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S. Van der Jeught, Sijbers, J., and Dirckx, J. J. J., Fast Fourier-based phase unwrapping on the graphics processing unit in real-time imaging applications, Journal of Imaging, vol. 1, pp. 31-44, 2015.PDF icon Download paper (1.35 MB)
W. Van den Broek, Rosenauer, A., Sijbers, J., Van Dyck, D., and Van Aert, S., A memory efficient method for fully three-dimensional object reconstruction with HAADF STEM Ultramicroscopy, Ultramicroscopy, vol. 141, pp. 22–31, 2014.
W. Van den Broek, Verbeeck, J., De Backer, S., Scheunders, P., and Schryvers, D., Acquisition of the EELS data cube by tomographic reconstruction, Ultramicroscopy, vol. 106, pp. 269-276, 2006.
W. Van den Broek, Verbeeck, J., Schryvers, D., De Backer, S., and Scheunders, P., Tomographic Spectroscopic Imaging; an experimental proof of concept, Ultramicroscopy, vol. 109, pp. 296-303, 2009.
G. Van de Wouwer, Scheunders, P., Van Dyck, D., Wuyts, F. L., and Van de Heyning, P. H., Voice recognition from spectrograms: a wavelet based approach, Fractals, vol. 5, pp. 165-172, 1997.
G. Van de Wouwer, Weyn, B., Scheunders, P., Jacob, W., Van Marck, E., and Van Dyck, D., Automated chromatin-texture based diagnosis of carcinoma nuclei, Journal of Microscopy, vol. 197, pp. 25-35, 2000.
G. Van de Wouwer and Scheunders, P., Wavelet-based texture classification, Recent Research in the Development of Pattern Recognition, vol. 1, pp. 77-87, 2000.
G. Van de Wouwer, Scheunders, P., and Van Dyck, D., Statistical texture characterization from discrete wavelet representations, IEEE Transactions on Image Processing, vol. 8, pp. 592-598, 1999.
G. Van de Wouwer, Scheunders, P., Livens, S., and Van Dyck, D., Wavelet correlation signatures for color texture characterization, pattern Recognition, vol. 32, pp. 443-451, 1999.
T. Van De Looverbosch, Jiaqi, H., Tempelaere, A., Kelchtermans, K., Verboven, P., Tuytelaars, T., Sijbers, J., and Nicolai, B., Inline nondestructive internal disorder detection in pear fruit using explainable deep anomaly detection on X-ray images, Computers and Electronics in Agriculture, vol. 197, no. 106962, pp. 1-14, 2022.
T. Van De Looverbosch, Bhuiyan, H. Rahman, Verboven, P., Dierick, M., Van Loo, D., De Beenhouwer, J., Sijbers, J., and Nicolai, B., Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning, Food Control, vol. 113, no. 107170, pp. 1-13, 2020.
T. Van De Looverbosch, Raeymaekers, E., Verboven, P., Sijbers, J., and Nicolai, B., Non-destructive internal disorder detection of Conference pears by semantic segmentation of X-ray CT scans using deep learning, Expert Systems with Applications, vol. 176, no. 114925, pp. 1-12, 2021.
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., An energy-based beam hardening model in tomography, Physics in Medicine and Biology, vol. 47, pp. 4181-4190, 2002.PDF icon Download full paper (203.21 KB)
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., A model-based correction method for beam hardening artefacts in X-ray microtomography, Journal of X-ray science and technology, vol. 12, pp. 53-57, 2004.PDF icon Download full paper (632.04 KB)
E. Van de Casteele, Perilli, E., Van Aarle, W., Reynolds, K., and Sijbers, J., Discrete tomography in an in vivo small animal bone study, Journal of Bone and Mineral Metabolism, vol. 36, no. 1, pp. 40–53, 2018.
M. Van Dael, Rogge, S., Verboven, P., Saeys, W., Sijbers, J., and Nicolai, B., Online Tomato Inspection Using X-Ray Radiographies and 3- Dimensional Shape Models, Chemical Engineering Transactions, vol. 44, pp. 37-42, 2015.
M. Van Dael, Lebotsa, S., Herremans, E., Verboven, P., Sijbers, J., Opara, U. L., Cronje, U. L., and Nicolai, B., A segmentation and classification algorithm for online detection of internal disorders in citrus using X-ray radiographs, Postharvest Biology and Technology, vol. 112, pp. 205-214, 2016.
M. Van Dael, Verboven, P., Zanella, A., Sijbers, J., and Nicolai, B., Combination of shape and X-ray inspection for apple internal quality control: in silico analysis of the methodology based on X-ray computed tomography, Postharvest Biology and Technology, vol. 148, pp. 218-227, 2019.
M. Van Dael, Verboven, P., Dhaene, J., Van Hoorebeke, L., Sijbers, J., and Nicolai, B., Multisensor X-ray inspection of internal defects in horticultural products, Postharvest Biology and Technology, vol. 128, pp. 33–43, 2017.
S. Van Cauter, Veraart, J., Sijbers, J., Peeters, R. R., Himmelreich, U., Gool, V. S., Van Calenbergh, F., De Vleeschouwer, S., Van Hecke, W., and Sunaert, S., Diffusion kurtosis imaging in the grading of gliomas, Radiology, vol. 2, pp. 492-501, 2012.
N. Van Camp, Blockx, I., Verhoye, M., Casteels, C., Coun, F., Leemans, A., Sijbers, J., Baekelandt, V., Van Laere, K., and Van Der Linden, A., Diffusion tensor imaging in a rat model of Parkinson's disease after lesioning of the nigrostriatal tract., NMR in biomedicine, vol. 22, no. 7, pp. 697-706, 2009.
N. Van Camp, Blockx, I., Camon, L., de Vera, N., Verhoye, M., Veraart, J., Van Hecke, W., Martinez, E., Guadelupe, S., Sijbers, J., Planas, A., and Van Der Linden, A., A complementary DTI-histological study in a model of Huntingtons disease, Neurobiology of Aging, vol. 33, pp. 945-959, 2012.
N. Van Camp, Vreys, R., Van Laere, K., Lauwers, E., Beque, D., Verhoye, M., Casteels, C., Verbruggen, A., Debyser, Z., Mortelmans, L., Sijbers, J., Nuyts, J., Baekelandt, V., and Van Der Linden, A., Morphologic and functional changes in the unilateral 6-hydroxydopamine lesion rat model for Parkinson's disease discerned with microSPECT and quantitative MRI., Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 23, no. 2, pp. 65-75, 2010.
J. Van Audekerke, Verhoye, M., Peeters, R. R., Sijbers, J., and Van Der Linden, A., Special designed RF-antenna with integrated non-invasive carbon electrodes for simultaneous MRI and EEG acquisition at 7T, Magnetic Resonance Imaging, vol. 18, pp. 887-891, 2000.PDF icon Download full paper (179 KB)
S. Van Aert, De Backer, A., Martinez, G. T., den Dekker, A. J., Van Dyck, D., Bals, S., and Van Tendeloo, G., Advanced electron crystallography through model-based imaging, IUCrJ, vol. 3, 2016.