TU Berlin

Numerische MathematikPublikationen

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  • E. Klann, R. Ramlau and P. Sun, A Mumford-Shah-type approach to simultaneous reconstruction and segmentation for emission tomography problems with Poisson statistics. Journal of Inverse and Ill-posed Problems, Jan. 2017 (online).
  • E. Klann, E.T. Quinto and R. Ramlau. Wavelet Methods for a Weighted Sparsity Penalty for Region of Interest Tomography. Inverse Problems 31 (2015) 025001.
  • D. Gerth, E. Klann, R. Ramlau and L. Reichel. On fractional Tikhonov regularization. Journal of Inverse and Ill-posed Problems, May 2015 (online).
  • E. Klann and R. Ramlau, Regularization properties of Mumford-Shah type functionals with perimeter and norm constraints for linear ill-posed problems, SIAM J. Imaging Sci., 6(1), 413–436, 2013.
  • S. Anzengruber, E. Klann, R. Ramlau, and D. Tonova, Numerical Methods for the Design of Gradient Index Optical Coatings, Applied Optics, vol. 51, 8277-8295 (2012).
  • E. Klann, A Mumford-Shah-Like Method for Limited Tomography with an Application to Electron Tomography. SIAM Journal of Imaging Sciences, Vol. 4, Issue 4, pp. 1029-1048, 2011.
  • E. Klann, R. Ramlau, and L. Reichel, Wavelet-Based Multilevel Methods for Linear Ill-Posed Problems. BIT Numer Math DOI 10.1007/s10543-011-0320-x.
  • E. Klann, R. Ramlau, and W. Ring, A Mumford-Shah level-set approach for the inversion and segmentation of SPECT/CT data, Inverse Problems and Imaging, Volume 30, Number 1, May 2011.
  • E. Klann, R. Ramlau, and W. Ring, A Mumford-Shah approach for tomography. In Mathematics and Algorithms in Tomography, Report No. 18/2010, MFO reports, pages 1039-1041, 2010.
  • E. Klann and R. Ramlau. Regularization by Fractional Filter Methods and Data Smoothing. Inverse Problems 24 No. 2, April 2008.
  • E. Klann, R. Ramlau and W. Ring. Simultaneous Reconstruction and Segmentation for Tomography Data. PAMM, Proc. Apl. Math. Mech. 7, 2007.
  • E. Klann, M. Kuhn, D.A. Lorenz, P. Maass and H. Thiele. Shrinkage versus deconvolution. Inverse Problems 23, no.5, p.2231-2248, 2007.
  • E. Klann, P. Maass and R. Ramlau. Two-step regularization methods for linear inverse problems. Journal for Inverse and Ill-Posed Problems, Vol. 14, No. 6, 583 - 609, 2006.
  • E. Klann. Regularization of Linear Ill-posed Problems in Two Steps: Combination of Data Smoothing and Reconstruction Methods. PhD Thesis, University of Bremen, 2006.



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