Combined multi-kernel chest computed tomography images optimized for depicting both lung and soft tissue
Abstract Purpose To evaluate the quality of our improved multi-kernel chest computed tomography (CT) images. Methods A random sample of 50 normal patients was retrospectively selected from those who underwent chest CT scans between January 2010 and July 2010. Normal lung structures were divided into...
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| Veröffentlicht in: | Clinical imaging 2014-03, Vol.38 (2), p.104-108 |
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| container_title | Clinical imaging |
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| creator | Takagi, Satoshi Nagase, Hiroyuki Hayashi, Tatsuya Kita, Tamotsu Hayashi, Katsumi Sanada, Shigeru Koike, Masayuki |
| description | Abstract Purpose To evaluate the quality of our improved multi-kernel chest computed tomography (CT) images. Methods A random sample of 50 normal patients was retrospectively selected from those who underwent chest CT scans between January 2010 and July 2010. Normal lung structures were divided into six categories, and two radiologists independently compared with lung images. Results The improved multi-kernel images were displayed identically to soft tissue images on soft tissue window settings and were evaluated as equal to lung images on lung window settings. Conclusions This improved multi-kernel technique required fewer stored images and simplified examinations of chest CT. |
| doi_str_mv | 10.1016/j.clinimag.2013.11.009 |
| format | Article |
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Methods A random sample of 50 normal patients was retrospectively selected from those who underwent chest CT scans between January 2010 and July 2010. Normal lung structures were divided into six categories, and two radiologists independently compared with lung images. Results The improved multi-kernel images were displayed identically to soft tissue images on soft tissue window settings and were evaluated as equal to lung images on lung window settings. Conclusions This improved multi-kernel technique required fewer stored images and simplified examinations of chest CT.</description><identifier>ISSN: 0899-7071</identifier><identifier>EISSN: 1873-4499</identifier><identifier>DOI: 10.1016/j.clinimag.2013.11.009</identifier><identifier>PMID: 24361172</identifier><identifier>CODEN: CLIMEB</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adult ; Aged ; Aged, 80 and over ; Algorithms ; Chest computed tomography ; Combined multi-kernel ; Female ; Humans ; Image Processing, Computer-Assisted - methods ; Lung - diagnostic imaging ; Lung diseases ; Male ; Middle Aged ; Noise ; Observer Variation ; Patients ; Radiographic Image Interpretation, Computer-Assisted ; Radiography, Thoracic ; Radiology ; Radiology - methods ; Reconstruction kernel ; Retrospective Studies ; Tomography ; Tomography, X-Ray Computed ; Window settings</subject><ispartof>Clinical imaging, 2014-03, Vol.38 (2), p.104-108</ispartof><rights>Elsevier Inc.</rights><rights>2014 Elsevier Inc.</rights><rights>Copyright © 2014 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c484t-77869470467361b6aad90b5e350427dc7fe1ec5b738619ca40cab8592f5c94e43</citedby><cites>FETCH-LOGICAL-c484t-77869470467361b6aad90b5e350427dc7fe1ec5b738619ca40cab8592f5c94e43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0899707113003161$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24361172$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Takagi, Satoshi</creatorcontrib><creatorcontrib>Nagase, Hiroyuki</creatorcontrib><creatorcontrib>Hayashi, Tatsuya</creatorcontrib><creatorcontrib>Kita, Tamotsu</creatorcontrib><creatorcontrib>Hayashi, Katsumi</creatorcontrib><creatorcontrib>Sanada, Shigeru</creatorcontrib><creatorcontrib>Koike, Masayuki</creatorcontrib><title>Combined multi-kernel chest computed tomography images optimized for depicting both lung and soft tissue</title><title>Clinical imaging</title><addtitle>Clin Imaging</addtitle><description>Abstract Purpose To evaluate the quality of our improved multi-kernel chest computed tomography (CT) images. Methods A random sample of 50 normal patients was retrospectively selected from those who underwent chest CT scans between January 2010 and July 2010. Normal lung structures were divided into six categories, and two radiologists independently compared with lung images. Results The improved multi-kernel images were displayed identically to soft tissue images on soft tissue window settings and were evaluated as equal to lung images on lung window settings. Conclusions This improved multi-kernel technique required fewer stored images and simplified examinations of chest CT.</description><subject>Adult</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Algorithms</subject><subject>Chest computed tomography</subject><subject>Combined multi-kernel</subject><subject>Female</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Lung - diagnostic imaging</subject><subject>Lung diseases</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Noise</subject><subject>Observer Variation</subject><subject>Patients</subject><subject>Radiographic Image Interpretation, Computer-Assisted</subject><subject>Radiography, Thoracic</subject><subject>Radiology</subject><subject>Radiology - methods</subject><subject>Reconstruction kernel</subject><subject>Retrospective Studies</subject><subject>Tomography</subject><subject>Tomography, X-Ray Computed</subject><subject>Window settings</subject><issn>0899-7071</issn><issn>1873-4499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkk1v1DAQhiMEokvhL1SWuHDJ4okdO74g0IovqRIH4Gw5zmTX2yQOtlNp-fU4bAtSL3CypXne-XqnKK6AboGCeH3c2sFNbjT7bUWBbQG2lKpHxQYayUrOlXpcbGijVCmphIviWYxHmoWKy6fFRcWZAJDVpjjs_Ni6CTsyLkNy5Q2GCQdiDxgTsX6cl5RjyY9-H8x8OJG1JEbi5-RG9zPHeh9Ih7OzyU170vp0IMOSf2bqSPR9IsnFuODz4klvhogv7t7L4vuH9992n8rrLx8_795dl5Y3PJVSNmuPlAuZW2yFMZ2ibY2sprySnZU9Atq6lawRoKzh1Jq2qVXV11Zx5OyyeHXOOwf_Y8lT6NFFi8NgJvRL1FDTRgqoaPVfKAdWMZHRlw_Qo1_ClAdZKcEbSnmTKXGmbPAxBuz1HPK-wkkD1att-qjvbdOrbRpAZ9uy8Oou_dKO2P2R3fuUgbdnAPPqbh0GHa3DyWLnAtqkO-_-XePNgxS_MWuGGzxh_DuPjpWm-ut6POvtAKOUgQD2C9eUwMg</recordid><startdate>20140301</startdate><enddate>20140301</enddate><creator>Takagi, Satoshi</creator><creator>Nagase, Hiroyuki</creator><creator>Hayashi, Tatsuya</creator><creator>Kita, Tamotsu</creator><creator>Hayashi, Katsumi</creator><creator>Sanada, Shigeru</creator><creator>Koike, Masayuki</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><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>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><scope>7QO</scope></search><sort><creationdate>20140301</creationdate><title>Combined multi-kernel chest computed tomography images optimized for depicting both lung and soft tissue</title><author>Takagi, Satoshi ; Nagase, Hiroyuki ; Hayashi, Tatsuya ; Kita, Tamotsu ; Hayashi, Katsumi ; Sanada, Shigeru ; Koike, Masayuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c484t-77869470467361b6aad90b5e350427dc7fe1ec5b738619ca40cab8592f5c94e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Algorithms</topic><topic>Chest computed tomography</topic><topic>Combined multi-kernel</topic><topic>Female</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Lung - diagnostic imaging</topic><topic>Lung diseases</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Noise</topic><topic>Observer Variation</topic><topic>Patients</topic><topic>Radiographic Image Interpretation, Computer-Assisted</topic><topic>Radiography, Thoracic</topic><topic>Radiology</topic><topic>Radiology - methods</topic><topic>Reconstruction kernel</topic><topic>Retrospective Studies</topic><topic>Tomography</topic><topic>Tomography, X-Ray Computed</topic><topic>Window settings</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Takagi, Satoshi</creatorcontrib><creatorcontrib>Nagase, Hiroyuki</creatorcontrib><creatorcontrib>Hayashi, Tatsuya</creatorcontrib><creatorcontrib>Kita, Tamotsu</creatorcontrib><creatorcontrib>Hayashi, Katsumi</creatorcontrib><creatorcontrib>Sanada, Shigeru</creatorcontrib><creatorcontrib>Koike, Masayuki</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><jtitle>Clinical imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Takagi, Satoshi</au><au>Nagase, Hiroyuki</au><au>Hayashi, Tatsuya</au><au>Kita, Tamotsu</au><au>Hayashi, Katsumi</au><au>Sanada, Shigeru</au><au>Koike, Masayuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Combined multi-kernel chest computed tomography images optimized for depicting both lung and soft tissue</atitle><jtitle>Clinical imaging</jtitle><addtitle>Clin Imaging</addtitle><date>2014-03-01</date><risdate>2014</risdate><volume>38</volume><issue>2</issue><spage>104</spage><epage>108</epage><pages>104-108</pages><issn>0899-7071</issn><eissn>1873-4499</eissn><coden>CLIMEB</coden><abstract>Abstract Purpose To evaluate the quality of our improved multi-kernel chest computed tomography (CT) images. Methods A random sample of 50 normal patients was retrospectively selected from those who underwent chest CT scans between January 2010 and July 2010. Normal lung structures were divided into six categories, and two radiologists independently compared with lung images. Results The improved multi-kernel images were displayed identically to soft tissue images on soft tissue window settings and were evaluated as equal to lung images on lung window settings. Conclusions This improved multi-kernel technique required fewer stored images and simplified examinations of chest CT.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>24361172</pmid><doi>10.1016/j.clinimag.2013.11.009</doi><tpages>5</tpages></addata></record> |
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| subjects | Adult Aged Aged, 80 and over Algorithms Chest computed tomography Combined multi-kernel Female Humans Image Processing, Computer-Assisted - methods Lung - diagnostic imaging Lung diseases Male Middle Aged Noise Observer Variation Patients Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Radiology Radiology - methods Reconstruction kernel Retrospective Studies Tomography Tomography, X-Ray Computed Window settings |
| title | Combined multi-kernel chest computed tomography images optimized for depicting both lung and soft tissue |
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