References

Al-Kadi, O.S., 2010. Assessment of texture measures susceptibility to noise in conventional and contrast enhanced computed tomography lung tumour images. Comput. Med. Imaging Graph., 34: 494-503.
CrossRef  |  Direct Link  |  

Andria, G., F. Attivissimo, A.M.L. Lanzolla and M. Savino, 2013. A suitable threshold for speckle reduction in ultrasound images. IEEE Trans. Instrum. Meas., 62: 2270-2279.
CrossRef  |  Direct Link  |  

Bala, E. and A. Ertuzun, 2005. A multivariate thresholding technique for image denoising using multiwavelets. EURASIP J. Applied Signal Process., 2005: 1205-1211.
CrossRef  |  Direct Link  |  

Chicklore, S., V. Goh, M. Siddique, A. Roy, P.K. Marsden and G.J. Cook, 2013. Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis. Eur. J. Nucl. Med. Mol. Imaging, 40: 133-140.
CrossRef  |  Direct Link  |  

Farbiz, F., M.B. Menhaj, S.A. Motamedi and M.T. Hagan, 2000. A new fuzzy logic filter for image enhancement. IEEE Trans. Syst. Man. Cybern. B Cybern., 30: 110-119.
CrossRef  |  

Gevers, T. and A.W. Smeulders, 2000. PicToSeek: Combining color and shape invariant features for image retrieval. IEEE Trans. Image Processing, 9: 102-119.
CrossRef  |  Direct Link  |  

Hiremath, P.S., P.T. Akkasaligar and S. Badiger, 2013. Speckle Noise Reduction in Medical Ultrasound Images. In: Advancements and Breakthroughs in Ultrasound Images, Gunarathne, G. (Ed.). InTech Publishers, Crortia, ISBN: 978-953-51-1159-7, pp: 201-241.

Hu, J., Y. Pu, X. Wu, Y. Zhang and J. Zhou, 2012. Improved DCT-based nonlocal means filter for MR images denoising. Comput. Math. Methods Med., Vol. 2012. 10.1155/2012/232685

Le Bihan, D., 2003. Looking into the functional architecture of the brain with diffusion MRI. Nat. Rev. Neurosci., 4: 469-480.
CrossRef  |  Direct Link  |  

Liu, Y., D. Zhang, G. Lu and W.Y. Ma, 2007. A survey of content-based image retrieval with high-level semantics. Pattern Recognition, 40: 262-282.
CrossRef  |  Direct Link  |  

Minnie, D. and S. Srinivasan, 2014. Preprocessing and generation of association rules for bone marrow analysis data of haematology for acute myeloid leukemia. Asian J. Inform. Technol., 13: 29-37.

Oigard, T.A., L.L. Scharf and A. Hanssen, 2005. Time-frequency and dual-frequency representation of fractional Brownian motion. Proceedings of the IEEE/SP 13th Workshop on Statistical Signal Processing, July 17-20, 2005, Novosibirsk, Russia, pp: 889-894.

Penttinen, A. and J. Virtamo, 2005. Simulation of two-dimensional fractional Brownian motion. Methodol. Comput. Applied Probability, 6: 99-107.
Direct Link  |  

Xu, F., T. Fan, C. Huang, X. Wang and L. Xu, 2014. Block-based MAP superresolution using feature-driven prior model. Math. Problems Eng., Vol. 2014. 10.1155/2014/508357