Linked Life Data

17590502

Source:http://linkedlifedata.com/resource/pubmed/id/17590502

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2007-9-28
pubmed:abstractText
To ensure the delineated boundaries of a series of 2-D images closely following the visually perceivable edges with high boundary coherence between consecutive slices, a cell-based two-region competition algorithm based on a maximum a posteriori (MAP) framework is proposed. It deforms the region boundary in a cell-by-cell fashion through a cell-based two-region competition process. The cell-based deformation is guided by a cell-based MAP framework with a posterior function characterizing the distribution of the cell means in each region, the salience and shape complexity of the region boundary and the boundary coherence of the consecutive slices. The proposed algorithm has been validated using 10 series of breast sonograms, including seven compression series and three freehand series. The compression series contains two carcinoma and five fibroadenoma cases and the freehand series contains two carcinoma and one fibroadenoma cases. The results show that >70% of the derived boundaries fall within the span of the manually delineated boundaries. The robustness of the proposed algorithm to the variation of regions-of-interest is confirmed by the Friedman tests and the p-values of which are 0.517 and 0.352 for the compression and freehand series groups, respectively. The Pearson's correlations between the lesion sizes derived by the proposed algorithm and those defined by the average manually delineated boundaries are all higher than 0.990. The overlapping and difference ratios between the derived boundaries and the average manually delineated boundaries are mostly higher than 0.90 and lower than 0.13, respectively. For both series groups, all assessments conclude that the boundaries derived by the proposed algorithm be comparable to those delineated manually. Moreover, it is shown that the proposed algorithm is superior to the Chan and Vese level set method based on the paired-sample t-tests on the performance indices at a 5% significance level.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0301-5629
pubmed:author
pubmed:issnType
Print
pubmed:volume
33
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1640-50
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Cell-based two-region competition algorithm with a map framework for boundary delineation of a series of 2D ultrasound images.
pubmed:affiliation
Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't