Publications

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R. Pinho, Luyckx, S., and Sijbers, J., “Robust Region Growing Based Intrathoracic Airway Tree Segmentation”, in Proceedings of 2nd International Workshop on Pulmonary Image Analysis, 2009, pp. 261-271.PDF icon Download paper (1.66 MB)
R. Pinho, Sijbers, J., and Vos, W., “Efficient approaches to intrathoracic airway tree segmentations”, in Proceedings of the Biomedical Engineering IEEE/EMBS Benelux Symposium, Brussels, Belgium, 2006, vol. 2, pp. 151-154.PDF icon Download paper (515.86 KB)
R. Pinho, Tournoy, K. G., Gosselin, R., and Sijbers, J., “A Decision Support System for the Treatment of Tracheal Stenosis”, in Proc. of Workshop on Discrete Geometry and Mathematical Morphology (WADGMM), Istanbul, 2010, pp. 72-76.
R. Pinho, Tournoy, K. G., Gosselin, R., and Sijbers, J., “Assessment of Tracheal Stenosis Using Active Shape Models of Healthy Tracheas: A Surface Registration Study”, in Proceedings of 2nd International Workshop on Pulmonary Image Analysis, 2009, pp. 125-136.
R. Pinho, Huysmans, T., Vos, W., and Sijbers, J., “Tracheal Stent Prediction Using Statistical Deformable Models of Healthy Tracheas”, in Liege Image Days 2008: Medical Imaging, 2008.PDF icon Full text (34.19 KB)
R. Pinho, Batenburg, K. J., and Sijbers, J., “Seeing Through the Window: Pre-fetching Strategies for Out-of-core Image Processing Algorithms”, in Proceedings of SPIE Medical Imaging, San Diego, CA, USA, 2008, vol. 6919.
R. Pinho, Sijbers, J., and Huysmans, T., “Segmentation of The Human Trachea Using Deformable Statistical Models of Tubular Shapes”, in Proceedings of Advanced Concepts for Intelligent Vision Systems, 2007, vol. 4678, pp. 531-542.PDF icon Download paper (570.18 KB)
R. Pinho, Huysmans, T., Vos, W., and Sijbers, J., “Tracheal Stent Prediction Using Statistical Deformable Models of Tubular Shapes”, in Proceedings of SPIE Medical Imaging, San Diego, CA, USA, 2008.PDF icon Full text (773.58 KB)
W. Pintjens, Sijbers, J., Verhoye, M., Van Audekerke, J., and Van Der Linden, A., “A Combined Correction Scheme For EPI Distortions at 7 Tesla”, in Belgian Day on Biomedical Engineering - IEEE/EMBS Benelux Symposium, Brussels, Belgium, 2006, pp. 147-150.
W. Pintjens, Sijbers, J., Verhoye, M., Van Audekerke, J., and Van Der Linden, A., “A total correction scheme for EPI distortions at high field”, in 22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 328-329.
W. Pintjens, Poot, D. H. J., Verhoye, M., Van Der Linden, A., and Sijbers, J., “Susceptibility correction for improved tractography using high field DT-EPI”, in Proceedings of SPIE Medical Imaging, San Diego, USA, 2008, vol. 6914.
W. Pintjens, Poot, D. H. J., Verhoye, M., Van Der Linden, A., and Sijbers, J., “Improved EPI Correction: Upgrading An Ultrafast Imaging Technique”, Liege Image Days 2008: Medical Imaging. 2008.
A. Pizurica, Philips, W., and Scheunders, P., “Wavelet domain denoising of single-band and multi-band images adapted to the probability of the presence of features of interes”, in SPIE Wavelets XI, San Diego, California, USA, 31 July – 4 Aug, 2005, vol. 5914, pp. 508-521.
A. Pizurica, Huysmans, B., Scheunders, P., and Philips, W., “Wavelet domain denoising of multispectral remote sensing imagery adapted to the local spatial and spectral context”, in IEEE International Geoscience and Remote Sensing Symp. IGARSS 2005, Seoul, Korea, 25-29 July, Seoul, Korea, 2005, vol. 6, pp. 4260-4263.
A. Pizurica, Scheunders, P., and Philips, W., “Multiresolution multispectral image denoising based on probability of presence of features of interest”, in Advanced Concepts in Image and Vision Systems, Brussels, 2004, pp. 357-364.
L. Plantagie, Palenstijn, W. J., Sijbers, J., and Batenburg, K. J., “Spatial Variations in Reconstruction Methods for CT”, in The Second International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting), 2012, pp. 170-173.
L. Plantagie, Van Aarle, W., Batenburg, K. J., and Sijbers, J., “Filtered backprojection using algebraic filters; Application to biomedical micro-CT data”, in International Symposium on Biomedical Imaging (ISBI), 2015, pp. 1596-1599.
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., 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, Jeurissen, B., Bastiaensen, Y., Veraart, J., Van Hecke, W., Parizel, P. M., and Sijbers, J., “Super-Resolution for Multislice Diffusion Tensor Imaging”, Magnetic Resonance in Medicine, vol. 69, no. 1, pp. 103–113, 2013.PDF icon Download paper (1.04 MB)
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, Van Meir, V., and Sijbers, J., “General and Efficient Super-Resolution method for Multi-Slice MRI”, in Medical Image Computing and Computer Assisted Intervention, 2010, vol. 13, no. 1, pp. 615-622.PDF icon Download paper (229.84 KB)
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.
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)
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.

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