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G. Thoonen, Vanden Borre, J., De Backer, S., and Scheunders, P., “Assessing the quality of heathland vegetation by classification of hyperspectral data using spatial information”, in Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009, Cape Town, South Africa, 2009, vol. 4, p. IV-330 - IV-333.
G. Thoonen, “Contextual classification of hyperspectral remote sensing images - Application in vegetation monitoring”, University of Antwerp, Antwerp, Belgium, 2012.PDF icon Download thesis (17.15 MB)
G. Thoonen, Hufkens, K., Vanden Borre, J., Spanhove, T., and Scheunders, P., “Accuracy assessment of contextual classification results for vegetation mapping”, International Journal of Applied Earth Observation and Geoinformation, vol. 15, pp. 7 - 15, 2012.
G. Thoonen, Hufkens, K., Vanden Borre, J., and Scheunders, P., “Using patch metrics as validation for contextual classification of heathland vegetation.”, in Proceedings of GEOBIA 2010, the Geographic Object-Based Image Analysis Conference, 2010, vol. XXXVIII-4/C7.
G. Thoonen, Spanhove, T., Vanden Borre, J., and Scheunders, P., “Classification of heathland vegetation in a hierarchical contextual framework”, International Journal of Remote Sensing, vol. 34, no. 1, pp. 96 - 111, 2013.
G. Thoonen, De Backer, S., Provoost, S., Kempeneers, P., and Scheunders, P., “Spatial Classification of Hyperspectral Data of Dune Vegetation along the Belgian Coast”, in Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International, Boston, MA, USA, 2008, vol. 3, p. III-483 - III-486.
G. Thoonen, Spanhove, T., Haest, B., Vanden Borre, J., and Scheunders, P., “Habitat mapping and quality assessment of heathlands using a modified kernel-based reclassification technique”, in Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International, Honolulu, HI, USA, 2010, pp. 2707 - 2710.
C. M. W. Tax, Jeurissen, B., Vos, S. B., Viergever, M. A., and Leemans, A., “Recursive calibration of the fiber response function for spherical deconvolution diffusion ODF sharpening”, ISMRM Workshop on Diffusion as a Probe of Neural Tissue Microstructure. Podstrana, Croatia, 2013.
C. M. W. Tax, Jeurissen, B., Vos, S. B., Viergever, M. A., and Leemans, A., “Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data.”, NeuroImage, vol. 86, pp. 67-80, 2014.
C. M. W. Tax, Jeurissen, B., Viergever, M. A., and Leemans, A., “Robust fiber response function estimation for deconvolution based diffusion MRI methods”, International Society for Magnetic Resonance in Medicine, vol. 21. Salt Lake City, Utah, p. 3149, 2013.
C. M. W. Tax, Jeurissen, B., Viergever, M. A., and Leemans, A., “Robust fiber response function estimation for deconvolution based diffusion MRI methods”, ISMRM Benelux Chapter, vol. 5. Rotterdam, The Netherlands, p. 55, 2013.
A. -yhuwertMurcia Tapias, Giraldo, D., and Romero, E., “Synthesizing fractional anisotropy maps from T1-weighted magnetic resonance images using a simplified generative adversarial network”, in Medical Imaging 2024: Clinical and Biomedical Imaging, 2024, vol. 12930, p. 129302P.
X. Tao, Koirala, B., Plaza, A., and Scheunders, P., “A New Dual-Feature Fusion Network for Enhanced Hyperspectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, pp. 1-1, 2024.PDF icon Download paper (2.13 MB)
N. Tanmay, Liu, G., Hassan, B., Weyn, B., De Backer, S., and Scheunders, P., “Automated Social behaviour Recognition At Low Resolution”, in ICPR14, International Conference on Pattern Recognition, Stockholm, Sweden, 2014.
F. Tajdari, Huysmans, T., Yang, Y., and Song, Y., “Feature preserving non-rigid iterative weighted closest point and semi-curvature registration”, IEEE Transactions on Image Processing, 2022.
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P. V. Sudeep, Palanisamy, P., Kesavadas, C., Sijbers, J., den Dekker, A. J., and Rajan, J., “A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps”, Signal Image and Video Processing, vol. 11, no. 5, pp. 913-920, 2017.
H. Struyfs, Van Hecke, W., Veraart, J., Sijbers, J., Slaets, S., De Belder, M., Wuyts, L., Peters, B., Sleegers, K., Robberecht, C., Van Broeckhoven, C., De Belder, F., Parizel, P. M., and Engelborghs, S., “Diffusion Kurtosis Imaging: a possible MRI biomarker for AD diagnosis?”, Journal of Alzheimer’s Disease, vol. 48, pp. 937-948, 2015.PDF icon Download paper (374.95 KB)
S. Sterckx, Coppin, P., De Backer, S., Debruyn, W., Kempeneers, P., Meuleman, K., Nackaerts, K., Reusen, I., and Scheunders, P., “Information extraction techniques for monitoring of stress symptoms in orchards”, in Proc. Earsel 2003, Imaging Spectroscopy workshop Oberpfaffenhofen, 2003, pp. 278-283.
K. Stanković, Danckaers, F., Booth, B. G., Burg, F., Duerinck, S., Sijbers, J., and Huysmans, T., “Foot Abnormality Mapping using Statistical Shape Modelling”, in 7th International Conference and Exhibition on 3D Body Scanning Technologies (3DBST), 2016, Lugano, Switzerland, 30 November - 1 December., pp. 70-79.
K. Stanković, Huysmans, T., Danckaers, F., Sijbers, J., and Booth, B. G., “Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis”, Expert Systems With Applications, vol. 151, no. 113372, pp. 1-11, 2020.
K. Stanković, “Quantitative assessment of 3D foot shape using statistical shape analysis”, 2022.PDF icon Download thesis (7.16 MB)
K. Stanković, Booth, B. G., Danckaers, F., Burg, F., Vermaelen, P., Duerinck, S., Sijbers, J., and Huysmans, T., “Three-dimensional quantitative analysis of healthy foot shape: a proof of concept study”, Journal of Foot and Ankle Research, vol. 11, no. 8, pp. 1-13, 2018.PDF icon Download paper (2.24 MB)
J. Soons, Danckaers, F., Keustermans, W., Huysmans, T., Sijbers, J., Casselman, J. W., and Dirckx, J. J. J., “3D morphometric analysis of the human incudomallear complex using clinical cone-beam CT”, Hearing research, vol. 340, pp. 79-88, 2016.
J. Soons, Danckaers, F., Huysmans, T., Sijbers, J., Casselamn, J. W., and Dirckx, J. J. J., “Statistical shape modeling of the incudomalleolar complex using micro-CT and clinical cone-beam CT”, MEMRO: 7th International Symposium on Middle Ear Mechanics in Research and Otology. Aalborg, Denmark, 2015.
R. M. Soleimanzadeh, Karami, A., and Scheunders, P., “Fusion of hyperspectral and Lidar images using non-subsampled shearlet transform”, in IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27, 2018.

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