Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
1987-12-1
pubmed:abstractText
Magnetic resonance imaging data is conventionally reconstructed using two dimensional discrete Fourier transforms. However, there is growing interest in other types of spectral estimation which minimize noise and artifacts due to truncated data. This note presents preliminary results--showing the improvement obtainable using a modified autoregressive model, the Transient Error method.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0730-725X
pubmed:author
pubmed:issnType
Print
pubmed:volume
4
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
257-61
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1986
pubmed:articleTitle
Application of autoregressive modelling in magnetic resonance imaging to remove noise and truncation artifacts.
pubmed:affiliation
Department of Electrical Engineering, University of Calgary, Alberta, Canada.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't