Item Details

title

COMPRESSIVE SENSING BASED IMAGE RECONSTRUCTION FOR COMPUTED TOMOGRAPHY DOSE REDUCTION

author

Miao, Chuang

abstract

Excessive radiation exposure is one of the major concerns in the computed tomography (CT) field. Few-view reconstruction using iterative algorithm is an important strategy to reduce the radiation dose. In the iterative CT reconstruction, the projection / backprojection model plays an important role in the overall computational cost, image quality, and reconstruction accuracy. In this dissertation, we first propose an improved distance-driven model (IDDM) whose computational cost is as low as the well-known distance-driven model (DDM) and the accuracy is comparable to the accurate area integral model (AIM). Recently, the Lp (0

subject

Compress Sensing

Computed Tomography

Medical Imaging

Non-convex optimization

Reconstruction

contributor

Yu, Hengyong (committee chair)

Wang, Ge (committee member)

Cao, Guohua (committee member)

Plemmons, Robert J. (committee member)

Li, King C. (committee member)

date

2015-08-25T08:35:26Z (accessioned)

2015-08-25T08:35:26Z (available)

2015 (issued)

degree

Biomedical Engineering (discipline)

identifier

http://hdl.handle.net/10339/57252 (uri)

language

en (iso)

publisher

Wake Forest University

type

Dissertation