Advanced computational tools for real-time MR imaging

Simple item page
dc.contributorPh.D. Program in Biomedical Engineering.
dc.contributor.advisorAdemoğlu, Ahmet.
dc.contributor.advisorÖztürk, Cengizhan.
dc.contributor.authorSaybaşılı, Haris.
dc.date.accessioned2023-03-16T13:16:56Z
dc.date.available2023-03-16T13:16:56Z
dc.date.issued2009.
dc.description.abstractReal-time Magnetic Resonance Imaging (MRI) has the potential of successfully guiding interventional applications. Overall, the requirements of real-time MRI can be categorized as: (i) fast data acquisition, (ii) fast image reconstruction, and (iii) good image quality. Fast data acquisition is provided by optimized real-time sequences, by parallel MRI (pMRI) techniques, or by non-Cartesian acquisition schemes (e.g. spiral and radial trajectories). However, fast image reconstruction is non-trivial, especially when computations demanding pMRI methods or non-Cartesian trajectories are involved. Even though signal-to-noise ratio (SNR) can be relatively high during real-time imaging, spatial resolution is limited. Thus, improved visual feedback during real-time MRI guided interventions is a must. This thesis defined three specific aims to improve real-time imaging: (i) real-time image reconstruction for pMRI, (ii) real-time image reconstruction for non-Cartesian trajectories, and (iii) fast MRI post-processing for improved visual feedback during interventions. Thesis contributions include: (i) real-time hybrid domain TGRAPPA based pMRI reconstruction algorithm (currently the fastest TGRAPPA based algorithm), (ii) first real-time implementation of GRAPPA Operator Gridding algorithm for radial acquisitions, (iii) multi-phase 3D angiography roadmaps for MRI guided interventions, (iv) improved active device visualization during real-time MRI guided interventions, (v) integration of a real-time active device localizer algorithm.|Keywords: Real-time MRI, pMRI, Non-cartesian trajectories, Parallel processing, MRI guided interventions.
dc.format.extent30cm.
dc.format.pagesxviii, 134 leaves;
dc.identifier.otherBM 2009 S27 PhD
dc.identifier.urihttps://digitalarchive.library.bogazici.edu.tr/handle/123456789/19069
dc.publisherThesis (Ph.D.)-Bogazici University. Institute of Biomedical Engineering, 2009.
dc.subject.lcshMagnetic resonance imaging.
dc.subject.lcshParallel processing (Electronic computers)
dc.titleAdvanced computational tools for real-time MR imaging

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
b1621919.006629.001.PDF
Size:
8.42 MB
Format:
Adobe Portable Document Format
Download

Collections

Ph.D. Theses