Free Access
Issue |
Math. Model. Nat. Phenom.
Volume 9, Number 5, 2014
Spectral problems
|
|
---|---|---|
Page(s) | 177 - 193 | |
DOI | https://doi.org/10.1051/mmnp/20149512 | |
Published online | 17 July 2014 |
- Y. Al-Kofahi, W. Lassoued, W. Lee, B. Roysam. Improved automatic detection and segmentation of cell nuclei in histopathology images. IEEE Trans. Biomed. Eng., 57 (2010), no. 4, 841-852. [CrossRef] [PubMed] [Google Scholar]
- E. J. Candès, D. L. Donoho. New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities. Comm. Pure and Appl. Math., 56 (2004), 216-266. [Google Scholar]
- C. W. Chang, M. A. Mycek. Total variation versus wavelet-based methods for image denoising in fluorescence lifetime imaging microscopy. J Biophotonics, 5 (2012), 449-457. [CrossRef] [PubMed] [Google Scholar]
- B. Delatour, V. Blanchard, L. Pradier, C. Duyckaerts. Alzheimer pathology disorganizes cortico-cortical circuitry: direct evidence from a transgenic animal model. Neurobiol Dis., 16 (2004), no. 1, 41-47. [CrossRef] [PubMed] [Google Scholar]
- A. Dima, M. Scholz, K. Obermayer. Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform. IEEE Trans. Image Process., 11 (2002), no. 7, 790-801. [CrossRef] [PubMed] [Google Scholar]
- G. Easley, D. Labate, W. Lim. Sparse directional image representations using the discrete shearlet transform. Appl. Comput. Harmon. Anal., 25 (2008), 25-46. [Google Scholar]
- G. Easley, D. Labate, P. S. Negi. 3D data denoising using combined sparse dictionaries. Math. Model. Nat. Phen., 8 (2013), no. 1, 60-74. [CrossRef] [EDP Sciences] [Google Scholar]
- N.I. Fisher. Statistical analysis of circular data. Cambridge University Press, 1993. [Google Scholar]
- C. Grigorescu, N. Petkov. Distance sets for shape filters and shape recognition. IEEE Trans. on Image Processing, 12 (2003), no. 10, 1274-1286. [CrossRef] [Google Scholar]
- K. Guo, D. Labate. Optimally sparse multidimensional representation using shearlets. SIAM J. Math. Anal., 39 (2007), 298-318. [CrossRef] [MathSciNet] [Google Scholar]
- K. Guo, D. Labate. Characterization and analysis of edges using the continuous shearlet transform. SIAM Journal on Imaging Sciences, 2 (2009), 959-986. [CrossRef] [Google Scholar]
- K. Guo, D. Labate. Analysis and detection of surface discontinuities using the 3D continuous shearlet transform. Appl. Comput. Harmon. Anal., 30 (2010), 231-242. [CrossRef] [Google Scholar]
- K. Guo, D. Labate. The construction of smooth Parseval frames of shearlets. Math. Model. Nat. Phen., 8 (2013), no. 1, 82-105. [CrossRef] [EDP Sciences] [Google Scholar]
- K. Guo, D. Labate, W. Lim. Edge Analysis and identification using the continuous shearlet transform. Appl. Comput. Harmon. Anal., 27 (2009), 24-46. [CrossRef] [Google Scholar]
- M. Holschneider. Wavelets. Analysis tool. Oxford University Press, Oxford, 1995. [Google Scholar]
- B. Jacobs, H. Praag, F. Gage. Adult brain neurogenesis and psychiatry: a novel theory of depression. Mol. Psychiatry, 5 (2000), no. 3, 262-269. [CrossRef] [PubMed] [Google Scholar]
- T. F. James, J. Luisi, M. N. Nenov, N. Panova-Electronova, D. Labate, F. Laezza. The Nav1.2 channel is regulated by glycogen synthase kinase 3 (GSK3). To appear in Neuropharmacology (2014). [Google Scholar]
- S. Kullback. Information theory and statistics. John Wiley and Sons, NY, 1959. [Google Scholar]
- G. Kutyniok, D. Labate. Resolution of the wavefront set using continuous shearlets. Trans. Amer. Math. Soc., 361 (2009), 2719-2754. [CrossRef] [MathSciNet] [Google Scholar]
- G. Kutyniok, D. Labate. Shearlets: multiscale analysis for multivariate data. Birkhäuser, Boston (2012). [Google Scholar]
- D. Labate, W. Lim, G. Kutyniok, G. Weiss. Sparse multidimensional representation using shearlets. Wavelets XI (San Diego, CA, 2005), 254-262, SPIE Proc. 5914, SPIE, Bellingham, WA, (2005). [Google Scholar]
- M.R. Lamprecht, D.M. Sabatini, A.E. Carpenter. CellProfiler: free, versatile software for automated biological image analysis. Biotechniques, 42 (2007), no. 1, 71-75. [CrossRef] [PubMed] [Google Scholar]
- C. G. Langhammer, P. M. Previtera, E. S. Sweet, S. S. Sran, M. Chen, B. L. Firestein. Automated Sholl analysis of digitized neuronal morphology at multiple scales: Whole cell Sholl analysis versus Sholl analysis of arbor subregions. Cytometry A, 77 (2010), no. 12, 1160-1168. [CrossRef] [PubMed] [Google Scholar]
- F. Li, Z. Yin, G. Jin, H. Zhao, S.T. Wong. Bioimage informatics for systems pharmacology. PLoS Comput Biol. 9 (2013), no. 4, Chapter 17. [Google Scholar]
- S. Mallat. A wavelet tour of signal processing. Academic Press, San Diego, CA, 1998. [Google Scholar]
- N.T. Milosevic, D. Ristanovic, J.B. Stankovic. Fractal analysis of the laminar organization of spinal cord neurons. Journal of Neuroscience Methods, 146 (2005), no. 2, 198-204. [CrossRef] [PubMed] [Google Scholar]
- R. F. Murphy, E. Meijering, G. Danuser. Special issue on molecular and cellular bioimaging. IEEE Trans. Image Process., 14 (2005), no. 9, 1233-1236. [CrossRef] [Google Scholar]
- V. Ntziachristos. Fluorescence molecular imaging. Annu. Rev. Biomed. Eng., 8 (2006), 1-33. [CrossRef] [PubMed] [Google Scholar]
- B. Ozcan, D. Labate, D. Jimenez, M. Papadakis. Directional and non-directional representations for the characterization of neuronal morphology. Wavelets XV (San Diego, CA, 2013), SPIE Proc. 8858 (2013). [Google Scholar]
- V. M. Patel, G. R. Easley, D. M. Healy. Shearlet-based deconvolution. IEEE Trans. Image Proc., 18 (2009), no. 12, 2673-2685. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
- C. Portera-Cailliau, R.M. Weimer, V. De Paola, P. Caroni, K. Svoboda. Diverse modes of axon elaboration in the developing neocortex. PLoS Biol., 3 (2005), no. 8, 1473-1487. [CrossRef] [Google Scholar]
- X. Qi, F. Xing, D. Foran, L. Yang. Robust segmentation of overlapping cells in histopathology specimens using parallel seed detection and repulsive level set. IEEE Trans Biomed Eng, 59 (2012), no. 3, 754-765. [CrossRef] [PubMed] [Google Scholar]
- Y. Rubner, C. Tomasi, L. J. Guibas. A metric for distributions with applications to image databases. Proceedings ICCV, (1998), 59-66. [Google Scholar]
- Y. Rubner, C. Tomasi, L. J. Guibas. The earth mover’s distance as a metric for image retrieval. International Journal of Computer Vision, 40 (2000), no. 2, 99-121. [Google Scholar]
- J. Schoenen. The dendritic organization of the human spinal cord: the dorsal horn. Neuroscience, 7 (1982), 2057-2087. [CrossRef] [PubMed] [Google Scholar]
- D. A. Sholl. Dendritic organization in the neurons of the visual and motor cortices of the cat. J. Anat., 87 (1953), 387-406. [PubMed] [Google Scholar]
- P. Vallotton, R. Lagerstrom, C. Sun, M. Buckley, D. Wang. Automated analysis of neurite branching in cultured cortical neurons using HCA-vision, Cytom. Part A, 71 (2007), no. 10, 889-895. [CrossRef] [Google Scholar]
- C. Vonesch, M. Unser. A fast thresholded Landweber algorithm for wavelet-regularized multidimensional deconvolution. IEEE Trans. Image Proc., 17 (2008), no. 4, 539-549. [CrossRef] [Google Scholar]
- C. Vonesch, M. Unser. A fast multilevel algorithm for wavelet-regularized image restoration. IEEE Trans. Image Proc., 18 (2009), no. 3, 509-523. [CrossRef] [Google Scholar]
- C. Wählby, I. M. Sintorn, F. Erlandsson, G. Borgefors, E. Bengtsson. Combining intensity, edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections. J. Microsc., 215 (2004), 67-76. [Google Scholar]
- G. Weiss, E. Wilson. The mathematical theory of wavelets. Proceeding of the NATO–ASI Meeting. Harmonic Analysis 2000. A Celebration. Kluwer Publisher, (2001). [Google Scholar]
- Q. Wen, A. Stepanyants, G.N. Elston, A. Y. Grosberg, D. B. Chklovskiia. Maximization of the connectivity repertoire as a statistical principle governing the shapes of dendritic arbors. PNAS, 106 (2009), no. 30, 12536-12541. [CrossRef] [Google Scholar]
- C. Yan, A. Li, B. Zhang, W. Ding, Q. Luo, H. Gong. Automated and accurate detection of soma location and surface morphology in large-scale 3D neuron images. PLoS One, no. 8 (2013), 4. [Google Scholar]
- S. Yi, D. Labate, G. R. Easley, H. Krim. A shearlet approach to edge analysis and detection. IEEE Trans. Image Process., 18 (2009), no. 5, 929-941. [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.