Linked Life Data

18072481

Source:http://linkedlifedata.com/resource/pubmed/id/18072481

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2007-12-12
pubmed:abstractText
The interpretation of medical images by radiologists is primarily and fundamentally a subjective activity, but there are a number of clinical applications such as tumor imaging where quantitative imaging (QI) metrics (such as tumor growth rate) would be valuable to the patient's care. It is predicted that the subjective interpretive environment of the past will, over the next decade, evolve toward the increased use of quantitative metrics for evaluating patient health from images. The increasing sophistication and resolution of modern tomographic scanners promote the development of meaningful quantitative end points, determined from images which are in turn produced using well-controlled imaging protocols. For the QI environment to expand, medical physicists, physicians, other researchers and equipment vendors need to work collaboratively to develop the quantitative protocols for imaging, scanner calibrations, and robust analytical software that will lead to the routine inclusion of quantitative parameters in the diagnosis and therapeutic assessment of human health. Most importantly, quantitative metrics need to be developed which have genuine impact on patient diagnosis and welfare, and only then will QI techniques become integrated into the clinical environment.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0094-2405
pubmed:author
pubmed:issnType
Print
pubmed:volume
34
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
4173-9
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Radiological interpretation 2020: toward quantitative image assessment.
pubmed:affiliation
University of California, Davis, UC Davis Medical Center, 4860 Y Street, Ellison Building Suite 3100, Sacramento, California 95817, USA. jmboone@ucdavis.edu
pubmed:publicationType
Journal Article