Linked Life Data

8044351

Source:http://linkedlifedata.com/resource/pubmed/id/8044351

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1994-9-1
pubmed:abstractText
This article is a case-based review that introduces applied statisticians to a number of issues and methods that arise in clinical studies with paired digital images as outcomes. Single photon emission computed tomography (SPECT) is the imaging modality used in two examples. The first is a physical simulation of relevant clinical features of SPECT images using a customized head phantom scanned under different experimental conditions. The objective is to demonstrate and compare several current methods for image registration, i.e., image superimposition in some optimal manner to obtain a common frame of reference within which to make pixel-by-pixel comparisons. Image registration together with image normalization to correct for spurious differences in background activity levels enable quantification of differences in paired images. The physical simulation assesses quantification accuracy. The second example involves two SPECT images of the same brain tumour patient taken about two months apart. The objective here is to demonstrate several tools from morphological image analysis for image segmentation, i.e., separation of 'figure' and 'ground', and simple image regression to detect patterns of differences in time, again after registration and normalization. The clinical context of both examples helps to keep the review in practical focus and is a useful starting point for descriptions of many standard tools in applied medical image analysis. References to relevant literature are provided for readers wanting to study particular subjects in depth. As medical image analysis becomes more sophisticated, more cost-conscious and scrutinized more intensively, proper attention to the computational and statistical bases for practical conclusions become even more crucial.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0962-2802
pubmed:author
pubmed:issnType
Print
pubmed:volume
3
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
23-40
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1994
pubmed:articleTitle
Some computational and statistical tools for paired comparisons of digital images.
pubmed:affiliation
National Institutes of Health, Bethesda, Maryland 20892.
pubmed:publicationType
Journal Article, Comparative Study, Review, Research Support, Non-U.S. Gov't