Zoom Meeting (Information posted at the end of the announcement)
Statistical Analysis of Ultrasound Signals for Tissue Characterization: The Homodyned K Distribution
Diagnostic ultrasound (US) is a safe and inexpensive imaging technology, but it is mostly useful for qualitative assessment of anatomic features that are much larger than a wavelength, at least several millimeters in size. Statistical analysis of US envelope signals can provide information about scattering from structures that are smaller than a wavelength, and can therefore provide information on tissue composition and organization that would otherwise require a biopsy. The Homodyned K (HK) distribution is the most general in the family of random walk envelope distributions, which are strongly grounded in a physical modeling of scattering and therefore are ideal for tissue characterization purposes. In this thesis, several issues are considered that relate to the implementation and interpretation of the HK distribution. The physical interpretations of the HK parameters are explored, providing greater context and understanding for clinical applications. A novel parameter estimation algorithm based on the Levenberg-Marquardt curve-fitting algorithm is presented, and it is shown to be more robust in the presence of image artifacts than the gold standard. The effects of a single-element US imaging system on HK parameters are characterized, enabling calibration and therefore system-independent measurements. Finally, two animal studies are presented that use HK parameters to characterize skeletal muscle and liver in mouse models. These results represent progress towards implementing the HK distribution as a system-independent, clinically useful analysis technique.
Thesis Supervisor:
Brian W. Anthony, PhD
Principal Research Scientist, Department of Mechanical Engineering, MIT
Thesis Committee Chair:
Henrik Schmidt, PhD
Professor of Mechanical and Ocean Engineering, MIT
Thesis Readers:
Kai E. Thomenius, PhD
Research Scientist, Institute for Medical Engineering and Science, MIT
Seward B. Rutkove, MD
Professor of Neurobiology, HMS
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Zoom information
Topic: Anne Pigula Tresansky: MEMP PhD Thesis Defense
Time: July 20, 2020 02:30 PM Eastern Time (US and Canada)
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