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Tomography

Computed tomography (CT)

General and Efficient Super-Resolution method for Multi-Slice MRI

D. H. J. Poot, Van Meir, V., and Sijbers, J., “General and Efficient Super-Resolution method for Multi-Slice MRI”, in Medical Image Computing and Computer Assisted Intervention, 2010, vol. 13, no. 1, pp. 615-622.

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Mediolateral shape and curvature analysis of the clavicle

A. Van Tongel, Huysmans, T., Bernat, A., Sijbers, J., and Van Glabbeek, F., “Mediolateral shape and curvature analysis of the clavicle”, 21st Annual Scientific Meeting of the British Elbow and Shoulder Society in Newcastle. 2011.

Quantitative evaluation of ASiR image quality: an adaptive statistical iterative reconstruction technique

E. Van de Casteele, Parizel, P. M., and Sijbers, J., “Quantitative evaluation of ASiR image quality: an adaptive statistical iterative reconstruction technique”, in SPIE Medical Imaging, 2012, vol. 8313.

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Bone segmentation using discrete tomography

E. Van de Casteele, Batenburg, K. J., Salmon, P., and Sijbers, J., “Bone segmentation using discrete tomography”, in Micro-CT User Meeting, 2011, pp. 178-183.

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A Decision Support System for the Assessment and Stenting of Tracheal Stenosis

R. Pinho, “A Decision Support System for the Assessment and Stenting of Tracheal Stenosis”, University of Antwerp, Antwerp, 2010.

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Towards accurate image reconstruction from truncated X-ray CT projections

G. Van Gompel, “Towards accurate image reconstruction from truncated X-ray CT projections”, University of Antwerp, Antwerp, 2009.

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Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

W. J. Palenstijn, Batenburg, K. J., and Sijbers, J., “Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)”, Journal of structural biology, vol. 176, no. 2, pp. 250-253, 2011.

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Ultra-High Resolution Electron Tomography for Materials Science: A Roadmap

K. J. Batenburg, Bals, S., Van Aert, S., Roelandts, T., and Sijbers, J., “Ultra-High Resolution Electron Tomography for Materials Science: A Roadmap”, Microscopy and Microanalysis 2011 Meeting. Nashville, TN, United States, 2011.

PDART: A Partially Discrete Algorithm for the Reconstruction of Dense Particles

T. Roelandts, Batenburg, K. J., and Sijbers, J., “PDART: A Partially Discrete Algorithm for the Reconstruction of Dense Particles”, in 11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully 3D), Potsdam, Germany, 2011, pp. 448-451.

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Real-time tomographical reconstructions using Neural Networks

Tomographical algorithms can be separated into two classes: analytical “one-step” methods and iterative reconstruction algorithms. Analytical methods are fast, but require projection data of high quality and are impossible to adapt to use prior knowledge about the reconstructed object. Iterative algorithms have less strict requirements for the used data and are more flexible, but their computation time impedes real-time reconstructions. By reformulating the reconstruction problem as a classification problem, a third option becomes available: machine learning.

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