Publications
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Direct 3D PET image reconstruction into MR image space University of Antwerp
A method which includes both the motion correction and image registration transformation parameters from PET image space to MR image space within the system matrix of the MLEM algorithm is presented. This approach can be of particular significance in the fields of neuroscience and psychiatry, whereby PET is used to investigate differences in activation patterns between groups of participants (such as healthy controls and patients). This requires ...
Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET KU Leuven
Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, ...
Simultaneous Reconstruction of the Activity Image and Registration of the CT Image in TOF-PET KU Leuven
Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image (or the attenuation sinogram) from TOF-PET data. In this contribution, we propose a method that addresses the same problem for TOF-PET/CT by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the ...
Preserving image texture while reducing radiation dose with a deep learning image reconstruction algorithm in chest CT: A phantom study KU Leuven University of Antwerp
Reconstruction of Uniform Sensitivity Emission Image with Partially Known Axial Attenuation Information in PET-CT Scanners Vrije Universiteit Brussel
In PET-CT the axial length of image reconstruction is defined by the CT scan, which delivers an axial extenddependent radiation dose. The beginning and end scanning points for CT and therefore PET scans are typically chosen in such away that the PET scan is performed with a particular number of beds. While PET bed overlapping is optimized to achieve uniform image sensitivity, the whole volume edge planes suffer from low sensitivity, since only ...
Productively accelerating positron emission tomography image reconstruction on graphics processing units with Julia Ghent University
Research in medical imaging is hampered by a lack of programming languages that support productive, flexible programming as well as high performance. In search for higher quality imaging, researchers can ideally experiment with novel algorithms using rapid-prototyping languages such as Python. However, to speed up image reconstruction, computational resources such as those of GPUs need to be used efficiently. Doing so requires re-programming the ...
Recasting a Viking warrior woman from Ribe: 3D digital image reconstruction compared Vrije Universiteit Brussel
We use 3D digital image reconstruction to recreate a unique anthropomorphic pendant from a group of casting mould fragments found in a workshop at the Viking-age emporium Ribe, Denmark. The image showing a figure in female dress and carrying weapons links a production site to ‘valkyrie’ pendants found in England, Denmark and southern Sweden. We compare three different set-ups for 3D recording and their results in terms of model quality, amount ...
Regularized non-convex image reconstruction in digital holographic microscopy Vrije Universiteit Brussel
Inverse problem approaches for image reconstruction can improve resolution recovery over spatial filtering methods while reducing interference artifacts in digital off-axis holography. Prior works implemented explicit regularization operators in the image space and were only able to match intensity measurements approximatively. As a consequence, convergence to a strictly compatible solution was not possible. In this paper, we replace the ...
Image Reconstruction with Smoothed Mixtures of Regressions Vrije Universiteit Brussel
This work builds upon the kernel regression framework for solving the general image processing problem of denoising, deblurring and interpolating from scattered image samples. A competitive expectation-maximization method estimates globally all parameters of a generative image model, accounting for missing samples. One 2D footprint kernel and a local linear regression plane are estimated per data sample. Kernels can shift and their prior ...