Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study
Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detec...
Ausführliche Beschreibung
Autor*in: |
Tanaka, Rie [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2010 |
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Schlagwörter: |
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Anmerkung: |
© CARS 2010 |
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Übergeordnetes Werk: |
Enthalten in: International journal of computer assisted radiology and surgery - Berlin : Springer, 2006, 6(2010), 1 vom: 13. Juni, Seite 103-110 |
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Übergeordnetes Werk: |
volume:6 ; year:2010 ; number:1 ; day:13 ; month:06 ; pages:103-110 |
Links: |
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DOI / URN: |
10.1007/s11548-010-0491-y |
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Katalog-ID: |
SPR02069881X |
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245 | 1 | 0 | |a Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study |
264 | 1 | |c 2010 | |
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520 | |a Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. | ||
650 | 4 | |a Functional imaging |7 (dpeaa)DE-He213 | |
650 | 4 | |a Flat-panel detector |7 (dpeaa)DE-He213 | |
650 | 4 | |a Ventilation |7 (dpeaa)DE-He213 | |
650 | 4 | |a Computer analysis |7 (dpeaa)DE-He213 | |
650 | 4 | |a Chest radiography |7 (dpeaa)DE-He213 | |
700 | 1 | |a Sanada, Shigeru |4 aut | |
700 | 1 | |a Fujimura, Masaki |4 aut | |
700 | 1 | |a Yasui, Masahide |4 aut | |
700 | 1 | |a Tsuji, Shiro |4 aut | |
700 | 1 | |a Hayashi, Norio |4 aut | |
700 | 1 | |a Okamoto, Hiroyuki |4 aut | |
700 | 1 | |a Nanbu, Yuko |4 aut | |
700 | 1 | |a Matsui, Osamu |4 aut | |
773 | 0 | 8 | |i Enthalten in |t International journal of computer assisted radiology and surgery |d Berlin : Springer, 2006 |g 6(2010), 1 vom: 13. Juni, Seite 103-110 |w (DE-627)512299250 |w (DE-600)2235881-X |x 1861-6429 |7 nnns |
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10.1007/s11548-010-0491-y doi (DE-627)SPR02069881X (SPR)s11548-010-0491-y-e DE-627 ger DE-627 rakwb eng Tanaka, Rie verfasserin aut Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2010 Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. Functional imaging (dpeaa)DE-He213 Flat-panel detector (dpeaa)DE-He213 Ventilation (dpeaa)DE-He213 Computer analysis (dpeaa)DE-He213 Chest radiography (dpeaa)DE-He213 Sanada, Shigeru aut Fujimura, Masaki aut Yasui, Masahide aut Tsuji, Shiro aut Hayashi, Norio aut Okamoto, Hiroyuki aut Nanbu, Yuko aut Matsui, Osamu aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 6(2010), 1 vom: 13. Juni, Seite 103-110 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:6 year:2010 number:1 day:13 month:06 pages:103-110 https://dx.doi.org/10.1007/s11548-010-0491-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2010 1 13 06 103-110 |
spelling |
10.1007/s11548-010-0491-y doi (DE-627)SPR02069881X (SPR)s11548-010-0491-y-e DE-627 ger DE-627 rakwb eng Tanaka, Rie verfasserin aut Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2010 Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. Functional imaging (dpeaa)DE-He213 Flat-panel detector (dpeaa)DE-He213 Ventilation (dpeaa)DE-He213 Computer analysis (dpeaa)DE-He213 Chest radiography (dpeaa)DE-He213 Sanada, Shigeru aut Fujimura, Masaki aut Yasui, Masahide aut Tsuji, Shiro aut Hayashi, Norio aut Okamoto, Hiroyuki aut Nanbu, Yuko aut Matsui, Osamu aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 6(2010), 1 vom: 13. Juni, Seite 103-110 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:6 year:2010 number:1 day:13 month:06 pages:103-110 https://dx.doi.org/10.1007/s11548-010-0491-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2010 1 13 06 103-110 |
allfields_unstemmed |
10.1007/s11548-010-0491-y doi (DE-627)SPR02069881X (SPR)s11548-010-0491-y-e DE-627 ger DE-627 rakwb eng Tanaka, Rie verfasserin aut Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2010 Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. Functional imaging (dpeaa)DE-He213 Flat-panel detector (dpeaa)DE-He213 Ventilation (dpeaa)DE-He213 Computer analysis (dpeaa)DE-He213 Chest radiography (dpeaa)DE-He213 Sanada, Shigeru aut Fujimura, Masaki aut Yasui, Masahide aut Tsuji, Shiro aut Hayashi, Norio aut Okamoto, Hiroyuki aut Nanbu, Yuko aut Matsui, Osamu aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 6(2010), 1 vom: 13. Juni, Seite 103-110 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:6 year:2010 number:1 day:13 month:06 pages:103-110 https://dx.doi.org/10.1007/s11548-010-0491-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2010 1 13 06 103-110 |
allfieldsGer |
10.1007/s11548-010-0491-y doi (DE-627)SPR02069881X (SPR)s11548-010-0491-y-e DE-627 ger DE-627 rakwb eng Tanaka, Rie verfasserin aut Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2010 Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. Functional imaging (dpeaa)DE-He213 Flat-panel detector (dpeaa)DE-He213 Ventilation (dpeaa)DE-He213 Computer analysis (dpeaa)DE-He213 Chest radiography (dpeaa)DE-He213 Sanada, Shigeru aut Fujimura, Masaki aut Yasui, Masahide aut Tsuji, Shiro aut Hayashi, Norio aut Okamoto, Hiroyuki aut Nanbu, Yuko aut Matsui, Osamu aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 6(2010), 1 vom: 13. Juni, Seite 103-110 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:6 year:2010 number:1 day:13 month:06 pages:103-110 https://dx.doi.org/10.1007/s11548-010-0491-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2010 1 13 06 103-110 |
allfieldsSound |
10.1007/s11548-010-0491-y doi (DE-627)SPR02069881X (SPR)s11548-010-0491-y-e DE-627 ger DE-627 rakwb eng Tanaka, Rie verfasserin aut Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © CARS 2010 Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. Functional imaging (dpeaa)DE-He213 Flat-panel detector (dpeaa)DE-He213 Ventilation (dpeaa)DE-He213 Computer analysis (dpeaa)DE-He213 Chest radiography (dpeaa)DE-He213 Sanada, Shigeru aut Fujimura, Masaki aut Yasui, Masahide aut Tsuji, Shiro aut Hayashi, Norio aut Okamoto, Hiroyuki aut Nanbu, Yuko aut Matsui, Osamu aut Enthalten in International journal of computer assisted radiology and surgery Berlin : Springer, 2006 6(2010), 1 vom: 13. Juni, Seite 103-110 (DE-627)512299250 (DE-600)2235881-X 1861-6429 nnns volume:6 year:2010 number:1 day:13 month:06 pages:103-110 https://dx.doi.org/10.1007/s11548-010-0491-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 6 2010 1 13 06 103-110 |
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Enthalten in International journal of computer assisted radiology and surgery 6(2010), 1 vom: 13. Juni, Seite 103-110 volume:6 year:2010 number:1 day:13 month:06 pages:103-110 |
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Functional imaging Flat-panel detector Ventilation Computer analysis Chest radiography |
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International journal of computer assisted radiology and surgery |
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Tanaka, Rie @@aut@@ Sanada, Shigeru @@aut@@ Fujimura, Masaki @@aut@@ Yasui, Masahide @@aut@@ Tsuji, Shiro @@aut@@ Hayashi, Norio @@aut@@ Okamoto, Hiroyuki @@aut@@ Nanbu, Yuko @@aut@@ Matsui, Osamu @@aut@@ |
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This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. 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Tanaka, Rie |
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Tanaka, Rie misc Functional imaging misc Flat-panel detector misc Ventilation misc Computer analysis misc Chest radiography Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study |
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Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study Functional imaging (dpeaa)DE-He213 Flat-panel detector (dpeaa)DE-He213 Ventilation (dpeaa)DE-He213 Computer analysis (dpeaa)DE-He213 Chest radiography (dpeaa)DE-He213 |
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Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study |
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Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study |
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Tanaka, Rie Sanada, Shigeru Fujimura, Masaki Yasui, Masahide Tsuji, Shiro Hayashi, Norio Okamoto, Hiroyuki Nanbu, Yuko Matsui, Osamu |
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ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study |
title_auth |
Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study |
abstract |
Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. © CARS 2010 |
abstractGer |
Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. © CARS 2010 |
abstract_unstemmed |
Purpose Decreased ventilation is observed on chest radiographs as small changes in X-ray translucency, and ventilatory impairments can therefore be detected by analyzing the distribution of respiratory-induced changes in pixel value. This study was performed to develop a ventilatory impairment detection method based on the distribution of respiratory-induced changes in pixel values. Methods Sequential chest radiographs during respiration were obtained using a dynamic flat panel detector system. Respiratory-induced changes in pixel value were measured in each local area and then compared for symmetrical positions in both lungs, which were located at the same distance from the axis of the thorax at the same level. The right–left symmetry was assessed in 20 clinical cases (Abnormal, 14; Normal, 6). Results In normal controls, the distribution was symmetrical, and there were good correlations of the pixel value changes in both lungs at symmetrical positions (r = 0.66±0.05). In contrast, abnormal cases did not show a symmetrical distribution of pixel value changes (r = 0.40±0.23) due to ventilation abnormalities observed as reductions in pixel value changes. Conclusions Ventilatory impairment could be detected as deviation from the right–left symmetry of respiratory-induced changes in pixel value. In particular, the present method could be useful for detecting unilateral abnormalities. However, to detect bilateral abnormalities, further studies are required to develop multilevel detection methods combined with several methods of pattern analysis. © CARS 2010 |
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title_short |
Ventilatory impairment detection based on distribution of respiratory-induced changes in pixel values in dynamic chest radiography: a feasibility study |
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https://dx.doi.org/10.1007/s11548-010-0491-y |
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Sanada, Shigeru Fujimura, Masaki Yasui, Masahide Tsuji, Shiro Hayashi, Norio Okamoto, Hiroyuki Nanbu, Yuko Matsui, Osamu |
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Sanada, Shigeru Fujimura, Masaki Yasui, Masahide Tsuji, Shiro Hayashi, Norio Okamoto, Hiroyuki Nanbu, Yuko Matsui, Osamu |
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512299250 |
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doi_str |
10.1007/s11548-010-0491-y |
up_date |
2024-07-03T17:41:05.037Z |
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score |
7.4002237 |