Linked Life Data

21668958

Source:http://linkedlifedata.com/resource/pubmed/id/21668958

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2011-7-19
pubmed:abstractText
Image segmentation is a crucial step in quantitative microscopy that helps to define regions of tissues, cells or subcellular compartments. Depending on the degree of user interactions, segmentation methods can be divided into manual, automated or semi-automated approaches. 3D image stacks usually require automated methods due to their large number of optical sections. However, certain applications benefit from manual or semi-automated approaches. Scenarios include the quantification of 3D images with poor signal-to-noise ratios or the generation of so-called ground truth segmentations that are used to evaluate the accuracy of automated segmentation methods.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1471-2105
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
232
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3D segmentation algorithms.
pubmed:affiliation
Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk
pubmed:publicationType
Journal Article