A Regularization Method Based on the Correlations of Diffusion Weighted Images
Diffusion weighted images are affected by several artifacts and noise which complicate the analysis and interpretation of DTI data. The method we present in this thesis works for the regularization of DTI data, which takes into account all the relations of DWI components, including relations of the...
Gespeichert in:
Hauptverfasser: | , , , , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 5 |
---|---|
container_issue | |
container_start_page | 1 |
container_title | |
container_volume | |
creator | Yi Sanli Chen Zhencheng Ling Hongli Jiang Pei Li Weng |
description | Diffusion weighted images are affected by several artifacts and noise which complicate the analysis and interpretation of DTI data. The method we present in this thesis works for the regularization of DTI data, which takes into account all the relations of DWI components, including relations of the values at different encoding directions. Our method is based on the theory of Wiener filter, and we molded it to filter the DWI dataset The method was illustrated by the synthetic and real data and the result has supported the filtering methodology proposed in this thesis. |
doi_str_mv | 10.1109/BMEI.2009.5304865 |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5304865</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5304865</ieee_id><sourcerecordid>5304865</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-32d07da033c5a2127a73676428cda1bc7966902c19529fb5b1064d9531e8380c3</originalsourceid><addsrcrecordid>eNo9kM1OAjEUhesPiYA8gHHTFxi897bTzl0CopKAJoZEd6TMdKAGHDMdFvr0gqKrk5Pvy1kcIa4Q-ojAN8PZeNInAO6nCnRm0hPRQU1aa1T69VS0kXWWEBOdiR7b7I-RPf9nqFuic9hg2AO-EL0Y3wAA2TBZ1RaPA_nsV7uNq8OXa0L1Lme-WVeFHLroC7nvzdrLUVXXfvPDo6xKeRvKchcP9osPq3WzNydbt_LxUrRKt4m-d8yumN-N56OHZPp0PxkNpklgaBJFBdjCgVJ56gjJOquMNZqyvHC4zC0bw0A5ckpcLtMlgtEFpwp9pjLIVVdc_84G7_3iow5bV38ujjepb-S0U4I</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>A Regularization Method Based on the Correlations of Diffusion Weighted Images</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Yi Sanli ; Chen Zhencheng ; Ling Hongli ; Jiang Pei ; Li Weng</creator><creatorcontrib>Yi Sanli ; Chen Zhencheng ; Ling Hongli ; Jiang Pei ; Li Weng</creatorcontrib><description>Diffusion weighted images are affected by several artifacts and noise which complicate the analysis and interpretation of DTI data. The method we present in this thesis works for the regularization of DTI data, which takes into account all the relations of DWI components, including relations of the values at different encoding directions. Our method is based on the theory of Wiener filter, and we molded it to filter the DWI dataset The method was illustrated by the synthetic and real data and the result has supported the filtering methodology proposed in this thesis.</description><identifier>ISSN: 1948-2914</identifier><identifier>ISBN: 9781424441327</identifier><identifier>ISBN: 1424441323</identifier><identifier>EISSN: 1948-2922</identifier><identifier>EISBN: 142444134X</identifier><identifier>EISBN: 9781424441341</identifier><identifier>DOI: 10.1109/BMEI.2009.5304865</identifier><identifier>LCCN: 2009901329</identifier><language>eng</language><publisher>IEEE</publisher><subject>Biomedical computing ; Biomedical engineering ; Diffusion tensor imaging ; Encoding ; Filtering theory ; Image analysis ; Rician channels ; Smoothing methods ; Tensile stress ; Wiener filter</subject><ispartof>2009 2nd International Conference on Biomedical Engineering and Informatics, 2009, p.1-5</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5304865$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5304865$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Yi Sanli</creatorcontrib><creatorcontrib>Chen Zhencheng</creatorcontrib><creatorcontrib>Ling Hongli</creatorcontrib><creatorcontrib>Jiang Pei</creatorcontrib><creatorcontrib>Li Weng</creatorcontrib><title>A Regularization Method Based on the Correlations of Diffusion Weighted Images</title><title>2009 2nd International Conference on Biomedical Engineering and Informatics</title><addtitle>BMEI</addtitle><description>Diffusion weighted images are affected by several artifacts and noise which complicate the analysis and interpretation of DTI data. The method we present in this thesis works for the regularization of DTI data, which takes into account all the relations of DWI components, including relations of the values at different encoding directions. Our method is based on the theory of Wiener filter, and we molded it to filter the DWI dataset The method was illustrated by the synthetic and real data and the result has supported the filtering methodology proposed in this thesis.</description><subject>Biomedical computing</subject><subject>Biomedical engineering</subject><subject>Diffusion tensor imaging</subject><subject>Encoding</subject><subject>Filtering theory</subject><subject>Image analysis</subject><subject>Rician channels</subject><subject>Smoothing methods</subject><subject>Tensile stress</subject><subject>Wiener filter</subject><issn>1948-2914</issn><issn>1948-2922</issn><isbn>9781424441327</isbn><isbn>1424441323</isbn><isbn>142444134X</isbn><isbn>9781424441341</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo9kM1OAjEUhesPiYA8gHHTFxi897bTzl0CopKAJoZEd6TMdKAGHDMdFvr0gqKrk5Pvy1kcIa4Q-ojAN8PZeNInAO6nCnRm0hPRQU1aa1T69VS0kXWWEBOdiR7b7I-RPf9nqFuic9hg2AO-EL0Y3wAA2TBZ1RaPA_nsV7uNq8OXa0L1Lme-WVeFHLroC7nvzdrLUVXXfvPDo6xKeRvKchcP9osPq3WzNydbt_LxUrRKt4m-d8yumN-N56OHZPp0PxkNpklgaBJFBdjCgVJ56gjJOquMNZqyvHC4zC0bw0A5ckpcLtMlgtEFpwp9pjLIVVdc_84G7_3iow5bV38ujjepb-S0U4I</recordid><startdate>200910</startdate><enddate>200910</enddate><creator>Yi Sanli</creator><creator>Chen Zhencheng</creator><creator>Ling Hongli</creator><creator>Jiang Pei</creator><creator>Li Weng</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200910</creationdate><title>A Regularization Method Based on the Correlations of Diffusion Weighted Images</title><author>Yi Sanli ; Chen Zhencheng ; Ling Hongli ; Jiang Pei ; Li Weng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-32d07da033c5a2127a73676428cda1bc7966902c19529fb5b1064d9531e8380c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Biomedical computing</topic><topic>Biomedical engineering</topic><topic>Diffusion tensor imaging</topic><topic>Encoding</topic><topic>Filtering theory</topic><topic>Image analysis</topic><topic>Rician channels</topic><topic>Smoothing methods</topic><topic>Tensile stress</topic><topic>Wiener filter</topic><toplevel>online_resources</toplevel><creatorcontrib>Yi Sanli</creatorcontrib><creatorcontrib>Chen Zhencheng</creatorcontrib><creatorcontrib>Ling Hongli</creatorcontrib><creatorcontrib>Jiang Pei</creatorcontrib><creatorcontrib>Li Weng</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yi Sanli</au><au>Chen Zhencheng</au><au>Ling Hongli</au><au>Jiang Pei</au><au>Li Weng</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A Regularization Method Based on the Correlations of Diffusion Weighted Images</atitle><btitle>2009 2nd International Conference on Biomedical Engineering and Informatics</btitle><stitle>BMEI</stitle><date>2009-10</date><risdate>2009</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><issn>1948-2914</issn><eissn>1948-2922</eissn><isbn>9781424441327</isbn><isbn>1424441323</isbn><eisbn>142444134X</eisbn><eisbn>9781424441341</eisbn><abstract>Diffusion weighted images are affected by several artifacts and noise which complicate the analysis and interpretation of DTI data. The method we present in this thesis works for the regularization of DTI data, which takes into account all the relations of DWI components, including relations of the values at different encoding directions. Our method is based on the theory of Wiener filter, and we molded it to filter the DWI dataset The method was illustrated by the synthetic and real data and the result has supported the filtering methodology proposed in this thesis.</abstract><pub>IEEE</pub><doi>10.1109/BMEI.2009.5304865</doi><tpages>5</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1948-2914 |
ispartof | 2009 2nd International Conference on Biomedical Engineering and Informatics, 2009, p.1-5 |
issn | 1948-2914 1948-2922 |
language | eng |
recordid | cdi_ieee_primary_5304865 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Biomedical computing Biomedical engineering Diffusion tensor imaging Encoding Filtering theory Image analysis Rician channels Smoothing methods Tensile stress Wiener filter |
title | A Regularization Method Based on the Correlations of Diffusion Weighted Images |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-30T08%3A45%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=A%20Regularization%20Method%20Based%20on%20the%20Correlations%20of%20Diffusion%20Weighted%20Images&rft.btitle=2009%202nd%20International%20Conference%20on%20Biomedical%20Engineering%20and%20Informatics&rft.au=Yi%20Sanli&rft.date=2009-10&rft.spage=1&rft.epage=5&rft.pages=1-5&rft.issn=1948-2914&rft.eissn=1948-2922&rft.isbn=9781424441327&rft.isbn_list=1424441323&rft_id=info:doi/10.1109/BMEI.2009.5304865&rft_dat=%3Cieee_6IE%3E5304865%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=142444134X&rft.eisbn_list=9781424441341&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5304865&rfr_iscdi=true |