Linked Life Data

19963739

Source:http://linkedlifedata.com/resource/pubmed/id/19963739

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-12-7
pubmed:abstractText
Metallic implants may cause severe artifacts in CT exams. Suppression of metal artifacts remains to be a very challenging problem, in which metal region segmentation is one of the most important steps. We proposed a novel, semiautomatic segmentation algorithm based on the dual-front active contour model and the boundary mapping strategy to detect the metal regions on reformatted projection data, and to effectively eliminate/suppress metal artifacts on reconstructed images. Experimental studies on clinical hip and shoulder CT exams demonstrated that the proposed method was able to segment multiple metal implants more accurately relative to threshold-based methods. The artifacts caused by dense metal implants were better suppressed.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1557-170X
pubmed:author
pubmed:issnType
Print
pubmed:volume
2009
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
993-6
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Metal artifact suppression from reformatted projections in multi-slice helical CT using dual-front active contours.
pubmed:affiliation
Department of Radiology, Mayo Clinic, Rochester, MN 55901, USA. li.hua@mayo.edu
pubmed:publicationType
Journal Article, Evaluation Studies