Linked Life Data

12557530

Source:http://linkedlifedata.com/resource/pubmed/id/12557530

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2003-1-31
pubmed:abstractText
This paper describes the state and the development of the application of the modern and traditional image segmentation technology in cell slice image segmentation. It includes edge detection, regional segmentation, wavelet transform, fuzzy mathematics, artificial neural networks, morphological image segmentation and so on. At last, the paper summaries that it is difficult to generally segmentate any kind of biological cell slice image automatically because of the complex structure of cell and cell slice image is not even gray distributed. It should be pointed out that general automatic cell slice image segmentation will be achieved only if visual mathematics model corresponding to mammalian vision systems is setup entirely.
pubmed:language
chi
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1001-5515
pubmed:author
pubmed:issnType
Print
pubmed:volume
19
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
487-92
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
[The state and development of cell image segmentation technology].
pubmed:affiliation
State Key Laboratory of Arid Agroecology, School of Information Science & Engineering of Lanzhou University, Lanzhou 730000.
pubmed:publicationType
Journal Article, English Abstract, Review, Research Support, Non-U.S. Gov't