Publications

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Journal Article
M. Bührer, Xu, H., Eller, J., Sijbers, J., Stampanoni, M., and Marone, F., “Unveiling Water Dynamics in Fuel Cells from Time-Resolved Tomographic Microscopy Data”, Scientific Reports, vol. 10, no. 16388 , 2020.PDF icon Download paper (4.12 MB)
M. Brackx, Verhelst, J., Scheunders, P., and Samson, R., “On the use of dorsiventral reflectance asymmetry of hornbeam (Carpinus betulus L.) leaves in air pollution estimation”, Environmental Monitoring and Assessment, vol. 189, no. 9, 2017.
M. Siqueira Pinto, Winzeck, S., Kornaropoulos, E. N., Richter, S., Paolella, R., Correia, M. M., Glocker, B., Williams, G., Vik, A., Posti, J., Håberg, A. Kristine, Stenberg, J., Guns, P. - J., den Dekker, A. J., Menon, D. K., Sijbers, J., Van Dyck, P., and Newcombe, V. F. J., “Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study”, Journal of Neurotrauma, vol. 40, no. 13-14, pp. 1317-1338, 2023.
C. C. Hung, Scheunders, P., Pham, M., Su, M. C., and Coleman, T., “Using Intelligent Optimization Techniques in the K-means Algorithm for Multispectral Image Classification”, International Journal of Fuzzy Systems, vol. 6, pp. 107-117, 2004.
P. Lopes, Van Herck, P., Verhoelst, E., Wirix-Speetjens, R., Sijbers, J., Bosmans, J., and Vander Sloten, J., “Using particle systems for mitral valve segmentation from 3D transoesophageal echocardiography (3D TOE) - a proof of concept”, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol. 11, no. 1, pp. 112-120, 2023.
R. Heylen, Akhter, M. A., and Scheunders, P., “On using projection onto convex sets for solving the hyperspectral unmixing problem”, IEEE Geoscience and Remote Sensing Letters, 2013.
D. Laefer, Zahiri, Z., and Gowen, A., “Using Short-wave Infrared Range Spectrometry Data to Determine Brick Characteristics”, INTERNATIONAL JOURNAL OF ARCHITECTURAL HERITAGE, 2018.
B. Weyn, Tjalam, W., Van de Wouwer, G., Van Daele, A., Scheunders, P., Jacob, W., Van Marck, E., and Van Dyck, D., “Validation of nuclear texture density, morphometry and tissue syntactic structure analysis as prognosticators of cervical carcinoma”, Analytical and Quantitative Cytology and Histology, vol. 22, pp. 373-382, 2000.
K. Hufkens, Scheunders, P., and Ceulemans, R., “Validation of the sigmoid wave curve fitting algorithm on a forest-tundra ecotone in the Northwest Territories, Canada”, Ecological Informatics, vol. 4, pp. 1-7, 2009.
B. Weyn, Van de Wouwer, G., Koprowski, M., Van Daele, A., Dhaene, K., Scheunders, P., Jacob, W., and Van Marck, E., “Value of morphometry, texture analysis, densitometry and histometry in the differential diagnosis and prognosis of malignant mesothelioma”, Journal of Pathology, vol. 4, pp. 581-589, 1999.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging”, Optics Express, vol. 31, no. 21, pp. 38695-38708, 2022.PDF icon Download paper (2.95 MB)
B. Fröhler, Elberfeld, T., Möller, T., Weissenböck, J., De Beenhouwer, J., Sijbers, J., Hege, H. - C., Kastner, J., and Heinzl, C., “A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science”, Computer Graphics Forum, vol. 38, no. 3, pp. 273-283, 2019.
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.
A. Karami, M.Rashidinejad,, and Gharaveisi, A. A., “Voltage Security Enhancement and Congestion Management via STATCOM & IPFC Using Artificial Intelligence”, Iranian Journal of Science and Technology, vol. 1, no. 5, 2007.
D. Iuso, Chatterjee, S., Cornelissen, S., Verhees, D., De Beenhouwer, J., and Sijbers, J., “Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models”, Applied Intelligence, vol. 54, pp. 13160–13177, 2024.PDF icon Download paper (2.48 MB)
J. Sijbers, Verhoye, M., Scheunders, P., Van Der Linden, A., Van Dyck, D., and Raman, E., “Watershed based segmentation of 3D MR data for volume quantization”, Magnetic Resonance Imaging, vol. 15, pp. 679-688, 1997.PDF icon Download paper (3.18 MB)
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.
P. Scheunders and De Backer, S., “Wavelet denoising of multicomponent images, using Gaussian Scale Mixture models and a noise-free image as priors”, IEEE Transactions on Image Processing, vol. 16, pp. 1865-1872, 2007.
P. Scheunders, “Wavelet thresholding of multivalued images”, IEEE Transactions on Image Processing, vol. 13, pp. 475-483, 2004.
A. Duijster, Scheunders, P., and De Backer, S., “Wavelet-Based EM Algorithm for Multispectral-Image Restoration”, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3892-3898, 2009.
P. Scheunders, Livens, S., Van de Wouwer, G., Vautrot, P., and Van Dyck, D., “Wavelet-based texture analysis”, Intern. Journal on Computer Science and Information Management, vol. 1, pp. 22-34, 1998.
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.
J. Veraart, Sijbers, J., Sunaert, S., Leemans, A., and Jeurissen, B., “Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls.”, NeuroImage, vol. 81, no. 1, pp. 335-346, 2013.PDF icon Download paper (2.89 MB)
H. Zivari Adab, Chalavi, S., Beets, I., Gooijers, J., Leunissen, I., Cheval, B., Collier, Q., Sijbers, J., Jeurissen, B., Swinnen, S. P., and Boisgontier, M., “White matter microstructural organization of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults”, European Journal of Neuroscience , vol. 47, no. 5, pp. 446–459, 2018.
S. Van Dongen, Danckaers, F., Beerten, J., and Huysmans, T., “Women's preferences for male facial masculinity are not condition-dependent in a large online study”, The All Results Journals: Biol, vol. 10, no. 1, 2019.

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