reference/16737166

http://rdf.ncbi.nlm.nih.gov/pubchem/reference/16737166

Outgoing Links

Predicate	Object
contentType	Proceedings Article
endingPage	212
issn	1945-7928
pageRange	209-212
publicationName	2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
startingPage	209
hasFundingAgency	http://rdf.ncbi.nlm.nih.gov/pubchem/organization/MD5_20d2acdc7b9f39ed033b62cfe2874d00
isSupportedBy	http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_3e55bdda02670a7243780b8b1b6a6c9d http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_8199c75051727fc804864d48b9cd5a33 http://rdf.ncbi.nlm.nih.gov/pubchem/grant/MD5_731bbb98dcf181fd7e72e37c7aea408a
bibliographicCitation	Liu B, Yang L, Kulikowski C, Zhou J, Gong L, Foran DJ, Jabbour SJ, Yue NJ. AN ADAPTIVE TRACKING ALGORITHM OF LUNG TUMORS IN FLUOROSCOPY USING ONLINE LEARNED COLLABORATIVE TRACKERS. Proc IEEE Int Symp Biomed Imaging. 2010 Apr 01;2010():209–12. PMID: 20622932; PMCID: PMC2900817.
creator	http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_8f8f3b4c0b972f55e3f90a0dac0e1a88 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f749cfdca0d90dd1b6d4e4932dc98ecc http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_4e28cee93348fb8ed4efd33477b72f8d http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_e2c8ddc2f69fcba754ebb4dce6637bbf http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_5514d39b8a6641194104c1aa15b4938a http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_8aac01e1f1a72f15765c7beb8bb4ed9b http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_0b40a15dadda9c9f0418fc93cac9ad74 http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_9c404cf5d360bc2a9fee1808a3fcce51
date	2010-04-01-04:00^^<http://www.w3.org/2001/XMLSchema#date>
identifier	https://doi.org/10.1109/isbi.2010.5490376 https://pubmed.ncbi.nlm.nih.gov/PMC2900817 https://pubmed.ncbi.nlm.nih.gov/20622932
isPartOf	https://portal.issn.org/resource/ISSN/1945-7928 http://rdf.ncbi.nlm.nih.gov/pubchem/journal/35639
language	English
source	https://www.crossref.org/ https://pubmed.ncbi.nlm.nih.gov/
title	An adaptive tracking algorithm of lung tumors in fluoroscopy using online learned collaborative trackers

Total number of triples: 29.