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Improving PET-based physiological quantification through methods of wavelet denoising
The goal of this study was to evaluate methods of multidimensional wavelet denoising on restoring the fidelity of biological signals hidden within dynamic positron emission tomography (PET) images. A reduction of noise within pixels, between adjacent regions, and time-serial frames was achieved via...
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| Published in: | IEEE transactions on biomedical engineering 2001-02, Vol.48 (2), p.202-212 |
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| Main Authors: | , , |
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| cites | cdi_FETCH-LOGICAL-c486t-f4d31b0ea167185a75fc45bd7eaa487db0eb977bcaba1faad330519a3ffb16773 |
| container_end_page | 212 |
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| container_title | IEEE transactions on biomedical engineering |
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| creator | Jou-Wei Lin Laine, A.F. Bergmann, S.R. |
| description | The goal of this study was to evaluate methods of multidimensional wavelet denoising on restoring the fidelity of biological signals hidden within dynamic positron emission tomography (PET) images. A reduction of noise within pixels, between adjacent regions, and time-serial frames was achieved via redundant multiscale representations. In analyzing dynamic PET data of healthy volunteers, a multiscale method improved the estimate-to-error ratio of flows fivefold without loss of detail. This technique also maintained accuracy of flow estimates in comparison with the "gold standard," using dynamic PET with O15-water. In addition, in studies of coronary disease patients, flow patterns were preserved and infarcted regions were well differentiated from normal regions. The results show that a wavelet-based noise-suppression method produced reliable approximations of salient underlying signals and led to an accurate quantification of myocardial perfusion. The described protocol can be generalized to other temporal biomedical imaging modalities including functional magnetic resonance imaging and ultrasound. |
| doi_str_mv | 10.1109/10.909641 |
| format | article |
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A reduction of noise within pixels, between adjacent regions, and time-serial frames was achieved via redundant multiscale representations. In analyzing dynamic PET data of healthy volunteers, a multiscale method improved the estimate-to-error ratio of flows fivefold without loss of detail. This technique also maintained accuracy of flow estimates in comparison with the "gold standard," using dynamic PET with O15-water. In addition, in studies of coronary disease patients, flow patterns were preserved and infarcted regions were well differentiated from normal regions. The results show that a wavelet-based noise-suppression method produced reliable approximations of salient underlying signals and led to an accurate quantification of myocardial perfusion. The described protocol can be generalized to other temporal biomedical imaging modalities including functional magnetic resonance imaging and ultrasound.</description><identifier>ISSN: 0018-9294</identifier><identifier>EISSN: 1558-2531</identifier><identifier>DOI: 10.1109/10.909641</identifier><identifier>PMID: 11296876</identifier><identifier>CODEN: IEBEAX</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Adult ; Algorithms ; Biological and medical sciences ; Cardiovascular system ; Coronary Disease - diagnostic imaging ; Data analysis ; Diseases ; Dynamic tests ; Dynamics ; Female ; Gold ; Heart - diagnostic imaging ; Humans ; Image Enhancement - methods ; Image restoration ; Imaging ; Investigative techniques, diagnostic techniques (general aspects) ; Magnetic noise ; Maintenance ; Male ; Medical imaging ; Medical research ; Medical sciences ; Middle Aged ; Models, Cardiovascular ; Multidimensional systems ; Multiscale methods ; Myocardial Infarction - diagnostic imaging ; NMR ; Noise reduction ; Nuclear magnetic resonance ; Patients ; Positron emission tomography ; Radionuclide investigations ; Reduction ; Signal restoration ; Tomography, Emission-Computed ; Wavelet</subject><ispartof>IEEE transactions on biomedical engineering, 2001-02, Vol.48 (2), p.202-212</ispartof><rights>2001 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2001</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c486t-f4d31b0ea167185a75fc45bd7eaa487db0eb977bcaba1faad330519a3ffb16773</citedby><cites>FETCH-LOGICAL-c486t-f4d31b0ea167185a75fc45bd7eaa487db0eb977bcaba1faad330519a3ffb16773</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/909641$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=902411$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/11296876$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jou-Wei Lin</creatorcontrib><creatorcontrib>Laine, A.F.</creatorcontrib><creatorcontrib>Bergmann, S.R.</creatorcontrib><title>Improving PET-based physiological quantification through methods of wavelet denoising</title><title>IEEE transactions on biomedical engineering</title><addtitle>TBME</addtitle><addtitle>IEEE Trans Biomed Eng</addtitle><description>The goal of this study was to evaluate methods of multidimensional wavelet denoising on restoring the fidelity of biological signals hidden within dynamic positron emission tomography (PET) images. A reduction of noise within pixels, between adjacent regions, and time-serial frames was achieved via redundant multiscale representations. In analyzing dynamic PET data of healthy volunteers, a multiscale method improved the estimate-to-error ratio of flows fivefold without loss of detail. This technique also maintained accuracy of flow estimates in comparison with the "gold standard," using dynamic PET with O15-water. In addition, in studies of coronary disease patients, flow patterns were preserved and infarcted regions were well differentiated from normal regions. The results show that a wavelet-based noise-suppression method produced reliable approximations of salient underlying signals and led to an accurate quantification of myocardial perfusion. The described protocol can be generalized to other temporal biomedical imaging modalities including functional magnetic resonance imaging and ultrasound.</description><subject>Adult</subject><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Cardiovascular system</subject><subject>Coronary Disease - diagnostic imaging</subject><subject>Data analysis</subject><subject>Diseases</subject><subject>Dynamic tests</subject><subject>Dynamics</subject><subject>Female</subject><subject>Gold</subject><subject>Heart - diagnostic imaging</subject><subject>Humans</subject><subject>Image Enhancement - methods</subject><subject>Image restoration</subject><subject>Imaging</subject><subject>Investigative techniques, diagnostic techniques (general aspects)</subject><subject>Magnetic noise</subject><subject>Maintenance</subject><subject>Male</subject><subject>Medical imaging</subject><subject>Medical research</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Models, Cardiovascular</subject><subject>Multidimensional systems</subject><subject>Multiscale methods</subject><subject>Myocardial Infarction - diagnostic imaging</subject><subject>NMR</subject><subject>Noise reduction</subject><subject>Nuclear magnetic resonance</subject><subject>Patients</subject><subject>Positron emission tomography</subject><subject>Radionuclide investigations</subject><subject>Reduction</subject><subject>Signal restoration</subject><subject>Tomography, Emission-Computed</subject><subject>Wavelet</subject><issn>0018-9294</issn><issn>1558-2531</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><recordid>eNqFkcFP2zAUxi20CUrHYdcdpohJGxwy_GInto8T6rZKldihPUcvid0aJXGJkyL-exxaDcQBTp-t9_Pn995HyGegPwGougqqqMo4HJEJpKmMk5TBBzKhFGSsEsVPyKn3t-HKJc-OyQlAojIpsglZzZtt53a2XUf_Zsu4QK-raLt58NbVbm1LrKO7AdvemnDurWujftO5Yb2JGt1vXOUjZ6J73Ola91GlW2d98PpEPhqsvT476JSsfs-W13_jxc2f-fWvRVxymfWx4RWDgmqETIBMUaSm5GlRCY3IpahCqVBCFCUWCAaxYoymoJAZU4Qngk3Jj71vmOFu0L7PG-tLXdfYajf4XEoJVGZCBfL7m6QQlAuVwbtgIplQkIzgxZvgOFPCRFh1QM9fobdu6NqwmdAhl4nkbOzwcg-VnfO-0ybfdrbB7iEHmo8xj7qPObBfD4ZD0ejqmTzkGoBvBwB9yNB02JbW_-cUTTiMNl_2lNVavyg-_fEINfe2kw</recordid><startdate>20010201</startdate><enddate>20010201</enddate><creator>Jou-Wei Lin</creator><creator>Laine, A.F.</creator><creator>Bergmann, S.R.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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diagnostic imaging</topic><topic>Data analysis</topic><topic>Diseases</topic><topic>Dynamic tests</topic><topic>Dynamics</topic><topic>Female</topic><topic>Gold</topic><topic>Heart - diagnostic imaging</topic><topic>Humans</topic><topic>Image Enhancement - methods</topic><topic>Image restoration</topic><topic>Imaging</topic><topic>Investigative techniques, diagnostic techniques (general aspects)</topic><topic>Magnetic noise</topic><topic>Maintenance</topic><topic>Male</topic><topic>Medical imaging</topic><topic>Medical research</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Models, Cardiovascular</topic><topic>Multidimensional systems</topic><topic>Multiscale methods</topic><topic>Myocardial Infarction - diagnostic imaging</topic><topic>NMR</topic><topic>Noise reduction</topic><topic>Nuclear magnetic resonance</topic><topic>Patients</topic><topic>Positron emission tomography</topic><topic>Radionuclide investigations</topic><topic>Reduction</topic><topic>Signal restoration</topic><topic>Tomography, Emission-Computed</topic><topic>Wavelet</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jou-Wei Lin</creatorcontrib><creatorcontrib>Laine, A.F.</creatorcontrib><creatorcontrib>Bergmann, S.R.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Xplore</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE transactions on biomedical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jou-Wei Lin</au><au>Laine, A.F.</au><au>Bergmann, S.R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Improving PET-based physiological quantification through methods of wavelet denoising</atitle><jtitle>IEEE transactions on biomedical engineering</jtitle><stitle>TBME</stitle><addtitle>IEEE Trans Biomed Eng</addtitle><date>2001-02-01</date><risdate>2001</risdate><volume>48</volume><issue>2</issue><spage>202</spage><epage>212</epage><pages>202-212</pages><issn>0018-9294</issn><eissn>1558-2531</eissn><coden>IEBEAX</coden><abstract>The goal of this study was to evaluate methods of multidimensional wavelet denoising on restoring the fidelity of biological signals hidden within dynamic positron emission tomography (PET) images. A reduction of noise within pixels, between adjacent regions, and time-serial frames was achieved via redundant multiscale representations. In analyzing dynamic PET data of healthy volunteers, a multiscale method improved the estimate-to-error ratio of flows fivefold without loss of detail. This technique also maintained accuracy of flow estimates in comparison with the "gold standard," using dynamic PET with O15-water. In addition, in studies of coronary disease patients, flow patterns were preserved and infarcted regions were well differentiated from normal regions. The results show that a wavelet-based noise-suppression method produced reliable approximations of salient underlying signals and led to an accurate quantification of myocardial perfusion. The described protocol can be generalized to other temporal biomedical imaging modalities including functional magnetic resonance imaging and ultrasound.</abstract><cop>New York, NY</cop><pub>IEEE</pub><pmid>11296876</pmid><doi>10.1109/10.909641</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | IEEE transactions on biomedical engineering, 2001-02, Vol.48 (2), p.202-212 |
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| source | IEEE Electronic Library (IEL) Journals |
| subjects | Adult Algorithms Biological and medical sciences Cardiovascular system Coronary Disease - diagnostic imaging Data analysis Diseases Dynamic tests Dynamics Female Gold Heart - diagnostic imaging Humans Image Enhancement - methods Image restoration Imaging Investigative techniques, diagnostic techniques (general aspects) Magnetic noise Maintenance Male Medical imaging Medical research Medical sciences Middle Aged Models, Cardiovascular Multidimensional systems Multiscale methods Myocardial Infarction - diagnostic imaging NMR Noise reduction Nuclear magnetic resonance Patients Positron emission tomography Radionuclide investigations Reduction Signal restoration Tomography, Emission-Computed Wavelet |
| title | Improving PET-based physiological quantification through methods of wavelet denoising |
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