Publications

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2014
A. J. den Dekker and Sijbers, J., “Data distributions in magnetic resonance images: a review”, Physica Medica, vol. 30, no. 7, pp. 725–741, 2014.PDF icon Download paper (410.33 KB)PDF icon Download paper (protected) (505.58 KB)
G. Ramos-Llordén, den Dekker, A. J., and Sijbers, J., “Joint motion correction and estimation for T1 mapping: proof of concept”, Medical Imaging Summer School 2014, Favignana, Italy. 2014.
J. Rajan, den Dekker, A. J., and Sijbers, J., “A new non local maximum likelihood estimation method for Rician noise reduction in Magnetic Resonance images using the Kolmogorov-Smirnov test”, Signal Processing, vol. 103, pp. 16-23, 2014.
J. Gonnissen, De Backer, A., den Dekker, A. J., Martinez, G. T., Rosenauer, A., Sijbers, J., and Van Aert, S., “Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images”, Applied Physics Letters, vol. 105, no. 063116, 2014.
T. Roelandts, Batenburg, K. J., den Dekker, A. J., and Sijbers, J., “The reconstructed residual error: A novel segmentation evaluation measure for reconstructed images in tomography”, Computer Vision and Image Understanding, vol. 126, pp. 28-37, 2014.PDF icon Download paper (4.58 MB)
2013
A. J. den Dekker, Gonnissen, J., De Backer, A., Sijbers, J., and Van Aert, S., “Estimation of unknown structure parameters from high-resolution (S)TEM images: what are the limits?”, Ultramicroscopy, vol. 134, pp. 34-43, 2013.
J. Rajan, den Dekker, A. J., Juntu, J., and Sijbers, J., “A New Nonlocal Maximum Likelihood Estimation Method for Denoising Magnetic Resonance Images”, in 5th International Conference, PReMI 2013, Kolkata, India, December 10-14, 2013. Proceedings, 2013, Lecture Notes in Computer Science., vol. 8251.
2010
D. H. J. Poot, den Dekker, A. J., Achten, E., Verhoye, M., and Sijbers, J., “Optimal experimental design for Diffusion Kurtosis Imaging”, IEEE Transactions on Medical Imaging, vol. 29, pp. 819-829, 2010.PDF icon Download paper (1.12 MB)
2009
D. H. J. Poot, “Advances in the reconstruction and statistical processing of Magnetic Resonance images”, 2009.PDF icon Download thesis (6.18 MB)
A. J. den Dekker, Poot, D. H. J., Bos, R., and Sijbers, J., “Likelihood based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study”, IEEE Transactions on Medical Imaging, vol. 28, pp. 287-296, 2009.
D. H. J. Poot, den Dekker, A. J., Verhoye, M., Blockx, I., Van Audekerke, J., Van Der Linden, A., and Sijbers, J., “Optimizing the Diffusion Weighting Gradients for Diffusion-Kurtosis Imaging”, ISMRM2009 proceedings, vol. 2009. p. 1394, 2009.PDF icon Download full paper (624.88 KB)
D. H. J. Poot, den Dekker, A. J., and Sijbers, J., “Pearson Set of Distributions as Improved Signal Model for Diffusion Kurtosis Imaging”, ISMRM conference proceedings. ISMRM, p. 1383, 2009.PDF icon Download full paper (638.23 KB)
2008
D. H. J. Poot, Sijbers, J., and den Dekker, A. J., “An exploration of spatial similarities in temporal noise spectra in fMRI measurements”, in Proceedings of SPIE Medical Imaging 2008, San Diego, CA, USA, 2008, vol. 6914, p. 69142.
D. H. J. Poot, Sijbers, J., and den Dekker, A. J., “Optimizing the Diffusion Kurtosis imaging acquisition”, in European Society for Magnetic Resonance in Medicine and Biology, Valencia, Spain, 2008.
2007
J. Sijbers, Poot, D. H. J., den Dekker, A. J., and Pintjens, W., “Automatic estimation of the noise variance from the histogram of a magnetic resonance image”, Physics in Medicine and Biology, vol. 52, pp. 1335-1348, 2007.PDF icon Download paper (297.18 KB)
2006
D. H. J. Poot, Sijbers, J., den Dekker, A. J., and Pintjens, W., “Automatic estimation of the noise variance from the histogram of a magnetic resonance image”, in IEEE/EBMS Benelux Symposium proceedings, 2006, pp. 135-138.
D. H. J. Poot, Sijbers, J., den Dekker, A. J., and Bos, R., “Estimation of the noise variance from the background histogram mode of an MR image”, in Proceedings of SPS-DARTS 2006 (The second annual IEEE BENELUX/DSP Valley Signal Processing Symposium), Antwerp, Belgium, 2006, pp. 159-162.
D. H. J. Poot, Sijbers, J., den Dekker, A. J., and Bos, R., “Estimation of the noise variance from the background histogram mode of an MR image”, in Proceedings of the 25th Benelux Meeting on Systems and Control, Heeze, The Netherlands, 2006.
J. Sijbers, den Dekker, A. J., Poot, D. H. J., Bos, R., Verhoye, M., Van Camp, N., and Van Der Linden, A., “Robust estimation of the noise variance from background MR data”, in Proceedings of SPIE Medical Imaging: Image Processing, San Diego, CA, USA, 2006, vol. 6144, pp. 2018-2028.
2005
A. J. den Dekker and Sijbers, J., “Advanced Image Processing in Magnetic Resonance Imaging”, in Series: Signal Processing and Communications, vol. 27, L. Landini, Ed. Marcel Dekker, 2005, pp. 85-143.
A. J. den Dekker, Sijbers, J., Bos, R., and Smolders, A., “Brain activation detection from functional magnetic resonance imaging data using likelihood based hypothesis tests”, in Abstracts of the 24th Benelux Meeting on Systems and Control, Houffalize, Belgium, 2005.
J. Sijbers and den Dekker, A. J., “Generalized likelihood Ratio tests for complex fMRI data: a simulation study”, IEEE Transactions on Medical Imaging, vol. 24, pp. 604-611, 2005.PDF icon Download paper (377.11 KB)
A. J. den Dekker and Sijbers, J., “Implications of the Rician distribution for fMRI generalized likelihood ratio tests”, Magnetic Resonance Imaging, vol. 23, pp. 953-959, 2005.PDF icon Download paper (1.36 MB)
J. Sijbers, den Dekker, A. J., and Bos, R., “A likelihood ratio test for functional MRI data analysis to account for colored noise”, Lecture Notes in Computer Science, vol. 3708, pp. 538-546, 2005.PDF icon Download full paper (483.15 KB)
2004
A. J. den Dekker and Sijbers, J., “Brain activation detection from magnitude fMRI data using a generalized likelihood ratio test”, in Abstracts of the 23rd Benelux Meeting on Systems and Control, Helvoirt, The Netherlands, 2004.

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