Reduced-Encoding Dynamic Imaging

Several techniques are proposed in this dissertation to improve the basis functions of the GS model by introducing dynamic information. The two-reference reduced-encoding imaging by generalized-series reconstruction (TRIGR) method suppresses background information through the use of a second high-resolution reference image. A second technique injects information from the dynamic data into the GS basis functions, as opposed to deriving them solely from the reference information. These techniques allow the GS basis functions to more accurately represent the areas of dynamic change. Finally, motion that occurs between the acquisition of the reference and dynamic data sets can render the reference information useless as a constraint for image reconstruction. A motion compensation method is proposed which uses a similarity norm to accurately detect the motion in spite of contrast changes and the low-resolution nature of the dynamic data.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Hanson, Jill Marie

Contributors dc:contributor

• Liang, Zhi-Pei
• Lauterbur, Paul C.

• Engineering, Biomedical

Language dc:language

eng

Identifier

(MiAaPQ)AAI9737126

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81182