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You searched for +publisher:"University of Houston" +contributor:("Glover, John R."). Showing records 1 – 2 of 2 total matches.

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University of Houston

1. Zhu, Xi 1984-. Single trial analysis of auditory fMRI data.

Degree: PhD, Electrical Engineering, 2012, University of Houston

This research is concerned with functional magnetic resonance imaging (fMRI) of the brain during auditory information processing. The main focus is the exploration of the brain areas involved in sensory gating, i.e., the ability of the central nervous system (CNS) to inhibit or modulate its sensitivity to incoming irrelevant sensory auditory input, as measured using a paired auditory stimulus paradigm. It is well-known that the brain’s responses are variable from trial-to-trial. This calls into question the current practice of using a single, representative response function (canonical HRF) to model fMRI data. Therefore, a correlation-based method was developed to deal with the variability of the HRF in response to repeated presentation of identical auditory stimuli. The goal of the analysis technique is to identify ‘active’ trials among all single trials. We verified that this correlation-based method can find significant differences between brain areas and brain states in actual fMRI data. Second, we determined if the cluster-based method can improve conventional fMRI analysis by exploring the brain regions involved in processing single stimuli using both methods. Data was collected from 14 healthy subjects listening to auditory tones. Our results indicated that by focusing on ‘active’ trials only, as determined by the clustering method, we obtained better statistical maps and that the sensitivity of the fMRI data analysis was increased through the identification of activated areas. The results indicated that the superior temporal gyrus (STG), inferior frontal gyrus (IFG), dorsolateral prefrontal cortex (DLPFC), and thalamus (THA) were involved in auditory information processing and sensory gating in general. While the conventional analysis could not find any regions involved in gating, the correlation-based method confirmed the involvement of bilateral STG, right THA and left DLPFC in sensory gating. Specifically, the right THA relays the sensory signal to the STG, with the bilateral STG involved in the first stage of auditory processing and the left DLPFC involved in the inhibitory circuit of sensory gating processing. Our findings suggest that the correlation-based single trial analysis method provides quantitative assessment of the neuronal origins of the sensory gating. It also improves the current fMRI analysis technique. Advisors/Committee Members: Jansen, Ben H. (advisor), Glover, John R. (committee member), Sheth, Bhavin R. (committee member), Hiscock, Merrill (committee member), Tsekos, Nikolaos V. (committee member).

Subjects/Keywords: Functional magnetic resonance imaging (fMRI); Single trial analysis; Sensory gating; Sensory neuroscience; Signal processing

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

APA (6th Edition):

Zhu, X. 1. (2012). Single trial analysis of auditory fMRI data. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/647

Chicago Manual of Style (16th Edition):

Zhu, Xi 1984-. “Single trial analysis of auditory fMRI data.” 2012. Doctoral Dissertation, University of Houston. Accessed December 03, 2020. http://hdl.handle.net/10657/647.

MLA Handbook (7th Edition):

Zhu, Xi 1984-. “Single trial analysis of auditory fMRI data.” 2012. Web. 03 Dec 2020.

Vancouver:

Zhu X1. Single trial analysis of auditory fMRI data. [Internet] [Doctoral dissertation]. University of Houston; 2012. [cited 2020 Dec 03]. Available from: http://hdl.handle.net/10657/647.

Council of Science Editors:

Zhu X1. Single trial analysis of auditory fMRI data. [Doctoral Dissertation]. University of Houston; 2012. Available from: http://hdl.handle.net/10657/647


University of Houston

2. Lancaster, Keith C. Asymmetry Measures for Automated Melanoma Detection in Dermoscopic Images.

Degree: PhD, Electrical Engineering, 2018, University of Houston

Dermoscopic rules such as the ABCD and Menzies rules are employed by dermatologists to determine the likelihood that a suspicious lesion is cancerous. This dissertation focuses on the improvement of automated melanoma recognition systems that implement these rules, specifically by enhancing the ability of these systems to recognize lesion asymmetry, a significant indicator of melanoma. Two approaches are proposed for asymmetry classification. The first utilizes the irregularity of the outer contour of the lesion combined with measures that compare quadrants of the lesion with respect to area, color, and melanin content. The second method uses size theory as the basis for determining asymmetry. In this approach, measuring functions are employed to expose relevant characteristics of the lesion. The one-dimensional measuring functions are mapped into size functions in R 2 and compared using the bottleneck distance. The distances are used as features for classification. Annotated dermoscopic images were used to train classifiers for both methods. Classification rates were competitive with other approaches for both methods independently, with the combined method exhibiting 95% accuracy. Additionally, decision fusion strategies were investigated as a means of combining the results from individual melanoma classifiers using the asymmetry methods developed in this study. The best approach showed 100% sensitivity and 64% specificity, exceeding the performance of the individual classifiers. Finally, a software framework for the development of medical applications is presented. This framework attempts to provide biomedical researchers with a simplified approach to creating mobile applications for medical processing. Advisors/Committee Members: Zouridakis, George (advisor), Chen, Ji (committee member), Jansen, Ben H. (committee member), Glover, John R. (committee member), Yuan, Xiaojing (committee member).

Subjects/Keywords: Image processing; Smartphone; Melanoma; Automated melanoma recognition

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

APA (6th Edition):

Lancaster, K. C. (2018). Asymmetry Measures for Automated Melanoma Detection in Dermoscopic Images. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/3137

Chicago Manual of Style (16th Edition):

Lancaster, Keith C. “Asymmetry Measures for Automated Melanoma Detection in Dermoscopic Images.” 2018. Doctoral Dissertation, University of Houston. Accessed December 03, 2020. http://hdl.handle.net/10657/3137.

MLA Handbook (7th Edition):

Lancaster, Keith C. “Asymmetry Measures for Automated Melanoma Detection in Dermoscopic Images.” 2018. Web. 03 Dec 2020.

Vancouver:

Lancaster KC. Asymmetry Measures for Automated Melanoma Detection in Dermoscopic Images. [Internet] [Doctoral dissertation]. University of Houston; 2018. [cited 2020 Dec 03]. Available from: http://hdl.handle.net/10657/3137.

Council of Science Editors:

Lancaster KC. Asymmetry Measures for Automated Melanoma Detection in Dermoscopic Images. [Doctoral Dissertation]. University of Houston; 2018. Available from: http://hdl.handle.net/10657/3137

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