دانشگاه تبریز
فهرست نشریات دارای اعتبار وزارت علوم، تحقیقات و فناوری
پایگاه استنادی علوم جهان اسلام (ISC)

 آمار

تعداد نشریات45
تعداد شماره‌ها1,392
تعداد مقالات17,028
تعداد مشاهده مقاله54,943,733
تعداد دریافت فایل اصل مقاله17,429,241
Seidzadeh, Maryam Sadat, Roohani Ghehsareh, Hadi, Etesami, Seyed Kamal. (1400). An anomalous diffusion approach for speckle noise reduction in medical ultrasound images. سامانه مدیریت نشریات علمی, 10(1), 225-235. doi: 10.22034/cmde.2020.41858.1812
Maryam Sadat Seidzadeh; Hadi Roohani Ghehsareh; Seyed Kamal Etesami. "An anomalous diffusion approach for speckle noise reduction in medical ultrasound images". سامانه مدیریت نشریات علمی, 10, 1, 1400, 225-235. doi: 10.22034/cmde.2020.41858.1812
Seidzadeh, Maryam Sadat, Roohani Ghehsareh, Hadi, Etesami, Seyed Kamal. (1400). 'An anomalous diffusion approach for speckle noise reduction in medical ultrasound images', سامانه مدیریت نشریات علمی, 10(1), pp. 225-235. doi: 10.22034/cmde.2020.41858.1812
Seidzadeh, Maryam Sadat, Roohani Ghehsareh, Hadi, Etesami, Seyed Kamal. An anomalous diffusion approach for speckle noise reduction in medical ultrasound images. سامانه مدیریت نشریات علمی, 1400; 10(1): 225-235. doi: 10.22034/cmde.2020.41858.1812

An anomalous diffusion approach for speckle noise reduction in medical ultrasound images

Computational Methods for Differential Equations
مقاله 17، دوره 10، شماره 1، فروردین 2022، صفحه 225-235    اصل مقاله (942.62 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22034/cmde.2020.41858.1812
نویسندگان
Maryam Sadat Seidzadeh؛ Hadi Roohani Ghehsareh* ؛ Seyed Kamal Etesami
Department of Mathematics, Faculty of Applied Sciences, Malek Ashtar University of Technology, Shahin Shahr, Iran.
چکیده
Medical ultrasound images are usually degraded by a specific type of noise, called ”speckle”. The presence of speckle noise in medical ultrasound images will reduce the image quality and affect the effective information, which can potentially cause a misdiagnosis. Therefore, medical image enhancement processing has been extensively studied and several denoising approaches have been introduced and developed. In the current work, a robust fractional partial differential equation (FPDE) model based on the anomalous diffusion theory is proposed and used for medical ultrasound image enhancement. An efficient computational approach based on a combination of a time integration scheme and localized meshless method in a domain decomposition framework is performed to deal with the model. In order to evaluate the performance of the proposed de-speckling approach, it is used for speckle noise reduction of a synthetic ultrasound image degraded by different levels of speckle noise. The results indicate the superiority of the proposed approach in comparison with classical anisotropic diffusion denoising model (Catte’s pde model). 
کلیدواژه‌ها
Medical ultrasound images؛ Images denoising؛ Fractional Perona-Malik equation؛ Localized meshfree method؛ Domain decomposition method
مراجع
  • [1]          R. Abazari and M. Lakestani, Fourier based discrete shearlet transform for speckle noise reduction in medical ultrasound images, Current Medical Imaging Reviews., 14 (2018), 447–483.
  • [2]          R. Abazari and M. Lakestani, A hybrid denoising algorithm based on shearlet transform method and yaroslavskys filter, Multimedia Tools and Applications., 77 (2018), 17829–17851.
  • [3]          R. Abazari and M. Lakestani, Non-subsampled shearlet transform and log-transform methods for despeckling of medical ultrasound images, Informatica., 30 (2019), 1–19.
  • [4]          S. Abbasbandy, H. R. Ghehsareh, and I. Hashim, A meshfree method for the solution of two-dimensional cubic nonlinear Schr¨odinger equation, Engineering Analysis with Boundary Elements., 37 (2013), 885–898.
  • [5]          S. Abbasbandy, H. R. Ghehsareh, I. Hashim and A. Alsaedi, A comparison study of meshfree  techniques  for  solving the two-dimensional linear hyperbolic telegraph equation, Engineering Analysis with Boundary Elements., 40 (2014), 10–20.
  • [6]          L. Alvarez, P.-L. Lions, and J.-M. Morel, Image selective smoothing and edge detection by nonlinear diffusion, SIAM Journal on numerical analysis., 29 (1992), 845–866.
  • [7]          G. Aubert and P. Kornprobst, Mathematical problems in image processing: partial differential equations and the calculus of variations, volume 147. Springer Science & Business Media, 2006.
  • [8]          J. Bai and X.-C. Feng, Fractional-order anisotropic diffusion for image denoising, IEEE transactions on image processing., 16(2007), 2492–2502.
  • [9]          F.  Catt´e,  P.-L.  Lions,  J.-M.  Morel,  and  T.  Coll,  Image  selective  smoothing  and  edge  detection  by  nonlinear diffusion, SIAM Journal on Numerical analysis., 29(1992), 182–193.
  • [10]        R. N. Czerwinski, D. L. Jones, and W. D. O’brien, Line and boundary detection in speckle images, IEEE Trans- actions on Image Processing., 7(1998), 1700–1714.
  • [11]        S. Das and I. Pan, Fractional order signal processing: introductory concepts and applications, Springer Science & Business Media, 2011.
  • [12]        M. H. Esfahani, H. R. Ghehsareh, and S. K. Etesami, The extended method  of  approximate  particular  solutions  to simulate two-dimensional electromagnetic scattering from arbitrary shaped anisotropic objects, Engineering Analysis with Boundary Elements., 82 (2017), 91–97.
  • [13]        G. E. Fasshauer, Meshfree approximation methods with MATLAB, volume 6, World Scientific, 2007.
  • [14]        D. Firsov and S. Lui, Domain decomposition methods in image denoising using gaussian curvature, Journal of Computational and Applied Mathematics., 193 (2006), 460–473.
  • [15]        H. R. Ghehsareh, A. Majlesi, and A. Zaghian, Lie symmetry analysis and conservation laws for time fractional coupled whitham-broer-kaup equations, UPB Sci. Bull. Ser. A Appl. Math. Phys., 80 (2018), 153–168.
  • [16]        H. R. Ghehsareh, M. Raei, and A. Zaghian, Application of meshless local petrov- galerkin technique to simulate two-dimensional time-fractional tricomi-type problem, Journal of the Brazilian Society of Mechanical Sciences and Engineering., 41 (2019), 252.
  • [17]        H. R. Ghehsareh, M. Raei, and A. Zaghian, Numerical simulation of a modified anomalous diffusion process with nonlinear source term by a local weak form meshless method, Engineering Analysis with Boundary Elements., 98 (2019), 64–76.
  • [18]        H. R. Ghehsareh, A. Zaghian, and M. Raei, A local weak form meshless method to simulate a variable order time- fractional mobile-immobile transport model, Engineering Analysis with Boundary Elements., 90 (2018), 63–75.
  • [19]        H. R. Ghehsareh, A. Zaghian, and S. M. Zabetzadeh, The use of local radial point interpolation method for solving two-dimensional linear fractional cable equation, Neural Computing and Applications., 29 (2018), 745–754.
  • [20]        J. W. Goodman, Some fundamental properties of speckle, JOSA., 66 (1976), 1145–1150.
  • [21]        F. Guan, P. Ton, S. Ge, and L. Zhao, Anisotropic diffusion fltering for ultrasound speckle reduction, Science China Technological Sciences., 57 (2014), 607–614.
  • [22]        A. Handloviˇcov´a, K. Mikula, and F. Sgallari, Variational numerical methods for solving nonlinear diffusion equa- tions arising in image processing, Journal of Visual Communication and Image Representation., 13 (2002), 217– 237.
  • [23]        X. Hao, S. Gao, and X. Gao, A novel multiscale nonlinear thresholding method for ultrasonic speckle suppressing, IEEE Transactions on Medical Imaging., 18 (1999), 787–794.
  • [24]        M. Hashemi and A. Akgu¨l, Solitary wave solutions of time-space nonlinear fractional schrodingers equation:  two analytical approaches, Journal of Computational and Applied Mathematics., 339 (2018), 147–160.
  • [25]        M. Hashemi and Z. Balmeh, On invariant analysis and conservation laws of the time fractional variant boussinesq and coupled boussinesq-burgers equations, The European Physical Journal Plus., 133 (2018), 427.
  • [26]        M. Hashemi, M. Inc, M. Parto-Haghighi, and M. Bayram, On numerical solution of the time-fractional diffusion- wave equation with the fictitious time integration  method,  The  European  Physical Journal  Plus.,  134  (2019), 488.
  • [27]        K. H¨ollig and J. A. Nohel, A diffusion equation with a nonmonotone constitutive function, Systems of Nonlinear Partial Differential Equations., Springer. (1983), 409–422.
  • [28]        M. Janev, S. Pilipovi´c, T. Atanackovi´c, R. Obradovi´c, and N. Ralevi´c, Fully  fractional  anisotropic  diffusion  for image denoising, Mathematical and Computer Modelling., 54 (2011), 729–741.
  • [29]        M. Kamranian, M. Dehghan, and M. Tatari, An image denoising approach based on a meshfree method and the domain decomposition technique, Engineering Analysis with Boundary Elements., 39 (2014), 101–110.
  • [30]        E. J. Kansa, Multiquadricsa scattered data approximation scheme with applications to computational fluid- dynamicsi surface approximations and partial derivative estimates, Computers & Mathematics with applications., 19 (1990), 127–145.
  • [31]        M. Khaksarfard, Y. Ordokhani, M. S. Hashemi, and K. Karimi, Space-time radial basis function collocation method for one-dimensional advection-diffusion problem, Computational Methods for Differential Equations., 6 (2018), 426–437.
  • [32]        M. A. Khan, W. Chen, Z. Fu, and A. Ullah, Meshfree digital total variation based  algorithm  for  multiplicative noise removal., J. Inf. Sci. Eng., 34 (2018), 1441–1468.
  • [33]        M. A. Khan, W. Chen, A. Ullah, and Z. Fu, A mesh-free algorithm for rof model., EURASIP Journal on Advances  in Signal Processing., 53 (2017) .
  • [34]        S. Kichenassamy, The perona-malik paradox., SIAM Journal on Applied Mathematics., 57 (1997), 1328–1342.
  • [35]        J.-S. Lee, Digital image enhancement and noise filtering by use of local statistics., IEEE Transactions on Pattern Analysis & Machine Intelligence., 2 (1980), 165–168.
  • [36]        L. Ling, R. Opfer, and R. Schaback, Results on meshless collocation techniques.,Engineering Analysis with Bound- ary Elements., 30 (2006), 247–253.
  • [37]        G.-R. Liu and Y.-T. Gu, An introduction to meshfree methods and their programming.,Springer Science & Business Media, 2005.
  • [38]        C. P. Loizou and C. S. Pattichis, Despeckle filtering algorithms and software for ultrasound imaging., Synthesis lectures on algorithms and software in engineering., 1 (2008), 166.
  • [39]        A. Majlesi, H. R. Ghehsareh, and A. Zaghian, On the fractional jaulent-miodek equation associated with energy- dependent schrodinger potential: Lie symmetry reductions, explicit exact solutions and conservation laws., The European Physical Journal Plus., 132 (2017), 516.
  • [40]        J. L. Mateo and A. Fern´andez-Caballero, Finding out general tendencies in speckle noise reduction in ultrasound images., Expert systems with applications., 36 (2009), 7786–7797.
  • [41]        N. Mohamadi, A. R. Soheili, and F. Toutounian, A denoising pde model based on isotropic diffusion and total variation models., Computational Methods for Differential Equations., 8 (2020), 815–826.
  • [42]        P. Noras and N. Aghazadeh, New denoising and edge detection scheme based on rationalized haar functions., MACHINE VISION AND IMAGE PROCESSING., 5 (2018), 99–111.
  • [43]        P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion., IEEE Transactions on pattern analysis and machine intelligence., 12 (1990), 629–639.
  • [44]        P. Perona, T. Shiota, and J. Malik, Anisotropic diffusion., In Geometry-driven diffusion in computer vision., Springer, (1994), 73–92.
  • [45]        Y. Povstenko, Fractional thermoelasticity., In Geometry-driven diffusion in computer vision., volume 219. Springer, 2015.
  • [46]        E. Ritenour, T. Nelson, and U. Raff, Applications of the median filter to digital radiographic images., In ICASSP’84. IEEE International Conference on Acoustics, Speech, and Signal Processing., volume 9 (1984), 251– 254.
  • [47]        H. Roohani Ghehsareh, M. Hajisadeghi Esfahani, and S. Kamal Etesami, Numerical simulation of electromagnetic wave scattering from  perfectly  conducting cylinders using the local  radial point interpolation technique., Journal  of Electromagnetic Waves and Applications., 33 (2019), 335–349.
  • [48]        H. Roohani Ghehsareh, M. S. Seidzadeh, and S. K. Etesami, Numerical simulation of a generalized anomalous electro-diffusion process in nerve cells by a localized meshless approach in pseudospectral mode., International Journal of Numerical Modelling: Electronic Networks, Devices and Fields., (2020).
  • [49]        M. Safarpoor and A. Shirzadi, Numerical investigation based on radial basis function- finite-difference (rbf-fd) method for solving the stokes-darcy equations., Engineering with Computers., (2019).
  • [50]        M. Safarpoor, F. Takhtabnoos, and A. Shirzadi, A localized rbf-mlpg method and its application to elliptic pdes., Engineering with Computers., (2019).
  • [51]        A. Shirzadi, Solving 2d reaction-diffusion equations with nonlocal boundary conditions by the rbf-mlpg method., Computational Mathematics and Modeling., 25 (2014), 521–529.
  • [52]        A. Shirzadi, L. Ling, and S. Abbasbandy, Meshless simulations of the two-dimensional fractional-time convection- diffusion-reaction equations., Engineering analysis with boundary elements., 36 (2012), 1522–1527.
  • [53]        E. Shivanian, Pseudospectral meshless radial point hermit interpolation versus pseudospectral meshless radial point interpolation., International Journal of Computational Methods., (2019).
  • [54]        E. Shivanian and H. Fatahi, Analysis of meshless local radial point interpolant on a model in population dynamics., Computational Methods for Differential Equations., 7 (2019), 276–288.
  • [55]        E. Shivanian and A. Jafarabadi, Two-dimensional capillary formation model in tumor angiogenesis problem through spectral meshless radial point interpolation., Engineering with Computers., (2019).
  • [56]        V. Sladek, J. Sladek, and A. Shirzadi, The local integral equation method for pattern formation simulations in reaction-diffusion systems., Engineering Analysis with Boundary Elements., 50 (2015), 329–340.
  • [57]        Z.-z. Sun and X. Wu, A fully discrete difference scheme for a diffusion-wave system., Applied Numerical Mathe- matics., 56 (2006), 193–209.
  • [58]        F. Takhtabnoos and A. Shirzadi, A local meshless method based on the nite collocation and local integral equations method for delay pdes., Engineering Analysis with Boundary Ele- ments., 83 (2017), 67–73.
  • [59]        V. V. Uchaikin, Fractional derivatives for physicists and engineers., volume 2. Springer, 2013.
  • [60]        L. A. Vese and S. J. Osher., Modeling textures with total variation minimization and oscillating patterns in image processing., Journal of scientific computing., 19 (2003), 553–572.
  • [61]        R. F. Wagner., Statistics of speckle in ultrasound B-scans., IEEE Trans. Sonics & Ultrason., 30 (1983), 156–163.
  • [62]        J. Weickert., Anisotropic diffusion in image processing., volume 1. Teubner Stuttgart, 1998.
  • [63]        J. Weickert and C. Schn¨orr, Pde-based preprocessing of medical images., 2000.
  • [64]        M. Wielgus., Perona-malik equation and its numerical properties., arXiv preprint arXiv:1412.6291, 2014.
  • [65]        Q. Yang, D. Chen, T. Zhao, and Y. Chen, Fractional calculus in image processing: a review., Fractional Calculus and Applied Analysis., 19 (2016), 1222–1249.
  • [66]        Y. Yu and S. T. Acton, Speckle reducing anisotropic diffusion., IEEE Transactions on image processing., 11 (2002), 1260–1270.
  • [67]        J. Zhang and Z. Wei, Fractional variational model and algorithm for image denoising., In 2008 Fourth International Conference on Natural Computation., volume 5, pages 524-528. IEEE, 2008.
  • [68]        J. Zhang, Z. Wei, and L. Xiao, Adaptive fractional-order multi-scale method for image denoising., Journal of Mathematical Imaging and Vision., 43 (2012), 39–49.
آمار
تعداد مشاهده مقاله: 913
تعداد دریافت فایل اصل مقاله: 875


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب