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Biomedical Engineering and Bioengineering Commons

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Theses/Dissertations

MRI

University of Iowa

Publication Year

Articles 1 - 3 of 3

Full-Text Articles in Biomedical Engineering and Bioengineering

Detecting Activity-Evoked Ph Changes In Human Brain, Hye Young Heo Jul 2013

Detecting Activity-Evoked Ph Changes In Human Brain, Hye Young Heo

Theses and Dissertations

Localized pH changes have been suggested to occur in the brain during normal function. However, a lack of methods for non-invasively measuring pH with high spatial and temporal resolution limits current knowledge of brain pH dynamics. Here I report that a magnetic resonance imaging (MRI) strategy named T1 relaxation in the rotating frame (T) is sufficiently sensitive to detect widespread pH changes in the mouse and human brain evoked by systemically manipulating carbon dioxide (CO2) or bicarbonate (HCO3). Moreover, T detected changes suggesting a localized acidosis in the human visual cortex induced by a flashing ...


Characterizing Cartilage-Specific T1rho Mri For Clinical Translation And Application, Noelle F. Klocke Jul 2011

Characterizing Cartilage-Specific T1rho Mri For Clinical Translation And Application, Noelle F. Klocke

Theses and Dissertations

T1rho MRI, spin-lattice relaxation in the rotating frame, is postulated to be sensitive to early biochemical changes within articular cartilage that may lead to osteoarthritis. This means that it has potential as a non-invasive, early biomarker for disease progression. However, T1rho has been primarily studied in a research setting. Therefore, the main question posed in this work is:

Can T1rho MRI be used in an at-risk population (ACL-rupture patients) and translated to a clinical setting?

To answer this question, two tools (Relaxometry program, Line Profile Analysis) were created and validated for measuring T1rho within living subjects. These tools were used ...


Multistructure Segmentation Of Multimodal Brain Images Using Artificial Neural Networks, Eun Young Kim Dec 2009

Multistructure Segmentation Of Multimodal Brain Images Using Artificial Neural Networks, Eun Young Kim

Theses and Dissertations

A method for simultaneously segmenting multiple anatomical brain structures from multi-modal MR images has been developed. An artificial neural network (ANN) was trained from a set of feature vectors created by a combination of high-resolution registration methods, atlas based spatial probability distributions, and a training set of 16 expert traced data sets. A set of feature vectors were adapted to increase performance of ANN segmentation; 1) a modified spatial location for structural symmetry of human brain, 2) neighbors along the priors' descent for directional consistency, and 3) candidate vectors based on the priors for the segmentation of multiple structures. The ...