Publications

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A
B. Auer, Zeraatkar, N., De Beenhouwer, J., Kalluri, K., Kuo, P. H., Furenlid, L. R., and King, M. A., Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, vol. 11072, pp. 187 – 190.
B. Auer, Könik, A., Fromme, T. J., Kalluri, K., De Beenhouwer, J., Zubal, G. I., Furenlid, L. R., and King, M. A., Preliminary evaluation of surface mesh modeling of system geometry, anatomy phantom, and source activity for GATE simulations, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.
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.
B. Auer, De Beenhouwer, J., Fromme, T. J., Kalluri, K., Goding, J. C., Zubal, G. I., Furenlid, L. R., and King, M. A., Preliminary investigation of design parameters of an innovative multi- pinhole system dedicated to brain SPECT imaging, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.
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. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Könik, A., Kuo, P. H., Furenlid, L. R., and King, M. A., Investigation of keel versus knife edge pinhole profiles for a next-generation SPECT system dedicated to clinical brain imaging, 2nd International Conference on Monte Carlo Techniques for Medical Applications. 2019.
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)
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., and Scheunders, P., Analysis of Plant Stress Response Using Hyperspectral Imaging and Kernel Ridge Regression, in 11th International Conference on Robotics, Vision, Signal Processing and Power Applications, Singapore, 2022, vol. 829.
M. Shahrimie Asaari, Mishra, P., Mertens, S., Dhondt, S., Wuyts, N., and Scheunders, P., Modeling effects of illumination and plant geometry on leaf reflectance spectra in close-range hyperspectral imaging, in 8th WHISPERS - Evolution in Remote Sensing, Los Angeles, USA, 2016.
S. Mohd. Asaari, Analysis of hyperspectral images for high-throughput plant phenotyping , 2019.
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Wuyts, N., and Scheunders, P., Detection of plant responses to drought using close-range hyperspectral imaging in a high-throughput phenotyping platform, in IEEE Whispers 2018, Workshop on Hyperspectral Image and Signal Processing, Amsterdam, 23-26 September , 2018.
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D., Koirala, B., and Scheunders, P., Non-Destructive Analysis of Plant Physiological Traits Using Hyperspectral Imaging: A Case Study on Drought Stress, Computers and Electronics in Agriculture, vol. 195, no. 106806, 2022.PDF icon 1-s2.0-s0168169922001235-main.pdf (5.53 MB)
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D. G., Koirala, B., and Scheunders, P., Non-destructive analysis of plant physiological traits using hyperspectral imaging: A case study on drought stress, Computers and Electronics in Agriculture, vol. 195, 2022.
M. Shahrimie Asaari, Mishra, P., Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., Close-range hyperspectral image analysis for the early detection of plant stress responses in individual plants in a high-throughput phenotyping platform, ISPRS Journal of Photogrammetry and Remote Sensing , vol. 138, pp. 121-138, 2018.
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform, Computers and Electronics in Agriculture, vol. 162, pp. 749-758, 2019.PDF icon shahrimie_2019.pdf (3.12 MB)
G. Araizi-Kanoutas, Geessinck, J., Gauquelin, N., Smit, S., Verbeeck, X. H., Mishra, S. K., Bencok, P., Schlueter, C., Lee, T. - L., Krishnan, D., Fatermans, J., Verbeeck, J., Rijnders, G., Koster, G., and Golden, M. S., Co valence transformation in isopolar LaCoO3/LaTiO3 perovskite heterostructures via interfacial engineering, Phys. Rev. Materials, vol. 4, 2020.
B. T. Antonsen, Jiang, Y., Veraart, J., Qu, H., Nguyen, H. P., Sijbers, J., Von Hörsten, S., Johnson, A. G., and Leergaard, T. B., Altered diffusion tensor imaging measurements in aged transgenic Huntington disease rats., Brain structure & function, vol. 218, no. 3, pp. 767-78, 2013.PDF icon Download paper (645.02 KB)
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.
V. Andrejchenko, Hyperspectral image mixture analysis using notions of sparsity, nonlinearity and decision fusion , 2020.
V. Andrejchenko, Liao, W., Philips, W., and Scheunders, P., Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields, Remote Sensing, vol. 11, 2019.PDF icon remotesensing-11-00624.pdf (1.5 MB)
V. Andrejchenko, Heylen, R., Scheunders, P., Philips, W., and Liao, W., Classification of hyperspectral images with very small training size using sparse unmixing, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 2016.
V. Andrejchenko, Heylen, R., Liao, W., Philips, W., and Scheunders, P., MRF-based decision fusion for hyperspectral image classification, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018.
V. Anania, Jeurissen, B., Morez, J., Buikema, A. Eline, Billiet, T., Sijbers, J., and den Dekker, A. J., Optimal acquisition settings for simultaneous diffusion kurtosis, free water fraction and T2 estimation, Joint Annual Meeting ISMRM-ESMRMB. 2022.

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