Linked Life Data

15910097

Source:http://linkedlifedata.com/resource/pubmed/id/15910097

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2005-5-24
pubmed:abstractText
Characterization of human tissue using near-IR (NIR) light is becoming increasingly popular. The light signal transmitted from the tissue contains information concerning inhomogeneities in tissue, such as size, position, and pathological states (benign or malignant). We discuss the most probable diffuse path (MPDP) related to frequency-domain diffuse photon density waves (DPDWs) propagating inside turbid media. We find that for a medium of finite size, the existence of boundaries between tissue and nonscattering media would have considerable impact on the path shape. It is also demonstrated that such paths can be used to obtain higher accuracy in localizing absorbers embedded in a homogeneous background. Based on the proposed MPDP, a new method for 3-D localization of heterogeneities in turbid media is proposed, which is validated by experiments using Intralipid and pork fat. The experiments are performed with an NIR breast cancer detection system designed and assembled in our lab, using 780-nm NIR light. In Intralipid, when the size of a single absorber is less than 1 cm, the localization error is about 2 mm. The results from pork fat are also acceptable.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1083-3668
pubmed:author
pubmed:copyrightInfo
Copyright 2005 Society of Photo-Optical Instrumentation Engineers.
pubmed:issnType
Print
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
024024
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:articleTitle
Locating inhomogeneities in tissue by using the most probable diffuse path of light.
pubmed:affiliation
Tsinghua University, Department of Biomedical Engineering, Beijing, China, 100084. deabj@tsinghua.edu.cn
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't