Linked Life Data

17399764

Source:http://linkedlifedata.com/resource/pubmed/id/17399764

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2007-5-28
pubmed:abstractText
A procedure for the semi-automatic identification of the main protozoa and metazoa species present in the activated sludge of wastewater treatment plants was developed. This procedure was based on both image processing and multivariable statistical methodologies, leading to the use of the image analysis morphological descriptors by discriminant analysis and neural network techniques. The image analysis program written in Matlab has proved to be adequate in terms of protozoa and metazoa recognition, as well as for the operating conditions assessment.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0043-1354
pubmed:author
pubmed:issnType
Print
pubmed:volume
41
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2581-9
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Development of an image analysis procedure for identifying protozoa and metazoa typical of activated sludge system.
pubmed:affiliation
Departamento de Engenharia Bio química, Escola de Química/UFRJ, Centro de Tecnologia, E-113, Cidade Universitária, Ilha do Fundão, Rio de Janeiro, CEP: 21941-900, Brazil. yovanka.perez@gmail.com
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't