Abstract
Medical image reconstruction is fraught with problems that are a result of noisy and incomplete data. The incomplete data give rise to null functions that are associated with the imaging operator, thus yielding an infinite number of solutions that fit the data equally well. Noise in the data often will lead to very rough reconstructions, which can be inconsistent with previous experience. The use of prior information can sometimes be introduced to help alleviate the aforementioned problems. If one knows that an object (or class of objects) possesses certain characteristics, then the reconstructions should possess the same characteristics.
© 1989 Optical Society of America
PDF ArticleMore Like This
Murielle Torregrossa, C. Virginie Zint, and Patrick Poulet
5143_29 European Conference on Biomedical Optics (ECBO) 2003
M. Xu, W. Cai, M. Lax, and R. R. Alfano
SuB7 Biomedical Topical Meeting (BIOMED) 2002
Chin-Tu Chen, Valen E. Johnson, Wing H. Wong, Xiaoping Hub, and Charles E. Metz
WD1 Signal Recovery and Synthesis (SRS) 1989