: 10.2478/v10177-010-0036-x ; eISSN 2300-1933 (since 2013) ; ISSN 2081-8491 (until 2012)

Source

International Journal of Electronics and Telecommunications; 2010; vol. 56; No 3

References

Ancona N. (2004), Data representation in kernel based learning machines, null, 129. ; Blum A. (1997), Selection of relevant features and examples in machine learning, Artificial Intelligence, 97, 245. ; Bobin J. (2007), Morphological component analysis: an adaptive thresholding strategy, Image Processing, IEEE Transactions on, 16, 11, 2675. ; Candés E. (2006), Compressive sampling, null, 1433. ; E. J. Candés, L. Demanet, D. L. Donoho, and L. Ying, "Fast discrete curvelet transforms," Technical Report, Cal Tech, Tech. Rep., 2005. ; DeVore R. (1998), Nonlinear approximation, Acta Numerica, 7, 51. ; Do M. (2003), Beyond Wavelets. ; G. V. W. (editor), <i>Beyond Wavelets</i>, ser. Studies in Computational Mathematics. Academic Press, 2003, vol. 10. ; Fhr H. (2006), Document and Image Compression. ; Floridi L. (2007), In defense of the veridical nature of semantic information, European Journal of Analytic Philosophy, 3, 31. ; Fornasier M. (2008), Iterative thresholding algorithms, Applied and Computational Harmonic Analysis, 25, 2, 187. ; M. L. Giger, "Computer-aided diagnosis in medical imaging - a new era in image interpretation," World Markets Research Centre, Tech. Rep., Tech. Rep., 2000. ; Gilbert A. (2006), Algorithms for simultaneous sparse approximation. part i: Greedy pursuit, Signal Processing, Special issue on sparse approximations in signal and image processing, 86, 572. ; Guido R. (2007), Wavelet-based algorithms for medical problems, Computers in Biology and Medicine, Special issue, 37, 4. ; Kinoshita S. (2007), Content-based retrieval of mammograms using visual features related to breast density patterns, Journal of Digital Imaging, 20, 2, 172. ; Mallat S. (1999), A wavelet tour of signal processing. ; Mallat S. (1993), Matching pursuits with time-frequency dictionaries, Signal Processing, IEEE Transactions on, 41, 12, 3397. ; Peyre G. (2009), Sparse modeling of textures, Journal of Mathematical Imaging and Vision, 34, 1, 17. ; Podsiadly-Marczykowska T. (2005), Mammography ontology, model structure, definitions and conception instances, Bio-Algorithms and Medical Systems, 1, 1, 247. ; Przelaskowski A. (2007), Ischemic stroke modeling: multiscale extraction of hypodense sign, Lecture Notes in Artificial Intelligence, 4482, 171. ; Przelaskowski A. (2009), Progress in Neuroradiology 2009, 69. ; Starck J.-L. (2005), Image decomposition via the combination of sparse representations and a variational approach, Image Processing, IEEE Transactions on, 14, 10, 1570. ; Starck J.-L. (2010), Sparse image and signal processing. ; R. von Kummer (2005), Thrombolytic therapy for stroke, 249, doi.org/10.1385/1-59259-933-8:249