Spectral signatures of point clouds and applications to detection of Alzheimer's Disease through Neuroimaging

We introduce a class of spectral shape signatures constructed from symmetric functions on the eigenfunctions of the Laplacian exponentially weighted by their eigenvalues. Such a construction is motivated by problems that arise in the use of the eigenfunctions for shape comparison, such as indetermin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Bates, J, Pafundi, D, Kanel, P, Liu, X, Mio, W
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1854
container_issue
container_start_page 1851
container_title
container_volume
creator Bates, J
Pafundi, D
Kanel, P
Liu, X
Mio, W
description We introduce a class of spectral shape signatures constructed from symmetric functions on the eigenfunctions of the Laplacian exponentially weighted by their eigenvalues. Such a construction is motivated by problems that arise in the use of the eigenfunctions for shape comparison, such as indeterminacies in the choice of signs and the particular ordering in which the eigenfunctions are presented. The spectral invariants are applied to the analysis of Alzheimer's disease (AD) data collected by the Alzheimer's Disease Neuroimaging Initiative, in particular, to the problem of determining whether the signatures can aid in early detection of AD through morphology and imaging.
doi_str_mv 10.1109/ISBI.2011.5872768
format Conference Proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5872768</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5872768</ieee_id><sourcerecordid>5872768</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-befe89a964e8f24073daa855f432ee70583ab32207a0a3ece2203a721e67725e3</originalsourceid><addsrcrecordid>eNpFUMtOwzAQNC-JUvoBiItvnFL8rJ1jKa9KFRwK52qbbFKjNI5s51C-niAqMZed0czOSkvIDWdTzll-v1w_LKeCcT7V1ggzsyfkiiuhlOLC6lMy4rnSmVVanP0bxpwfDZMLe0kmMX6xAUYpydSI7NcdFilAQ6OrW0h9wEh9RTvv2kSLxvdlpNCWFLqucQUk59tIk6clpmFxUL_pefO9Q7fHcBfpo4sIEWnaBd_XO_qGffBuD7Vr62tyUUETcXKcY_L5_PSxeM1W7y_LxXyVOW50yrZYoc0hnym0lVDMyBLAal0pKRAN01bCVgrBDDCQWOBAJRjBcWaM0CjH5Pav1yHipgvD-XDYHN8mfwBCDV6Z</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Spectral signatures of point clouds and applications to detection of Alzheimer's Disease through Neuroimaging</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Bates, J ; Pafundi, D ; Kanel, P ; Liu, X ; Mio, W</creator><creatorcontrib>Bates, J ; Pafundi, D ; Kanel, P ; Liu, X ; Mio, W</creatorcontrib><description>We introduce a class of spectral shape signatures constructed from symmetric functions on the eigenfunctions of the Laplacian exponentially weighted by their eigenvalues. Such a construction is motivated by problems that arise in the use of the eigenfunctions for shape comparison, such as indeterminacies in the choice of signs and the particular ordering in which the eigenfunctions are presented. The spectral invariants are applied to the analysis of Alzheimer's disease (AD) data collected by the Alzheimer's Disease Neuroimaging Initiative, in particular, to the problem of determining whether the signatures can aid in early detection of AD through morphology and imaging.</description><identifier>ISSN: 1945-7928</identifier><identifier>ISBN: 1424441277</identifier><identifier>ISBN: 9781424441273</identifier><identifier>EISSN: 1945-8452</identifier><identifier>EISBN: 1424441285</identifier><identifier>EISBN: 9781424441280</identifier><identifier>DOI: 10.1109/ISBI.2011.5872768</identifier><language>eng</language><publisher>IEEE</publisher><subject>ADNI ; Alzheimer's disease ; Eigenvalues and eigenfunctions ; Heating ; Hippocampus ; Laplace equations ; Point-cloud Laplacian ; Shape ; shape analysis ; spectral signatures</subject><ispartof>2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011, p.1851-1854</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/5872768$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,2052,27906,54901</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5872768$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Bates, J</creatorcontrib><creatorcontrib>Pafundi, D</creatorcontrib><creatorcontrib>Kanel, P</creatorcontrib><creatorcontrib>Liu, X</creatorcontrib><creatorcontrib>Mio, W</creatorcontrib><title>Spectral signatures of point clouds and applications to detection of Alzheimer's Disease through Neuroimaging</title><title>2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro</title><addtitle>ISBI</addtitle><description>We introduce a class of spectral shape signatures constructed from symmetric functions on the eigenfunctions of the Laplacian exponentially weighted by their eigenvalues. Such a construction is motivated by problems that arise in the use of the eigenfunctions for shape comparison, such as indeterminacies in the choice of signs and the particular ordering in which the eigenfunctions are presented. The spectral invariants are applied to the analysis of Alzheimer's disease (AD) data collected by the Alzheimer's Disease Neuroimaging Initiative, in particular, to the problem of determining whether the signatures can aid in early detection of AD through morphology and imaging.</description><subject>ADNI</subject><subject>Alzheimer's disease</subject><subject>Eigenvalues and eigenfunctions</subject><subject>Heating</subject><subject>Hippocampus</subject><subject>Laplace equations</subject><subject>Point-cloud Laplacian</subject><subject>Shape</subject><subject>shape analysis</subject><subject>spectral signatures</subject><issn>1945-7928</issn><issn>1945-8452</issn><isbn>1424441277</isbn><isbn>9781424441273</isbn><isbn>1424441285</isbn><isbn>9781424441280</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFUMtOwzAQNC-JUvoBiItvnFL8rJ1jKa9KFRwK52qbbFKjNI5s51C-niAqMZed0czOSkvIDWdTzll-v1w_LKeCcT7V1ggzsyfkiiuhlOLC6lMy4rnSmVVanP0bxpwfDZMLe0kmMX6xAUYpydSI7NcdFilAQ6OrW0h9wEh9RTvv2kSLxvdlpNCWFLqucQUk59tIk6clpmFxUL_pefO9Q7fHcBfpo4sIEWnaBd_XO_qGffBuD7Vr62tyUUETcXKcY_L5_PSxeM1W7y_LxXyVOW50yrZYoc0hnym0lVDMyBLAal0pKRAN01bCVgrBDDCQWOBAJRjBcWaM0CjH5Pav1yHipgvD-XDYHN8mfwBCDV6Z</recordid><startdate>201103</startdate><enddate>201103</enddate><creator>Bates, J</creator><creator>Pafundi, D</creator><creator>Kanel, P</creator><creator>Liu, X</creator><creator>Mio, W</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201103</creationdate><title>Spectral signatures of point clouds and applications to detection of Alzheimer's Disease through Neuroimaging</title><author>Bates, J ; Pafundi, D ; Kanel, P ; Liu, X ; Mio, W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-befe89a964e8f24073daa855f432ee70583ab32207a0a3ece2203a721e67725e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>ADNI</topic><topic>Alzheimer's disease</topic><topic>Eigenvalues and eigenfunctions</topic><topic>Heating</topic><topic>Hippocampus</topic><topic>Laplace equations</topic><topic>Point-cloud Laplacian</topic><topic>Shape</topic><topic>shape analysis</topic><topic>spectral signatures</topic><toplevel>online_resources</toplevel><creatorcontrib>Bates, J</creatorcontrib><creatorcontrib>Pafundi, D</creatorcontrib><creatorcontrib>Kanel, P</creatorcontrib><creatorcontrib>Liu, X</creatorcontrib><creatorcontrib>Mio, W</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>Bates, J</au><au>Pafundi, D</au><au>Kanel, P</au><au>Liu, X</au><au>Mio, W</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Spectral signatures of point clouds and applications to detection of Alzheimer's Disease through Neuroimaging</atitle><btitle>2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro</btitle><stitle>ISBI</stitle><date>2011-03</date><risdate>2011</risdate><spage>1851</spage><epage>1854</epage><pages>1851-1854</pages><issn>1945-7928</issn><eissn>1945-8452</eissn><isbn>1424441277</isbn><isbn>9781424441273</isbn><eisbn>1424441285</eisbn><eisbn>9781424441280</eisbn><abstract>We introduce a class of spectral shape signatures constructed from symmetric functions on the eigenfunctions of the Laplacian exponentially weighted by their eigenvalues. Such a construction is motivated by problems that arise in the use of the eigenfunctions for shape comparison, such as indeterminacies in the choice of signs and the particular ordering in which the eigenfunctions are presented. The spectral invariants are applied to the analysis of Alzheimer's disease (AD) data collected by the Alzheimer's Disease Neuroimaging Initiative, in particular, to the problem of determining whether the signatures can aid in early detection of AD through morphology and imaging.</abstract><pub>IEEE</pub><doi>10.1109/ISBI.2011.5872768</doi><tpages>4</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1945-7928
ispartof 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011, p.1851-1854
issn 1945-7928
1945-8452
language eng
recordid cdi_ieee_primary_5872768
source IEEE Electronic Library (IEL) Conference Proceedings
subjects ADNI
Alzheimer's disease
Eigenvalues and eigenfunctions
Heating
Hippocampus
Laplace equations
Point-cloud Laplacian
Shape
shape analysis
spectral signatures
title Spectral signatures of point clouds and applications to detection of Alzheimer's Disease through Neuroimaging
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T20%3A54%3A22IST&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=Spectral%20signatures%20of%20point%20clouds%20and%20applications%20to%20detection%20of%20Alzheimer's%20Disease%20through%20Neuroimaging&rft.btitle=2011%20IEEE%20International%20Symposium%20on%20Biomedical%20Imaging:%20From%20Nano%20to%20Macro&rft.au=Bates,%20J&rft.date=2011-03&rft.spage=1851&rft.epage=1854&rft.pages=1851-1854&rft.issn=1945-7928&rft.eissn=1945-8452&rft.isbn=1424441277&rft.isbn_list=9781424441273&rft_id=info:doi/10.1109/ISBI.2011.5872768&rft_dat=%3Cieee_6IE%3E5872768%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1424441285&rft.eisbn_list=9781424441280&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5872768&rfr_iscdi=true