Linked Life Data

11679208

Source:http://linkedlifedata.com/resource/pubmed/id/11679208

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2001-10-26
pubmed:abstractText
Orthogonal subspace projection (OSP) approach has shown success in hyperspectral image classification. Recently, the feasibility of applying OSP to multispectral image classification was also demonstrated via SPOT (Satellite Pour 1'Observation de la Terra) and Landsat (Land Satellite) images. Since an MR (magnetic resonance) image sequence is also acquired by multiple spectral channels (bands), this paper presents a new application of OSP in MR image classification. The idea is to model an MR image pixel in the sequence as a linear mixture of substances (such as white matter, gray matter, cerebral spinal fluid) of interest from which each of these substances can be classified by a specific subspace projection operator followed by a desired matched filter. The experimental results show that OSP provides a promising alternative to existing MR image classification techniques.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0895-6111
pubmed:author
pubmed:issnType
Print
pubmed:volume
25
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
465-76
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:articleTitle
Orthogonal subspace projection-based approaches to classification of MR image sequences.
pubmed:affiliation
Department of Electrical Engineering, National Cheng Kung University, 1 University Road, Tainan, Taiwan.
pubmed:publicationType
Journal Article