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You searched for +publisher:"University of Southern California" +contributor:("Leahy, Richard M."). Showing records 1 – 30 of 32 total matches.

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University of Southern California

1. Zhu, Wentao. Direct wholebody Patlak and Logan image estimation from listmode PET data.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 We investigate using list‐mode PET data to perform Patlak and Logan modeling. We first propose an estimation method for irreversible tracers (where Patlak modeling is… (more)

Subjects/Keywords: direct; wholebody; Patlak; Logan; listmode

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APA (6th Edition):

Zhu, W. (2014). Direct wholebody Patlak and Logan image estimation from listmode PET data. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/459551/rec/2011

Chicago Manual of Style (16th Edition):

Zhu, Wentao. “Direct wholebody Patlak and Logan image estimation from listmode PET data.” 2014. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/459551/rec/2011.

MLA Handbook (7th Edition):

Zhu, Wentao. “Direct wholebody Patlak and Logan image estimation from listmode PET data.” 2014. Web. 17 Oct 2019.

Vancouver:

Zhu W. Direct wholebody Patlak and Logan image estimation from listmode PET data. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/459551/rec/2011.

Council of Science Editors:

Zhu W. Direct wholebody Patlak and Logan image estimation from listmode PET data. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/459551/rec/2011


University of Southern California

2. Cho, Sungje. Techniques for de novo sequence assembly: algorithms and experimental results.

Degree: PhD, Electrical Engineering, 2012, University of Southern California

 The deep sequencing of second generation sequencing technology has enabled us to study complex biological structures, which have multiple DNA units simultaneously such as transcriptomics… (more)

Subjects/Keywords: computational biology; bioinformatics; sequence assembly

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APA (6th Edition):

Cho, S. (2012). Techniques for de novo sequence assembly: algorithms and experimental results. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/77527/rec/6362

Chicago Manual of Style (16th Edition):

Cho, Sungje. “Techniques for de novo sequence assembly: algorithms and experimental results.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/77527/rec/6362.

MLA Handbook (7th Edition):

Cho, Sungje. “Techniques for de novo sequence assembly: algorithms and experimental results.” 2012. Web. 17 Oct 2019.

Vancouver:

Cho S. Techniques for de novo sequence assembly: algorithms and experimental results. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/77527/rec/6362.

Council of Science Editors:

Cho S. Techniques for de novo sequence assembly: algorithms and experimental results. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/77527/rec/6362


University of Southern California

3. Somayajula, Sangeetha. Information theoretic measures for PET image reconstruction and non-rigid image registration.

Degree: PhD, Electrical Engineering, 2009, University of Southern California

 We explore the use of information theoretic measures for positron emission tomography (PET) image reconstruction and for multi-modality non-rigid registration.; PET is a functional imaging… (more)

Subjects/Keywords: biomedical imaging; joint entropy; multi-modality imaging; mutual information; PET reconstruction; image registration

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APA (6th Edition):

Somayajula, S. (2009). Information theoretic measures for PET image reconstruction and non-rigid image registration. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/268947/rec/3488

Chicago Manual of Style (16th Edition):

Somayajula, Sangeetha. “Information theoretic measures for PET image reconstruction and non-rigid image registration.” 2009. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/268947/rec/3488.

MLA Handbook (7th Edition):

Somayajula, Sangeetha. “Information theoretic measures for PET image reconstruction and non-rigid image registration.” 2009. Web. 17 Oct 2019.

Vancouver:

Somayajula S. Information theoretic measures for PET image reconstruction and non-rigid image registration. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/268947/rec/3488.

Council of Science Editors:

Somayajula S. Information theoretic measures for PET image reconstruction and non-rigid image registration. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/268947/rec/3488


University of Southern California

4. Karimi-Ashtiani, Shahryar. Theory and simulation of diffusion magnetic resonance imaging on brain's white matter.

Degree: PhD, Electrical Engineering, 2012, University of Southern California

 Diffusion MRI (D-MRI) has opened a new front for uncovering the convoluted structure of the central nervous system by providing capability for the non-invasive identification… (more)

Subjects/Keywords: brain imaging; white matter; MRI

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APA (6th Edition):

Karimi-Ashtiani, S. (2012). Theory and simulation of diffusion magnetic resonance imaging on brain's white matter. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/379286/rec/7424

Chicago Manual of Style (16th Edition):

Karimi-Ashtiani, Shahryar. “Theory and simulation of diffusion magnetic resonance imaging on brain's white matter.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/379286/rec/7424.

MLA Handbook (7th Edition):

Karimi-Ashtiani, Shahryar. “Theory and simulation of diffusion magnetic resonance imaging on brain's white matter.” 2012. Web. 17 Oct 2019.

Vancouver:

Karimi-Ashtiani S. Theory and simulation of diffusion magnetic resonance imaging on brain's white matter. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/379286/rec/7424.

Council of Science Editors:

Karimi-Ashtiani S. Theory and simulation of diffusion magnetic resonance imaging on brain's white matter. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/379286/rec/7424


University of Southern California

5. McCleary, Brent. Digital imaging system testing and design using physical sensor characteristics.

Degree: PhD, Electrical Engineering, 2009, University of Southern California

 Image sensor testing and image quality enhancement methods that are geared towards commercial CMOS image sensors are developed in this thesis. The methods utilize sensor… (more)

Subjects/Keywords: CMOS image sensors; cross-talk; PRNU; sensor characterization

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APA (6th Edition):

McCleary, B. (2009). Digital imaging system testing and design using physical sensor characteristics. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/600665/rec/1997

Chicago Manual of Style (16th Edition):

McCleary, Brent. “Digital imaging system testing and design using physical sensor characteristics.” 2009. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/600665/rec/1997.

MLA Handbook (7th Edition):

McCleary, Brent. “Digital imaging system testing and design using physical sensor characteristics.” 2009. Web. 17 Oct 2019.

Vancouver:

McCleary B. Digital imaging system testing and design using physical sensor characteristics. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/600665/rec/1997.

Council of Science Editors:

McCleary B. Digital imaging system testing and design using physical sensor characteristics. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/600665/rec/1997


University of Southern California

6. Lin, Yanguang. Model based PET image reconstruction and kinetic parameter estimation.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 Positron Emission Tomography (PET) is a powerful molecular imaging technique that can provide quantitative information about molecular processes in the living body. The system detects… (more)

Subjects/Keywords: signal processing; image processing; image reconstruction; medical imaging; tomography; PET

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APA (6th Edition):

Lin, Y. (2014). Model based PET image reconstruction and kinetic parameter estimation. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/454482/rec/4105

Chicago Manual of Style (16th Edition):

Lin, Yanguang. “Model based PET image reconstruction and kinetic parameter estimation.” 2014. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/454482/rec/4105.

MLA Handbook (7th Edition):

Lin, Yanguang. “Model based PET image reconstruction and kinetic parameter estimation.” 2014. Web. 17 Oct 2019.

Vancouver:

Lin Y. Model based PET image reconstruction and kinetic parameter estimation. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/454482/rec/4105.

Council of Science Editors:

Lin Y. Model based PET image reconstruction and kinetic parameter estimation. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/454482/rec/4105


University of Southern California

7. Dogdas, Belma. Image registration with applications to multimodal small animal imaging.

Degree: PhD, Electrical Engineering, 2009, University of Southern California

 Biomedical imaging technologies that were originally developed for human medical diagnosis have been adapted to study the anatomy and metabolism of small animals. However, multimodality… (more)

Subjects/Keywords: small animal imaging; image registration; mouse atlas; structured light; 3D surface profiling; skull and scalp segmentation

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APA (6th Edition):

Dogdas, B. (2009). Image registration with applications to multimodal small animal imaging. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/537232/rec/3346

Chicago Manual of Style (16th Edition):

Dogdas, Belma. “Image registration with applications to multimodal small animal imaging.” 2009. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/537232/rec/3346.

MLA Handbook (7th Edition):

Dogdas, Belma. “Image registration with applications to multimodal small animal imaging.” 2009. Web. 17 Oct 2019.

Vancouver:

Dogdas B. Image registration with applications to multimodal small animal imaging. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/537232/rec/3346.

Council of Science Editors:

Dogdas B. Image registration with applications to multimodal small animal imaging. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/537232/rec/3346


University of Southern California

8. Fan, Zihong. Interactive fast random access, retrieval, and navigation of large datasets.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 This research is motivated by two important trends. First, more than ever before large amounts of data and information are being accessed through mobile devices… (more)

Subjects/Keywords: fast random access; large datasets; interactive

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APA (6th Edition):

Fan, Z. (2011). Interactive fast random access, retrieval, and navigation of large datasets. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/651579/rec/3568

Chicago Manual of Style (16th Edition):

Fan, Zihong. “Interactive fast random access, retrieval, and navigation of large datasets.” 2011. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/651579/rec/3568.

MLA Handbook (7th Edition):

Fan, Zihong. “Interactive fast random access, retrieval, and navigation of large datasets.” 2011. Web. 17 Oct 2019.

Vancouver:

Fan Z. Interactive fast random access, retrieval, and navigation of large datasets. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/651579/rec/3568.

Council of Science Editors:

Fan Z. Interactive fast random access, retrieval, and navigation of large datasets. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/651579/rec/3568


University of Southern California

9. Aydore, Sergul. Measuring functional connectivity of the brain.

Degree: PhD, Electrical Engineering, 2015, University of Southern California

 The rich temporal content of measurements of electromagnetic activity, including electroencephalography (EEG) and magnetoencephalography (MEG), allow researchers to study dynamic functional networks in the human… (more)

Subjects/Keywords: functional connectivity; brain; EEG; MEG

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APA (6th Edition):

Aydore, S. (2015). Measuring functional connectivity of the brain. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/468390/rec/3989

Chicago Manual of Style (16th Edition):

Aydore, Sergul. “Measuring functional connectivity of the brain.” 2015. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/468390/rec/3989.

MLA Handbook (7th Edition):

Aydore, Sergul. “Measuring functional connectivity of the brain.” 2015. Web. 17 Oct 2019.

Vancouver:

Aydore S. Measuring functional connectivity of the brain. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/468390/rec/3989.

Council of Science Editors:

Aydore S. Measuring functional connectivity of the brain. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/468390/rec/3989


University of Southern California

10. Dutta, Joyita. Computational methods for fluorescence molecular tomography.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 Fluorescence molecular tomography is an imaging modality which exploits the specificity of fluorescent biomarkers to generate volumetric images using near-infrared light, which is safe and… (more)

Subjects/Keywords: cancer; fluorescence; imaging; near infrared; optical; tomography; preclinical

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APA (6th Edition):

Dutta, J. (2011). Computational methods for fluorescence molecular tomography. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445926/rec/1544

Chicago Manual of Style (16th Edition):

Dutta, Joyita. “Computational methods for fluorescence molecular tomography.” 2011. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445926/rec/1544.

MLA Handbook (7th Edition):

Dutta, Joyita. “Computational methods for fluorescence molecular tomography.” 2011. Web. 17 Oct 2019.

Vancouver:

Dutta J. Computational methods for fluorescence molecular tomography. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445926/rec/1544.

Council of Science Editors:

Dutta J. Computational methods for fluorescence molecular tomography. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445926/rec/1544


University of Southern California

11. Noronha, Sanjay P. 3-D building detection and description from multiple intensity images using hierarchical grouping and matching of features.

Degree: PhD, Computer Science, 2013, University of Southern California

 A method for detection and description of rectangular buildings with flat and with gable roofs from two or more registered aerial intensity images is proposed.… (more)

Subjects/Keywords: computer vision; automated building detection

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APA (6th Edition):

Noronha, S. P. (2013). 3-D building detection and description from multiple intensity images using hierarchical grouping and matching of features. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/218764/rec/16

Chicago Manual of Style (16th Edition):

Noronha, Sanjay P. “3-D building detection and description from multiple intensity images using hierarchical grouping and matching of features.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/218764/rec/16.

MLA Handbook (7th Edition):

Noronha, Sanjay P. “3-D building detection and description from multiple intensity images using hierarchical grouping and matching of features.” 2013. Web. 17 Oct 2019.

Vancouver:

Noronha SP. 3-D building detection and description from multiple intensity images using hierarchical grouping and matching of features. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/218764/rec/16.

Council of Science Editors:

Noronha SP. 3-D building detection and description from multiple intensity images using hierarchical grouping and matching of features. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/218764/rec/16


University of Southern California

12. Thaipanich, Tanaphol. Image and video enhancement through motion based interpolation and nonlocal-means denoising techniques.

Degree: PhD, Electrical Engineering, 2010, University of Southern California

 In this research, we investigate advanced image and video enhancement techniques based on motion based interpolation and nonlocal-means (NL-means) denoising. The dissertation consists of three… (more)

Subjects/Keywords: adaptive nonlocal-means; frame rate up-conversion; image denoising; motion based interpolation; video error concealment

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APA (6th Edition):

Thaipanich, T. (2010). Image and video enhancement through motion based interpolation and nonlocal-means denoising techniques. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/293950/rec/3344

Chicago Manual of Style (16th Edition):

Thaipanich, Tanaphol. “Image and video enhancement through motion based interpolation and nonlocal-means denoising techniques.” 2010. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/293950/rec/3344.

MLA Handbook (7th Edition):

Thaipanich, Tanaphol. “Image and video enhancement through motion based interpolation and nonlocal-means denoising techniques.” 2010. Web. 17 Oct 2019.

Vancouver:

Thaipanich T. Image and video enhancement through motion based interpolation and nonlocal-means denoising techniques. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/293950/rec/3344.

Council of Science Editors:

Thaipanich T. Image and video enhancement through motion based interpolation and nonlocal-means denoising techniques. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/293950/rec/3344


University of Southern California

13. Chang, Yu-Teng. Network structures: graph theory, statistics, and neuroscience applications.

Degree: PhD, Electrical Engineering, 2012, University of Southern California

 Network modeling and graph theory have been widely studied and applied in a variety of modern research areas. The detection of network structures in these… (more)

Subjects/Keywords: brain connectome; graph theory; modularity; network structures; random matrix theory; statistical significance

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APA (6th Edition):

Chang, Y. (2012). Network structures: graph theory, statistics, and neuroscience applications. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/39102/rec/4361

Chicago Manual of Style (16th Edition):

Chang, Yu-Teng. “Network structures: graph theory, statistics, and neuroscience applications.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/39102/rec/4361.

MLA Handbook (7th Edition):

Chang, Yu-Teng. “Network structures: graph theory, statistics, and neuroscience applications.” 2012. Web. 17 Oct 2019.

Vancouver:

Chang Y. Network structures: graph theory, statistics, and neuroscience applications. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/39102/rec/4361.

Council of Science Editors:

Chang Y. Network structures: graph theory, statistics, and neuroscience applications. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/39102/rec/4361


University of Southern California

14. Kuo, Cheng-Hao. Multiple pedestrians tracking by discriminative models.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 We present our work on multiple pedestrians tracking in a single camera and across multiple non-overlapping cameras. We propose an approach for online learning of… (more)

Subjects/Keywords: adaboost; association-based tracking; detection-based tracking; discriminative models; multiple instance learning; mutli-target tracking

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APA (6th Edition):

Kuo, C. (2011). Multiple pedestrians tracking by discriminative models. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/671069/rec/4275

Chicago Manual of Style (16th Edition):

Kuo, Cheng-Hao. “Multiple pedestrians tracking by discriminative models.” 2011. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/671069/rec/4275.

MLA Handbook (7th Edition):

Kuo, Cheng-Hao. “Multiple pedestrians tracking by discriminative models.” 2011. Web. 17 Oct 2019.

Vancouver:

Kuo C. Multiple pedestrians tracking by discriminative models. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/671069/rec/4275.

Council of Science Editors:

Kuo C. Multiple pedestrians tracking by discriminative models. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/671069/rec/4275


University of Southern California

15. Hui, Hua Brian. Signal processing methods for interaction analysis of functional brain imaging data.

Degree: PhD, Electrical Engineering, 2010, University of Southern California

 Modeling functional brain interaction networks using non-invasive EEG and MEG data is more challenging than using intracranial recordings data. This is because most interaction measures… (more)

Subjects/Keywords: beamformer; cross-talk; functional interaction; intracranial EEG; MEG; phase synchrony

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APA (6th Edition):

Hui, H. B. (2010). Signal processing methods for interaction analysis of functional brain imaging data. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/292402/rec/5844

Chicago Manual of Style (16th Edition):

Hui, Hua Brian. “Signal processing methods for interaction analysis of functional brain imaging data.” 2010. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/292402/rec/5844.

MLA Handbook (7th Edition):

Hui, Hua Brian. “Signal processing methods for interaction analysis of functional brain imaging data.” 2010. Web. 17 Oct 2019.

Vancouver:

Hui HB. Signal processing methods for interaction analysis of functional brain imaging data. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/292402/rec/5844.

Council of Science Editors:

Hui HB. Signal processing methods for interaction analysis of functional brain imaging data. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/292402/rec/5844


University of Southern California

16. Lin, Yenting. Transmission tomography for high contrast media based on sparse data.

Degree: PhD, Electrical Engineering, 2013, University of Southern California

 Transmission tomography is a powerful tool to image the interior structure based on measured data on the boundary. It provides a "non-destructive" imaging and widely… (more)

Subjects/Keywords: tomography; high contrast; sparse data

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APA (6th Edition):

Lin, Y. (2013). Transmission tomography for high contrast media based on sparse data. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/315223/rec/7584

Chicago Manual of Style (16th Edition):

Lin, Yenting. “Transmission tomography for high contrast media based on sparse data.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/315223/rec/7584.

MLA Handbook (7th Edition):

Lin, Yenting. “Transmission tomography for high contrast media based on sparse data.” 2013. Web. 17 Oct 2019.

Vancouver:

Lin Y. Transmission tomography for high contrast media based on sparse data. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/315223/rec/7584.

Council of Science Editors:

Lin Y. Transmission tomography for high contrast media based on sparse data. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/315223/rec/7584


University of Southern California

17. Wheland, David Stanford. Signal processing methods for brain connectivity.

Degree: PhD, Electrical Engineering, 2013, University of Southern California

 Although the human brain has been studied for centuries, and the advent of non-invasive brain imaging modalities in the last century in particular has led… (more)

Subjects/Keywords: connectivity; network; brain; neuroimaging; sparsity; graphical model; multivariate autoregressive model; coherence; Granger causality; partial correlation; blind source separation; independent component analysis; gray matter thickness; cortical curvature; fMRI; MRI; EEG

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APA (6th Edition):

Wheland, D. S. (2013). Signal processing methods for brain connectivity. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/328335/rec/5843

Chicago Manual of Style (16th Edition):

Wheland, David Stanford. “Signal processing methods for brain connectivity.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/328335/rec/5843.

MLA Handbook (7th Edition):

Wheland, David Stanford. “Signal processing methods for brain connectivity.” 2013. Web. 17 Oct 2019.

Vancouver:

Wheland DS. Signal processing methods for brain connectivity. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/328335/rec/5843.

Council of Science Editors:

Wheland DS. Signal processing methods for brain connectivity. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/328335/rec/5843


University of Southern California

18. Poletti Soto, Juan Luis. Multivariate statistical analysis of magnetoencephalography data.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 I describe methods for the detection of brain activation and functional connectivity in cortically constrained maps of current density computed from magnetoencephalography (MEG) data using… (more)

Subjects/Keywords: functional connectivity; magnetoencephalography (MEG); multivariate statistics; oscillatory brain activity

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APA (6th Edition):

Poletti Soto, J. L. (2011). Multivariate statistical analysis of magnetoencephalography data. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/427403/rec/4282

Chicago Manual of Style (16th Edition):

Poletti Soto, Juan Luis. “Multivariate statistical analysis of magnetoencephalography data.” 2011. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/427403/rec/4282.

MLA Handbook (7th Edition):

Poletti Soto, Juan Luis. “Multivariate statistical analysis of magnetoencephalography data.” 2011. Web. 17 Oct 2019.

Vancouver:

Poletti Soto JL. Multivariate statistical analysis of magnetoencephalography data. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/427403/rec/4282.

Council of Science Editors:

Poletti Soto JL. Multivariate statistical analysis of magnetoencephalography data. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/427403/rec/4282


University of Southern California

19. Cho, Sang Hee. Fast iterative image reconstruction for 3D PET and its extension to time-of-flight PET.

Degree: PhD, Electrical Engineering, 2009, University of Southern California

 Positron emission tomography (PET) is a functional biomedical imaging technique that provides in vivo information about physiological processes within the body by reconstructing the 3D… (more)

Subjects/Keywords: Fourier rebinning; fully 3D PET; inverse rebinning; iterative reconstruction; time-of-flight PET

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APA (6th Edition):

Cho, S. H. (2009). Fast iterative image reconstruction for 3D PET and its extension to time-of-flight PET. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/117793/rec/2769

Chicago Manual of Style (16th Edition):

Cho, Sang Hee. “Fast iterative image reconstruction for 3D PET and its extension to time-of-flight PET.” 2009. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/117793/rec/2769.

MLA Handbook (7th Edition):

Cho, Sang Hee. “Fast iterative image reconstruction for 3D PET and its extension to time-of-flight PET.” 2009. Web. 17 Oct 2019.

Vancouver:

Cho SH. Fast iterative image reconstruction for 3D PET and its extension to time-of-flight PET. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/117793/rec/2769.

Council of Science Editors:

Cho SH. Fast iterative image reconstruction for 3D PET and its extension to time-of-flight PET. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/117793/rec/2769


University of Southern California

20. Files, Benjamin Taylor. Selectivity for visual speech in posterior temporal cortex.

Degree: PhD, Neuroscience, 2013, University of Southern California

 Visual speech perception, also known as lipreading or speech reading, involves extracting linguistic information from seeing a talking face. What information is available in a… (more)

Subjects/Keywords: lipreading; visual speech perception; behavior; discrimination; electroencephalography; visual speech mismatch negativity

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APA (6th Edition):

Files, B. T. (2013). Selectivity for visual speech in posterior temporal cortex. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340643/rec/5762

Chicago Manual of Style (16th Edition):

Files, Benjamin Taylor. “Selectivity for visual speech in posterior temporal cortex.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340643/rec/5762.

MLA Handbook (7th Edition):

Files, Benjamin Taylor. “Selectivity for visual speech in posterior temporal cortex.” 2013. Web. 17 Oct 2019.

Vancouver:

Files BT. Selectivity for visual speech in posterior temporal cortex. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340643/rec/5762.

Council of Science Editors:

Files BT. Selectivity for visual speech in posterior temporal cortex. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340643/rec/5762


University of Southern California

21. Wong, Chi Wah (Alec). Diffusion MRI white matter tractography: estimation of multiple fibers per voxel using independent component analysis.

Degree: PhD, Biomedical Engineering, 2009, University of Southern California

 Brownian motion is a phenomenon describing the random movement of particles. Water molecules, the most abundant particle inside the body, diffuse in all directions with… (more)

Subjects/Keywords: diffusion MRI; magnetic resonance imaging; diffusion tensor imaging; independent componenet analysis; tractography; multiple fibers; fiber crossing

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APA (6th Edition):

Wong, C. W. (. (2009). Diffusion MRI white matter tractography: estimation of multiple fibers per voxel using independent component analysis. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406386/rec/1992

Chicago Manual of Style (16th Edition):

Wong, Chi Wah (Alec). “Diffusion MRI white matter tractography: estimation of multiple fibers per voxel using independent component analysis.” 2009. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406386/rec/1992.

MLA Handbook (7th Edition):

Wong, Chi Wah (Alec). “Diffusion MRI white matter tractography: estimation of multiple fibers per voxel using independent component analysis.” 2009. Web. 17 Oct 2019.

Vancouver:

Wong CW(. Diffusion MRI white matter tractography: estimation of multiple fibers per voxel using independent component analysis. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406386/rec/1992.

Council of Science Editors:

Wong CW(. Diffusion MRI white matter tractography: estimation of multiple fibers per voxel using independent component analysis. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/406386/rec/1992


University of Southern California

22. Wilkins, Bryce. Diffusion MRI of the human brain: signal modeling and quantitative analysis.

Degree: PhD, Biomedical Engineering, 2014, University of Southern California

 Diffusion-weighted magnetic resonance imaging (DW-MRI) and specific applications such as diffusion tensor imaging (DTI) are uniquely capable of revealing the human brain's complex white-matter structure.… (more)

Subjects/Keywords: diffusion; magnetic resonance imaging; diffusion analysis methods; human brain imaging; white matter structure

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APA (6th Edition):

Wilkins, B. (2014). Diffusion MRI of the human brain: signal modeling and quantitative analysis. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/514770/rec/1991

Chicago Manual of Style (16th Edition):

Wilkins, Bryce. “Diffusion MRI of the human brain: signal modeling and quantitative analysis.” 2014. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/514770/rec/1991.

MLA Handbook (7th Edition):

Wilkins, Bryce. “Diffusion MRI of the human brain: signal modeling and quantitative analysis.” 2014. Web. 17 Oct 2019.

Vancouver:

Wilkins B. Diffusion MRI of the human brain: signal modeling and quantitative analysis. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/514770/rec/1991.

Council of Science Editors:

Wilkins B. Diffusion MRI of the human brain: signal modeling and quantitative analysis. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/514770/rec/1991


University of Southern California

23. Ashrafulla, Syed. Causality and consistency in electrophysiological signals.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 Model‐based approaches to electrophysiological signal processing provide low‐variance estimates of the activity and relationships within neurological systems. In this dissertation, we develop a method for… (more)

Subjects/Keywords: signal processing; correlation; causality; autoregression; conditional heteroscedasticity; brain; electroencephalography; magnetoencephalography; electrophysiology

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APA (6th Edition):

Ashrafulla, S. (2014). Causality and consistency in electrophysiological signals. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256

Chicago Manual of Style (16th Edition):

Ashrafulla, Syed. “Causality and consistency in electrophysiological signals.” 2014. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256.

MLA Handbook (7th Edition):

Ashrafulla, Syed. “Causality and consistency in electrophysiological signals.” 2014. Web. 17 Oct 2019.

Vancouver:

Ashrafulla S. Causality and consistency in electrophysiological signals. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256.

Council of Science Editors:

Ashrafulla S. Causality and consistency in electrophysiological signals. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/366875/rec/1256


University of Southern California

24. Chaudhari, Abhijit J. Hyperspectral and multispectral optical bioluminescence and fluorescence tomography in small animal imaging.

Degree: PhD, Electrical engineering, 2007, University of Southern California

 For bioluminescence and fluorescence imaging studies in small animals, it is important to be able to accurately estimate the 3D distribution of a light-emitting source… (more)

Subjects/Keywords: hyperspectral; mutispectral; bioluminescence; fluorescence; tomography; small animal imaging

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APA (6th Edition):

Chaudhari, A. J. (2007). Hyperspectral and multispectral optical bioluminescence and fluorescence tomography in small animal imaging. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/158799/rec/3297

Chicago Manual of Style (16th Edition):

Chaudhari, Abhijit J. “Hyperspectral and multispectral optical bioluminescence and fluorescence tomography in small animal imaging.” 2007. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/158799/rec/3297.

MLA Handbook (7th Edition):

Chaudhari, Abhijit J. “Hyperspectral and multispectral optical bioluminescence and fluorescence tomography in small animal imaging.” 2007. Web. 17 Oct 2019.

Vancouver:

Chaudhari AJ. Hyperspectral and multispectral optical bioluminescence and fluorescence tomography in small animal imaging. [Internet] [Doctoral dissertation]. University of Southern California; 2007. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/158799/rec/3297.

Council of Science Editors:

Chaudhari AJ. Hyperspectral and multispectral optical bioluminescence and fluorescence tomography in small animal imaging. [Doctoral Dissertation]. University of Southern California; 2007. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/158799/rec/3297


University of Southern California

25. Pantazis, Dimitrios. Statistical signal processing of magnetoencephalography data.

Degree: PhD, Electrical Engineering, 2006, University of Southern California

 Imaging approaches in MEG typically generate dynamic current density maps (CDMs) on the cortical surface, where the activation in each location is represented by a… (more)

Subjects/Keywords: magnetoencephalography; permutations

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APA (6th Edition):

Pantazis, D. (2006). Statistical signal processing of magnetoencephalography data. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/28405/rec/6047

Chicago Manual of Style (16th Edition):

Pantazis, Dimitrios. “Statistical signal processing of magnetoencephalography data.” 2006. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/28405/rec/6047.

MLA Handbook (7th Edition):

Pantazis, Dimitrios. “Statistical signal processing of magnetoencephalography data.” 2006. Web. 17 Oct 2019.

Vancouver:

Pantazis D. Statistical signal processing of magnetoencephalography data. [Internet] [Doctoral dissertation]. University of Southern California; 2006. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/28405/rec/6047.

Council of Science Editors:

Pantazis D. Statistical signal processing of magnetoencephalography data. [Doctoral Dissertation]. University of Southern California; 2006. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/28405/rec/6047


University of Southern California

26. Lee, Hsu-Lei. Wideband steady-state free precession for cardiac MRI.

Degree: PhD, Electrical Engineering, 2008, University of Southern California

 Balanced steady-state free precession (SSFP) is an MRI pulse sequence that is widely used for cardiac imaging, because it provides superior SNR and excellent blood-myocardium… (more)

Subjects/Keywords: alternating repetition times; coronary artery imaging; initial preparation; LV function; steady-state free precession; wideband SSFP

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APA (6th Edition):

Lee, H. (2008). Wideband steady-state free precession for cardiac MRI. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/131278/rec/7933

Chicago Manual of Style (16th Edition):

Lee, Hsu-Lei. “Wideband steady-state free precession for cardiac MRI.” 2008. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/131278/rec/7933.

MLA Handbook (7th Edition):

Lee, Hsu-Lei. “Wideband steady-state free precession for cardiac MRI.” 2008. Web. 17 Oct 2019.

Vancouver:

Lee H. Wideband steady-state free precession for cardiac MRI. [Internet] [Doctoral dissertation]. University of Southern California; 2008. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/131278/rec/7933.

Council of Science Editors:

Lee H. Wideband steady-state free precession for cardiac MRI. [Doctoral Dissertation]. University of Southern California; 2008. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/131278/rec/7933


University of Southern California

27. Joshi, Anand Arvind. Geometric methods of image registration and analysis.

Degree: PhD, Electrical Engineering, 2008, University of Southern California

 Registration and analysis of neuro-imaging data presents a challenging problem due to the complex folding patterns in the human brain. Specifically, the cortical surface of… (more)

Subjects/Keywords: brain image registration; harmonic maps; PDE based

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APA (6th Edition):

Joshi, A. A. (2008). Geometric methods of image registration and analysis. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/91929/rec/3029

Chicago Manual of Style (16th Edition):

Joshi, Anand Arvind. “Geometric methods of image registration and analysis.” 2008. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/91929/rec/3029.

MLA Handbook (7th Edition):

Joshi, Anand Arvind. “Geometric methods of image registration and analysis.” 2008. Web. 17 Oct 2019.

Vancouver:

Joshi AA. Geometric methods of image registration and analysis. [Internet] [Doctoral dissertation]. University of Southern California; 2008. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/91929/rec/3029.

Council of Science Editors:

Joshi AA. Geometric methods of image registration and analysis. [Doctoral Dissertation]. University of Southern California; 2008. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/91929/rec/3029


University of Southern California

28. Yang, Hua. Prediction modeling and statistical analysis of amino acid substitutions.

Degree: PhD, Electrical Engineering, 2006, University of Southern California

 Classifying and predicting amino acid substitutions are important in pharmaceutical and pathological research. We proposed a novel feature set from amino acids' physicochemical properties, evolutionary… (more)

Subjects/Keywords: machine learning; data processing; classification; prediction model; statistical analysis; simulated annealing bump hunting strategy; Monte-Carlo simulation with variable temperature; predicting

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APA (6th Edition):

Yang, H. (2006). Prediction modeling and statistical analysis of amino acid substitutions. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/21662/rec/5181

Chicago Manual of Style (16th Edition):

Yang, Hua. “Prediction modeling and statistical analysis of amino acid substitutions.” 2006. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/21662/rec/5181.

MLA Handbook (7th Edition):

Yang, Hua. “Prediction modeling and statistical analysis of amino acid substitutions.” 2006. Web. 17 Oct 2019.

Vancouver:

Yang H. Prediction modeling and statistical analysis of amino acid substitutions. [Internet] [Doctoral dissertation]. University of Southern California; 2006. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/21662/rec/5181.

Council of Science Editors:

Yang H. Prediction modeling and statistical analysis of amino acid substitutions. [Doctoral Dissertation]. University of Southern California; 2006. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/21662/rec/5181


University of Southern California

29. de Carvalho, Joao Luiz Azevedo. Velocity-encoded magnetic resonance imaging: acquisition, reconstruction and applications.

Degree: PhD, Electrical Engineering, 2008, University of Southern California

 Cardiovascular disease is the leading cause of death and disability in the United States. An important component of the assessment of cardiovascular disease is the… (more)

Subjects/Keywords: FVE; Fourier velocity encoding; MRI flow imaging; aortic stenosis; aortic regurgitation; wall shear stress; carotid artery disease

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APA (6th Edition):

de Carvalho, J. L. A. (2008). Velocity-encoded magnetic resonance imaging: acquisition, reconstruction and applications. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/78563/rec/7810

Chicago Manual of Style (16th Edition):

de Carvalho, Joao Luiz Azevedo. “Velocity-encoded magnetic resonance imaging: acquisition, reconstruction and applications.” 2008. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/78563/rec/7810.

MLA Handbook (7th Edition):

de Carvalho, Joao Luiz Azevedo. “Velocity-encoded magnetic resonance imaging: acquisition, reconstruction and applications.” 2008. Web. 17 Oct 2019.

Vancouver:

de Carvalho JLA. Velocity-encoded magnetic resonance imaging: acquisition, reconstruction and applications. [Internet] [Doctoral dissertation]. University of Southern California; 2008. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/78563/rec/7810.

Council of Science Editors:

de Carvalho JLA. Velocity-encoded magnetic resonance imaging: acquisition, reconstruction and applications. [Doctoral Dissertation]. University of Southern California; 2008. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/78563/rec/7810


University of Southern California

30. Sung, Kyunghyun. Radio-frequency non-uniformity in cardiac magnetic resonance imaging.

Degree: PhD, Electrical Engineering, 2008, University of Southern California

 Cardiovascular magnetic resonance imaging (MRI) is now routinely used for evaluating cardiac function, and myocardial viability. Due to its unique exibility, MRI has the potential… (more)

Subjects/Keywords: magnetic resonance imaging; cardiac imaging; high field imaging; B1+ inhomogeneity

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APA (6th Edition):

Sung, K. (2008). Radio-frequency non-uniformity in cardiac magnetic resonance imaging. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/90505/rec/5387

Chicago Manual of Style (16th Edition):

Sung, Kyunghyun. “Radio-frequency non-uniformity in cardiac magnetic resonance imaging.” 2008. Doctoral Dissertation, University of Southern California. Accessed October 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/90505/rec/5387.

MLA Handbook (7th Edition):

Sung, Kyunghyun. “Radio-frequency non-uniformity in cardiac magnetic resonance imaging.” 2008. Web. 17 Oct 2019.

Vancouver:

Sung K. Radio-frequency non-uniformity in cardiac magnetic resonance imaging. [Internet] [Doctoral dissertation]. University of Southern California; 2008. [cited 2019 Oct 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/90505/rec/5387.

Council of Science Editors:

Sung K. Radio-frequency non-uniformity in cardiac magnetic resonance imaging. [Doctoral Dissertation]. University of Southern California; 2008. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/90505/rec/5387

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