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You searched for +publisher:"Georgia Tech" +contributor:("Brummer, Marijn"). Showing records 1 – 6 of 6 total matches.

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Georgia Tech

1. Rane, Swati. Diffusion tensor imaging at long diffusion time.

Degree: PhD, Biomedical Engineering, 2009, Georgia Tech

 Diffusion Tensor Imaging (DTI) is a well-established magnetic resonance technique that can non-invasively interpret tissue geometry and track neural pathways by sampling the diffusion of… (more)

Subjects/Keywords: In vivo; Ex vivo; Fixed; Rhesus; Fiber tracking; FA; DTI; Diffusion time; Fractional anisotropy; ADC; Diagnostic imaging; Imaging systems in medicine; Magnetic resonance imaging; Diffusion tensor imaging; Diffusion magnetic resonance imaging

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APA (6th Edition):

Rane, S. (2009). Diffusion tensor imaging at long diffusion time. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/29708

Chicago Manual of Style (16th Edition):

Rane, Swati. “Diffusion tensor imaging at long diffusion time.” 2009. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/29708.

MLA Handbook (7th Edition):

Rane, Swati. “Diffusion tensor imaging at long diffusion time.” 2009. Web. 20 Oct 2019.

Vancouver:

Rane S. Diffusion tensor imaging at long diffusion time. [Internet] [Doctoral dissertation]. Georgia Tech; 2009. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/29708.

Council of Science Editors:

Rane S. Diffusion tensor imaging at long diffusion time. [Doctoral Dissertation]. Georgia Tech; 2009. Available from: http://hdl.handle.net/1853/29708

2. Muir, Eric R. Magnetic resonance imaging of retinal physiology and anatomy in mice.

Degree: PhD, Biomedical Engineering, 2010, Georgia Tech

 MRI can provide anatomical, functional, and physiological images at relatively high spatial resolution and is non-invasive and does not have depth limitation. However, the application… (more)

Subjects/Keywords: Choroid; Diabetic retinopathy; Retinal degeneration; Retina; Blood flow; Arterial spin labeling; Magnetic resonance imaging; Retina Diseases; Degeneration (Pathology); Diagnostic imaging

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APA (6th Edition):

Muir, E. R. (2010). Magnetic resonance imaging of retinal physiology and anatomy in mice. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/37268

Chicago Manual of Style (16th Edition):

Muir, Eric R. “Magnetic resonance imaging of retinal physiology and anatomy in mice.” 2010. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/37268.

MLA Handbook (7th Edition):

Muir, Eric R. “Magnetic resonance imaging of retinal physiology and anatomy in mice.” 2010. Web. 20 Oct 2019.

Vancouver:

Muir ER. Magnetic resonance imaging of retinal physiology and anatomy in mice. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/37268.

Council of Science Editors:

Muir ER. Magnetic resonance imaging of retinal physiology and anatomy in mice. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/37268

3. Suever, Jonathan D. MRI methods for predicting response to cardiac resynchronization therapy.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2013, Georgia Tech

 Cardiac Resynchronization Therapy (CRT) is a treatment option for heart failure patients with ventricular dyssynchrony. CRT corrects for dyssynchrony by electrically stimulating the septal and… (more)

Subjects/Keywords: Magnetic resonance imaging; Cardiac resynchronization therapy; Electrophysiology; Image processing; Heart failure; Heart Magnetic resonance imaging; Cardiac pacing; Electric stimulation; Congestive heart failure Treatment

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APA (6th Edition):

Suever, J. D. (2013). MRI methods for predicting response to cardiac resynchronization therapy. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50224

Chicago Manual of Style (16th Edition):

Suever, Jonathan D. “MRI methods for predicting response to cardiac resynchronization therapy.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/50224.

MLA Handbook (7th Edition):

Suever, Jonathan D. “MRI methods for predicting response to cardiac resynchronization therapy.” 2013. Web. 20 Oct 2019.

Vancouver:

Suever JD. MRI methods for predicting response to cardiac resynchronization therapy. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/50224.

Council of Science Editors:

Suever JD. MRI methods for predicting response to cardiac resynchronization therapy. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50224


Georgia Tech

4. Wallin, Ashley Kay. Renal Arterial Blood Flow Quantification by Breath-held Phase-velocity Encoded MRI.

Degree: MS, Bioengineering, 2004, Georgia Tech

 Autosomal dominant polycystic disease (ADPKD) is the most common hereditary renal disease and is characterized by renal cyst growth and enlargement. Hypertension occurs early when… (more)

Subjects/Keywords: Bland-Altman plot; Magnetic resonance imaging; Blood flow; Polyvinyl alcohol; Phase-velocity encoded MRI; Autosomal dominant polycystic kidney disease; PC-MRI accuracy and precision; Renal circulation; Polycystic kidney disease Magnetic resonance imaging; Magnetic resonance imaging

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APA (6th Edition):

Wallin, A. K. (2004). Renal Arterial Blood Flow Quantification by Breath-held Phase-velocity Encoded MRI. (Masters Thesis). Georgia Tech. Retrieved from http://hdl.handle.net/1853/4982

Chicago Manual of Style (16th Edition):

Wallin, Ashley Kay. “Renal Arterial Blood Flow Quantification by Breath-held Phase-velocity Encoded MRI.” 2004. Masters Thesis, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/4982.

MLA Handbook (7th Edition):

Wallin, Ashley Kay. “Renal Arterial Blood Flow Quantification by Breath-held Phase-velocity Encoded MRI.” 2004. Web. 20 Oct 2019.

Vancouver:

Wallin AK. Renal Arterial Blood Flow Quantification by Breath-held Phase-velocity Encoded MRI. [Internet] [Masters thesis]. Georgia Tech; 2004. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/4982.

Council of Science Editors:

Wallin AK. Renal Arterial Blood Flow Quantification by Breath-held Phase-velocity Encoded MRI. [Masters Thesis]. Georgia Tech; 2004. Available from: http://hdl.handle.net/1853/4982


Georgia Tech

5. Deshpande, Gopikrishna. Nonlinear and network characterization of brain function using functional MRI.

Degree: PhD, Biomedical Engineering, 2007, Georgia Tech

 Functional magnetic resonance imaging (fMRI) has emerged as the method of choice to non-invasively investigate brain function in humans. Though brain is known to act… (more)

Subjects/Keywords: Functional magnetic resonance imaging; Nonlinear dynamics; Granger causality; Brain networks; Signal and image processing; Brain Localization of functions; Magnetic resonance imaging; Nonlinear functional analysis; Dynamics

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APA (6th Edition):

Deshpande, G. (2007). Nonlinear and network characterization of brain function using functional MRI. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/24760

Chicago Manual of Style (16th Edition):

Deshpande, Gopikrishna. “Nonlinear and network characterization of brain function using functional MRI.” 2007. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/24760.

MLA Handbook (7th Edition):

Deshpande, Gopikrishna. “Nonlinear and network characterization of brain function using functional MRI.” 2007. Web. 20 Oct 2019.

Vancouver:

Deshpande G. Nonlinear and network characterization of brain function using functional MRI. [Internet] [Doctoral dissertation]. Georgia Tech; 2007. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/24760.

Council of Science Editors:

Deshpande G. Nonlinear and network characterization of brain function using functional MRI. [Doctoral Dissertation]. Georgia Tech; 2007. Available from: http://hdl.handle.net/1853/24760


Georgia Tech

6. Abufadel, Amer Y. 4D Segmentation of Cardiac MRI Data Using Active Surfaces with Spatiotemporal Shape Priors.

Degree: PhD, Electrical and Computer Engineering, 2006, Georgia Tech

 This dissertation presents a fully automatic segmentation algorithm for cardiac MR data. Some of the currently published methods are automatic, but they only work well… (more)

Subjects/Keywords: Shape priors; 4D segmentation; Level sets; Confidence labels; Imaging systems in medicine; Magnetic resonance imaging; Diagnostic imaging; Image processing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Abufadel, A. Y. (2006). 4D Segmentation of Cardiac MRI Data Using Active Surfaces with Spatiotemporal Shape Priors. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/14005

Chicago Manual of Style (16th Edition):

Abufadel, Amer Y. “4D Segmentation of Cardiac MRI Data Using Active Surfaces with Spatiotemporal Shape Priors.” 2006. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/14005.

MLA Handbook (7th Edition):

Abufadel, Amer Y. “4D Segmentation of Cardiac MRI Data Using Active Surfaces with Spatiotemporal Shape Priors.” 2006. Web. 20 Oct 2019.

Vancouver:

Abufadel AY. 4D Segmentation of Cardiac MRI Data Using Active Surfaces with Spatiotemporal Shape Priors. [Internet] [Doctoral dissertation]. Georgia Tech; 2006. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/14005.

Council of Science Editors:

Abufadel AY. 4D Segmentation of Cardiac MRI Data Using Active Surfaces with Spatiotemporal Shape Priors. [Doctoral Dissertation]. Georgia Tech; 2006. Available from: http://hdl.handle.net/1853/14005

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