Publications

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2019
R. Heylen, Andrejchenko, V., Zahiri, Z., Parente, M., and Scheunders, P., “Nonlinear hyperspectral unmixing with graphical models”, IEEE Transaction on Geoscience and Remote Sensing, vol. 57, no. 7, pp. 4844-4856, 2019.PDF icon published.pdf (3.15 MB)
B. Auer, De Beenhouwer, J., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., “Preliminary investigation of attenuation and scatter correction strategies for a next-generation SPECT system dedicated to quantitative clinical brain imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Manchester, UK, 2019.
A. Könik, Auer, B., De Beenhouwer, J., Kalluri, K., Zeraatkar, N., Furenlid, L. R., and King, M. A., “Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT”, Physics in Medicine & Biology, vol. 64, no. 24, p. 245001, 2019.PDF icon i123_spectra_final_revision_11_7_19.pdf (7.63 MB)
V. Andrejchenko, Zahiri, Z., Heylen, R., and Scheunders, P., “A spectral mixing model accounting for multiple reflections and shadow”, in IGARSS 2019, International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 286-289.
B. Koirala, Khodadadzadeh, M., Contreras, C., Zahiri, Z., Gloaguen, R., and Scheunders, P., “A supervised method for nonlinear hyperspectral unmixing”, Remote Sensing, vol. 11, no. 20 , 2019.PDF icon remotesensing-11-02458-v3.pdf (3.23 MB)
2020
B. Auer, Kalluri, K., Abayazeed, A. H., De Beenhouwer, J., Zeraatkar, N., Lindsay, C., Momsen, N., R. Richards, G., May, M., Kupinski, M. A., Kuo, P. H., Furenlid, L. R., and King, M. A., “Aperture size selection for improved brain tumor detection and quantification in multi-pinhole 123I-CLINDE SPECT imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Boston, USA (2020), 2020.
B. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Momsen, N., Kuo, P. H., Furenlid, L. R., and King, M. A., “Keel-Edge Height Selection for Improved Multi-Pinhole 123I Brain SPECT Imaging”, Journal of Nuclear Medicine, vol. 61, p. 573, 2020.PDF icon Download paper (127.73 KB)
B. Koirala, Zahiri, Z., and Scheunders, P., “A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements”, IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 10, pp. 7393-7405, 2020.PDF icon final_version_leaf_parameter_estimation.pdf (2.66 MB)
B. Auer, Kalluri, K., De Beenhouwer, J., Doty, K., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., “Reconstruction using Depth of Interaction Information of Curved and Flat Detector Designs for Quantitative Multi-Pinhole Brain SPECT”, Journal of Nuclear Medicine, vol. 61, p. 103, 2020.PDF icon snm2020_recon_curved.pdf (103.23 KB)
2021
J. Van Houtte, Gao, X., Sijbers, J., and Zheng, G., “2D/3D registration with a statistical deformation model prior using deep learning”, in the IEEE International Conference on Biomedical and Health Informatics (BHI'21) , 2021, pp. 1-4.PDF icon Download paper (1.41 MB)
S. Hosseinnejad, Bosch, E. G. T., Kohr, H., Lazić, I., Zharinov, V., Franken, E., Sijbers, J., and De Beenhouwer, J., “3D atomic resolution tomography from iDPC-STEM images using multiple atom model prior”, Microscopy Conference. 2021.PDF icon Download abstract (534.35 KB)
T. Hu, Liu, N., Li, W., Tao, R., Zhang, F., and Scheunders, P., “Destriping Hyperspectral Imagery By Adaptive Anisotropic Total Variation And Truncated Nuclear Norm”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
M. A. Zampini, Sijbers, J., Verhoye, M., and Garipov, R., “EPIFANI for ultrafast B1-corrected T1 and PD mapping”, Magn Reson Mater Phy, vol. 34. pp. S59-S60, 2021.
J. Van Houtte, Vandenberghe, F., Zheng, G., Huysmans, T., and Sijbers, J., “EquiSim: An open-source articulatable statistical model of the equine distal limb”, Frontiers in Veterinary Science , vol. 8, no. 75, 2021.
A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 2021.
A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 2021.
A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 2021.
J. Van Houtte, Sijbers, J., and Zheng, G., “Graphical User Interface for Joint Space Width Assessment by Optical Marker Tracking”, in 4th International Conference on Bio-engineering for Smart Technologies, 2021.
M. Zare, M. Helfroush, S., Kazemi, K., and Scheunders, P., “Hyperspectral and multispectral image fusion using coupled non-negative tucker tensor decomposition”, Remote Sensing, vol. 13, no. 2930, 2021.PDF icon remotesensing-13-02930.pdf (3.79 MB)
T. Hu, Li, W., Liu, N., Tao, R., Zhang, F., and Scheunders, P., “Hyperspectral Image Restoration Using Adaptive Anisotropy Total Variation and Nuclear Norms”, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 2, pp. 1516-1533, 2021.PDF icon tgrs_2020.pdf (5.71 MB)
M. Ljubenović, Zhuang, L., De Beenhouwer, J., and Sijbers, J., “Joint Deblurring and Denoising of THz Time-Domain Images”, IEEE Access, vol. 9, pp. 162-176, 2021.PDF icon Download paper (2.38 MB)
M. A. Zampini, Sijbers, J., Verhoye, M., and Garipov, R., “RAMSES: Relaxation Alternate Mapping of Spoiled Echo Signals sequence for simultaneous accurate T1 and T2* mapping”, ISMRM & SMRT Annual Meeting. 2021.
B. Koirala, Zahiri, Z., Lamberti, A., and Scheunders, P., “Robust supervised method for nonlinear spectral unmixing accounting for endmember variability”, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 9, pp. 7434-7448, 2021.PDF icon ieee_version.pdf (3.76 MB)
2022
J. Van Houtte, Audenaert, E., Zheng, G., and Sijbers, J., “Deep learning-based 2D/3D registration of an atlas to biplanar X-ray images”, International Journal of Computer Assisted Radiology and Surgery, vol. 309, pp. 1333–1342, 2022.PDF icon Download paper (3.41 MB)
G. Pascoletti, Huysmans, T., Conti, P., and Zanetti, E. M., “Evaluation of a Morphable Anthropomorphic Articulated Total Body Model”, in Design Tools and Methods in Industrial Engineering II - Proceedings of the 2nd International Conference on Design Tools and Methods in Industrial Engineering, ADM 2021, 2022, pp. 761–772.

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