Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms
This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-par...
Gespeichert in:
| Veröffentlicht in: | IEEE journal of biomedical and health informatics 2005-03, Vol.9 (1), p.132-138 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 138 |
|---|---|
| container_issue | 1 |
| container_start_page | 132 |
| container_title | IEEE journal of biomedical and health informatics |
| container_volume | 9 |
| creator | Kassim, A.A. Pingkun Yan Wei Siong Lee Sengupta, K. |
| description | This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT. |
| doi_str_mv | 10.1109/TITB.2004.838376 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_crossref_primary_10_1109_TITB_2004_838376</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1402455</ieee_id><sourcerecordid>888112448</sourcerecordid><originalsourceid>FETCH-LOGICAL-c438t-35622f563a2409241cea2efd67cbe2043e4e498b1d37e65195ed67a5767c42ee3</originalsourceid><addsrcrecordid>eNqFkU1LJDEQhoMoft-FhSV4cE89VpJKJ330Yz8EZS_jucn0VA8t3Z0x6Vb896Z3BgQP6ykv1FMvoR7GzgTMhIDicn43v55JAJxZZZXJd9ih0NpmAErupgy2yIwx4oAdxfgEIFALtc8OhDbWgNCHbPXgh8b3vPLdmvroBlry1sf4lg0-m0JLMf6bhhQm0tccs1ve0bKpXMubzq0o8jE2_Yo3_UArCvzVvVBLAx-C62PtQxdP2F7t2kin2_eYPf76Ob_5k93__X13c3WfVajskCmdS1nrXDmJUEgUFTlJ9TI31YIkoCIkLOxCLJWhXItCU5o5bRKAkkgdsx-b3nXwzyPFoeyaWFHbup78GEtrrRAS0Sby4r9kbjTmYM2XoLSA0lr4EhQFygJxajz_BD75MfTpLul_CrU0skgQbKAqJA2B6nId0rHDWymgnOyXk_1ysl9u7KeV79vecZH8fCxsdSfg2wZoiOhjjCBRa_UOSmOy9w</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>883452729</pqid></control><display><type>article</type><title>Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms</title><source>IEEE Electronic Library (IEL)</source><creator>Kassim, A.A. ; Pingkun Yan ; Wei Siong Lee ; Sengupta, K.</creator><creatorcontrib>Kassim, A.A. ; Pingkun Yan ; Wei Siong Lee ; Sengupta, K.</creatorcontrib><description>This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.</description><identifier>ISSN: 1089-7771</identifier><identifier>ISSN: 2168-2194</identifier><identifier>EISSN: 1558-0032</identifier><identifier>EISSN: 2168-2208</identifier><identifier>DOI: 10.1109/TITB.2004.838376</identifier><identifier>PMID: 15787015</identifier><identifier>CODEN: ITIBFX</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Artificial Intelligence ; Biomedical imaging ; Cluster Analysis ; Computed tomography ; Cube matching algorithm ; Data Compression - methods ; Decoding ; Discrete wavelet transforms ; four-dimensional (4-D) medical image ; Humans ; Image coding ; Image Enhancement - methods ; Image Interpretation, Computer-Assisted - methods ; Image sequences ; Image storage ; Imaging, Three-Dimensional - methods ; integer wavelet transform (IWT) ; lossy-to-lossless compression ; Medical diagnostic imaging ; Motion compensation ; Movement ; Numerical Analysis, Computer-Assisted ; Pattern Recognition, Automated - methods ; Reproducibility of Results ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Subtraction Technique ; three-dimensional (3-D) set-partitioning in hierarchical trees (SPIHT) ; Video Recording - methods ; Wavelet transforms</subject><ispartof>IEEE journal of biomedical and health informatics, 2005-03, Vol.9 (1), p.132-138</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2005</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-35622f563a2409241cea2efd67cbe2043e4e498b1d37e65195ed67a5767c42ee3</citedby><cites>FETCH-LOGICAL-c438t-35622f563a2409241cea2efd67cbe2043e4e498b1d37e65195ed67a5767c42ee3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1402455$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,781,785,797,27929,27930,54763</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1402455$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15787015$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kassim, A.A.</creatorcontrib><creatorcontrib>Pingkun Yan</creatorcontrib><creatorcontrib>Wei Siong Lee</creatorcontrib><creatorcontrib>Sengupta, K.</creatorcontrib><title>Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms</title><title>IEEE journal of biomedical and health informatics</title><addtitle>TITB</addtitle><addtitle>IEEE Trans Inf Technol Biomed</addtitle><description>This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Biomedical imaging</subject><subject>Cluster Analysis</subject><subject>Computed tomography</subject><subject>Cube matching algorithm</subject><subject>Data Compression - methods</subject><subject>Decoding</subject><subject>Discrete wavelet transforms</subject><subject>four-dimensional (4-D) medical image</subject><subject>Humans</subject><subject>Image coding</subject><subject>Image Enhancement - methods</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image sequences</subject><subject>Image storage</subject><subject>Imaging, Three-Dimensional - methods</subject><subject>integer wavelet transform (IWT)</subject><subject>lossy-to-lossless compression</subject><subject>Medical diagnostic imaging</subject><subject>Motion compensation</subject><subject>Movement</subject><subject>Numerical Analysis, Computer-Assisted</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Subtraction Technique</subject><subject>three-dimensional (3-D) set-partitioning in hierarchical trees (SPIHT)</subject><subject>Video Recording - methods</subject><subject>Wavelet transforms</subject><issn>1089-7771</issn><issn>2168-2194</issn><issn>1558-0032</issn><issn>2168-2208</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqFkU1LJDEQhoMoft-FhSV4cE89VpJKJ330Yz8EZS_jucn0VA8t3Z0x6Vb896Z3BgQP6ykv1FMvoR7GzgTMhIDicn43v55JAJxZZZXJd9ih0NpmAErupgy2yIwx4oAdxfgEIFALtc8OhDbWgNCHbPXgh8b3vPLdmvroBlry1sf4lg0-m0JLMf6bhhQm0tccs1ve0bKpXMubzq0o8jE2_Yo3_UArCvzVvVBLAx-C62PtQxdP2F7t2kin2_eYPf76Ob_5k93__X13c3WfVajskCmdS1nrXDmJUEgUFTlJ9TI31YIkoCIkLOxCLJWhXItCU5o5bRKAkkgdsx-b3nXwzyPFoeyaWFHbup78GEtrrRAS0Sby4r9kbjTmYM2XoLSA0lr4EhQFygJxajz_BD75MfTpLul_CrU0skgQbKAqJA2B6nId0rHDWymgnOyXk_1ysl9u7KeV79vecZH8fCxsdSfg2wZoiOhjjCBRa_UOSmOy9w</recordid><startdate>20050301</startdate><enddate>20050301</enddate><creator>Kassim, A.A.</creator><creator>Pingkun Yan</creator><creator>Wei Siong Lee</creator><creator>Sengupta, K.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>NAPCQ</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20050301</creationdate><title>Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms</title><author>Kassim, A.A. ; Pingkun Yan ; Wei Siong Lee ; Sengupta, K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-35622f563a2409241cea2efd67cbe2043e4e498b1d37e65195ed67a5767c42ee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>Biomedical imaging</topic><topic>Cluster Analysis</topic><topic>Computed tomography</topic><topic>Cube matching algorithm</topic><topic>Data Compression - methods</topic><topic>Decoding</topic><topic>Discrete wavelet transforms</topic><topic>four-dimensional (4-D) medical image</topic><topic>Humans</topic><topic>Image coding</topic><topic>Image Enhancement - methods</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Image sequences</topic><topic>Image storage</topic><topic>Imaging, Three-Dimensional - methods</topic><topic>integer wavelet transform (IWT)</topic><topic>lossy-to-lossless compression</topic><topic>Medical diagnostic imaging</topic><topic>Motion compensation</topic><topic>Movement</topic><topic>Numerical Analysis, Computer-Assisted</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Signal Processing, Computer-Assisted</topic><topic>Subtraction Technique</topic><topic>three-dimensional (3-D) set-partitioning in hierarchical trees (SPIHT)</topic><topic>Video Recording - methods</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kassim, A.A.</creatorcontrib><creatorcontrib>Pingkun Yan</creatorcontrib><creatorcontrib>Wei Siong Lee</creatorcontrib><creatorcontrib>Sengupta, K.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</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>ProQuest Health & Medical Complete (Alumni)</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>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE journal of biomedical and health informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kassim, A.A.</au><au>Pingkun Yan</au><au>Wei Siong Lee</au><au>Sengupta, K.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms</atitle><jtitle>IEEE journal of biomedical and health informatics</jtitle><stitle>TITB</stitle><addtitle>IEEE Trans Inf Technol Biomed</addtitle><date>2005-03-01</date><risdate>2005</risdate><volume>9</volume><issue>1</issue><spage>132</spage><epage>138</epage><pages>132-138</pages><issn>1089-7771</issn><issn>2168-2194</issn><eissn>1558-0032</eissn><eissn>2168-2208</eissn><coden>ITIBFX</coden><abstract>This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>15787015</pmid><doi>10.1109/TITB.2004.838376</doi><tpages>7</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1089-7771 |
| ispartof | IEEE journal of biomedical and health informatics, 2005-03, Vol.9 (1), p.132-138 |
| issn | 1089-7771 2168-2194 1558-0032 2168-2208 |
| language | eng |
| recordid | cdi_crossref_primary_10_1109_TITB_2004_838376 |
| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Artificial Intelligence Biomedical imaging Cluster Analysis Computed tomography Cube matching algorithm Data Compression - methods Decoding Discrete wavelet transforms four-dimensional (4-D) medical image Humans Image coding Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image sequences Image storage Imaging, Three-Dimensional - methods integer wavelet transform (IWT) lossy-to-lossless compression Medical diagnostic imaging Motion compensation Movement Numerical Analysis, Computer-Assisted Pattern Recognition, Automated - methods Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Subtraction Technique three-dimensional (3-D) set-partitioning in hierarchical trees (SPIHT) Video Recording - methods Wavelet transforms |
| title | Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-11T14%3A25%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Motion%20compensated%20lossy-to-lossless%20compression%20of%204-D%20medical%20images%20using%20integer%20wavelet%20transforms&rft.jtitle=IEEE%20journal%20of%20biomedical%20and%20health%20informatics&rft.au=Kassim,%20A.A.&rft.date=2005-03-01&rft.volume=9&rft.issue=1&rft.spage=132&rft.epage=138&rft.pages=132-138&rft.issn=1089-7771&rft.eissn=1558-0032&rft.coden=ITIBFX&rft_id=info:doi/10.1109/TITB.2004.838376&rft_dat=%3Cproquest_RIE%3E888112448%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=883452729&rft_id=info:pmid/15787015&rft_ieee_id=1402455&rfr_iscdi=true |