Reconstruction of Retinal OCT Images with Sparse Representation
作者： Leyuan Fang , Shutao Li
DOI: 10.1007/978-981-13-1825-2_4
关键词:
摘要: In addition to the speckle noise introduced in acquisition process, clinical-used OCT images often have high resolution and thus create a heavy burden for storage transmission. To alleviate these problems, this chapter introduces several sparse representation based reconstruction methods denoising, interpolation compression, which enhance quality of efficiently manage such large amounts data.
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Jianchao Yang, John Wright, Thomas S Huang, Yi Ma, Image Super-Resolution Via Sparse Representation IEEE Transactions on Image Processing. ,vol. 19, pp. 2861- 2873 ,(2010) , 10.1109/TIP.2010.2050625
Hossein Rabbani, Reza Nezafat, Saeed Gazor, Wavelet-Domain Medical Image Denoising Using Bivariate Laplacian Mixture Model IEEE Transactions on Biomedical Engineering. ,vol. 56, pp. 2826- 2837 ,(2009) , 10.1109/TBME.2009.2028876
Xuan Liu, Jin U. Kang, Compressive SD-OCT: the application of compressed sensing in spectral domain optical coherence tomography Optics Express. ,vol. 18, pp. 22010- 22019 ,(2010) , 10.1364/OE.18.022010
P. Thevenaz, U.E. Ruttimann, M. Unser, A pyramid approach to subpixel registration based on intensity IEEE Transactions on Image Processing. ,vol. 7, pp. 27- 41 ,(1998) , 10.1109/83.650848
A. Wong, A. Mishra, P. Fieguth, D. A. Clausi, Sparse Reconstruction of Breast MRI Using Homotopic $L_0$ Minimization in a Regional Sparsified Domain IEEE Transactions on Biomedical Engineering. ,vol. 60, pp. 743- 752 ,(2013) , 10.1109/TBME.2010.2089456
J. Zepeda, C. Guillemot, E. Kijak, Image Compression Using Sparse Representations and the Iteration-Tuned and Aligned Dictionary IEEE Journal of Selected Topics in Signal Processing. ,vol. 5, pp. 1061- 1073 ,(2011) , 10.1109/JSTSP.2011.2135332
Alessandro Foi, Noise estimation and removal in MR imaging: The variance-stabilization approach 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro. pp. 1809- 1814 ,(2011) , 10.1109/ISBI.2011.5872758
Lin Zhang, Lei Zhang, Xuanqin Mou, D. Zhang, FSIM: A Feature Similarity Index for Image Quality Assessment IEEE Transactions on Image Processing. ,vol. 20, pp. 2378- 2386 ,(2011) , 10.1109/TIP.2011.2109730
Roman Zeyde, Michael Elad, Matan Protter, On Single Image Scale-Up Using Sparse-Representations Curves and Surfaces. pp. 711- 730 ,(2012) , 10.1007/978-3-642-27413-8_47
Wolfgang Drexler, Uwe Morgner, Ravi K. Ghanta, Franz X. Kärtner, Joel S. Schuman, James G. Fujimoto, Ultrahigh-resolution ophthalmic optical coherence tomography Nature Medicine. ,vol. 7, pp. 502- 507 ,(2001) , 10.1038/86589