Publications

Export 487 results:
[ Author(Asc)] Type Year
Filters: Term is Visionlab and Type is Conference Paper  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
P
A. Presenti, Sijbers, J., den Dekker, A. J., and De Beenhouwer, J., CAD-based defect inspection with optimal view angle selection based on polychromatic X-ray projection images, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019, pp. 1-5.PDF icon ict2019_full_paper_55.pdf (216.2 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., 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.
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., 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.
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.
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.
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.
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, 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.
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, 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, 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.
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, 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, 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, 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, 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)
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, 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, 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.
H. N. B. Pinheiro, Tsang, I. R., Cavalcanti, G. D. C., Tsang, I. J., and Sijbers, J., Type-2 fuzzy GMMs for robust text-independent speaker verification in noisy environments, in International Conference of Pattern Recognition, 2014.
D. Pelt, Sijbers, J., and Batenburg, K. J., Fast Tomographic Reconstruction from Highly Limited Data Using Artificial Neural Networks, in 1st International Conference on Tomography of Materials and Structures (ICTMS), 2013, pp. 109-112.PDF icon Download paper (2.15 MB)

Pages