Collaborative Computational Project in Synergistic Reconstruction for Biomedical Imaging

Synergistic Symposium 2019 Educational Talks

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Kris Thielemans
Chair Welcome
Simon Arridge Methods for joint image reconstruction from multiple modalities
AbstractSeveral imaging problems consider multiple images simultaneously. Examples include colour and multispectral imaging, hybrid imaging in medical imaging (such as PET-MRI, and SPECT-CT), as well as geophysical imaging (electrical and acoustic properties reconstruction). The use of variational regularisation techniques for inverse problems in these applications can treat each image channel seperately or jointly. In this talk, we review some recent progress developing methods based on the joint information of multiple images in terms of both their geometry, and their statistics.
Emil Sidky Image reconstruction methods for energy-resolved CT
AbstractThis talk will focus on the various methods in which dual- or multi-energy transmission data are processed and reconstructed to form tomographic images. The type of images formed depend on how the X-ray attenuation map of the subject is represented in a basis-image expansion. The potential uses of spectral CT images will also be reviewed. Image reconstruction in energy-resolved CT involves two main operations: a processing step that converts energy-windowed data to image basis expansion data and a reconstruction step that forms images from sinograms. The order of these steps or the combination of the steps into an inversion of a spectral CT data model comprise the basic image reconstruction methods. Post-reconstruction processing: energy windowed data are treated as if they were acquired by standard CT and energy-windowed images are reconstructed. The resulting images are combined to form the spectral CT basis image of interest. Pre-reconstruction processing: energy windowed data are processed to estimate sinograms of basis images, which are in turn reconstructed to obtain the basis images themselves. One-step reconstruction: iterative solution of the spectral CT model is performed, where the basis images are obtained directly from the energy-windowed transmission data. The comparative advantages and disadvantages of each approach will be discussed in addition to how these various image reconstruction approaches mesh with different energy-resolved CT hardware configurations. The impact of confounding physical factors and calibration will also be briefly presented.
Rene Botnar Multiparametric MR
AbstractMagnetic resonance imaging (MRI) has become the gold standard for the assessment of cardiac anatomy, left ventricular function, myocardial viability and perfusion due to its excellent soft tissue contrast, high spatial resolution and lack of ionizing radiation. Recent clinical research studies also have demonstrated its usefulness for quantitative myocardial tissue characterization (T1 and T2 relaxation time mapping) and its ability to detect focal and diffuse fibrosis, oedema, iron and protein deposition. In addition, MRI has shown potential for coronary lumen, plaque and thrombus/haemorrhage characterization. A key limitation of the current MRI acquisition scheme is that all imaging sequences are acquired sequentially, in different geometric orientations, at different breath-hold positions or using time inefficient navigator gating methods to compensate for respiratory motion. This imposes several challenges: (1) radiographers need high expertise to perform the complex examination, (2) patients have to perform multiple (>30) breathholds which can be very challenging in sick patients, (3) the duration of the examination is long leading to high operational costs and (4) data fusion is difficult because of the different breathhold positions, scan geometries and non-isotropic spatial resolution. To address these challenges we have developed a self-navigation motion correction framework and combined it with image acceleration techniques to enable motion corrected multi-contrast and quantitative high-resolution free-breathing (no breathholds) 3D cardiac imaging with minimal planning (less training required) and near 100% scan efficiency (faster scans, lower costs). Here we will discuss the latest technical developments and show first results in healthy volunteers and patients with cardiovascular disease.
Ciprian Catana From simultaneous PET-MR to synergistic reconstruction to multimodal data integration Video