Designing a compact MRI motion phantom
Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for ev...
Ausführliche Beschreibung
Autor*in: |
Schmiedel Max [verfasserIn] Moeller Anita [verfasserIn] Koch Martin A. [verfasserIn] Mertins Alfred [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2016 |
---|
Schlagwörter: |
---|
Übergeordnetes Werk: |
In: Current Directions in Biomedical Engineering - De Gruyter, 2016, 2(2016), 1, Seite 471-474 |
---|---|
Übergeordnetes Werk: |
volume:2 ; year:2016 ; number:1 ; pages:471-474 |
Links: |
---|
DOI / URN: |
10.1515/cdbme-2016-0104 |
---|
Katalog-ID: |
DOAJ05575368X |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | DOAJ05575368X | ||
003 | DE-627 | ||
005 | 20230502064248.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230227s2016 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1515/cdbme-2016-0104 |2 doi | |
035 | |a (DE-627)DOAJ05575368X | ||
035 | |a (DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 0 | |a Schmiedel Max |e verfasserin |4 aut | |
245 | 1 | 0 | |a Designing a compact MRI motion phantom |
264 | 1 | |c 2016 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
520 | |a Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. | ||
650 | 4 | |a motion artifacts | |
650 | 4 | |a motion phantom | |
650 | 4 | |a mri | |
653 | 0 | |a Medicine | |
653 | 0 | |a R | |
700 | 0 | |a Moeller Anita |e verfasserin |4 aut | |
700 | 0 | |a Koch Martin A. |e verfasserin |4 aut | |
700 | 0 | |a Mertins Alfred |e verfasserin |4 aut | |
773 | 0 | 8 | |i In |t Current Directions in Biomedical Engineering |d De Gruyter, 2016 |g 2(2016), 1, Seite 471-474 |w (DE-627)835382605 |w (DE-600)2835398-5 |x 23645504 |7 nnns |
773 | 1 | 8 | |g volume:2 |g year:2016 |g number:1 |g pages:471-474 |
856 | 4 | 0 | |u https://doi.org/10.1515/cdbme-2016-0104 |z kostenfrei |
856 | 4 | 0 | |u https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0 |z kostenfrei |
856 | 4 | 0 | |u https://doi.org/10.1515/cdbme-2016-0104 |z kostenfrei |
856 | 4 | 2 | |u https://doaj.org/toc/2364-5504 |y Journal toc |z kostenfrei |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_DOAJ | ||
912 | |a SSG-OLC-PHA | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_65 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_4012 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4335 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4367 | ||
912 | |a GBV_ILN_4700 | ||
951 | |a AR | ||
952 | |d 2 |j 2016 |e 1 |h 471-474 |
author_variant |
s m sm m a ma k m a kma m a ma |
---|---|
matchkey_str |
article:23645504:2016----::einnaopcmioi |
hierarchy_sort_str |
2016 |
publishDate |
2016 |
allfields |
10.1515/cdbme-2016-0104 doi (DE-627)DOAJ05575368X (DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0 DE-627 ger DE-627 rakwb eng Schmiedel Max verfasserin aut Designing a compact MRI motion phantom 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. motion artifacts motion phantom mri Medicine R Moeller Anita verfasserin aut Koch Martin A. verfasserin aut Mertins Alfred verfasserin aut In Current Directions in Biomedical Engineering De Gruyter, 2016 2(2016), 1, Seite 471-474 (DE-627)835382605 (DE-600)2835398-5 23645504 nnns volume:2 year:2016 number:1 pages:471-474 https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0 kostenfrei https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/toc/2364-5504 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 471-474 |
spelling |
10.1515/cdbme-2016-0104 doi (DE-627)DOAJ05575368X (DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0 DE-627 ger DE-627 rakwb eng Schmiedel Max verfasserin aut Designing a compact MRI motion phantom 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. motion artifacts motion phantom mri Medicine R Moeller Anita verfasserin aut Koch Martin A. verfasserin aut Mertins Alfred verfasserin aut In Current Directions in Biomedical Engineering De Gruyter, 2016 2(2016), 1, Seite 471-474 (DE-627)835382605 (DE-600)2835398-5 23645504 nnns volume:2 year:2016 number:1 pages:471-474 https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0 kostenfrei https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/toc/2364-5504 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 471-474 |
allfields_unstemmed |
10.1515/cdbme-2016-0104 doi (DE-627)DOAJ05575368X (DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0 DE-627 ger DE-627 rakwb eng Schmiedel Max verfasserin aut Designing a compact MRI motion phantom 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. motion artifacts motion phantom mri Medicine R Moeller Anita verfasserin aut Koch Martin A. verfasserin aut Mertins Alfred verfasserin aut In Current Directions in Biomedical Engineering De Gruyter, 2016 2(2016), 1, Seite 471-474 (DE-627)835382605 (DE-600)2835398-5 23645504 nnns volume:2 year:2016 number:1 pages:471-474 https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0 kostenfrei https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/toc/2364-5504 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 471-474 |
allfieldsGer |
10.1515/cdbme-2016-0104 doi (DE-627)DOAJ05575368X (DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0 DE-627 ger DE-627 rakwb eng Schmiedel Max verfasserin aut Designing a compact MRI motion phantom 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. motion artifacts motion phantom mri Medicine R Moeller Anita verfasserin aut Koch Martin A. verfasserin aut Mertins Alfred verfasserin aut In Current Directions in Biomedical Engineering De Gruyter, 2016 2(2016), 1, Seite 471-474 (DE-627)835382605 (DE-600)2835398-5 23645504 nnns volume:2 year:2016 number:1 pages:471-474 https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0 kostenfrei https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/toc/2364-5504 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 471-474 |
allfieldsSound |
10.1515/cdbme-2016-0104 doi (DE-627)DOAJ05575368X (DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0 DE-627 ger DE-627 rakwb eng Schmiedel Max verfasserin aut Designing a compact MRI motion phantom 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. motion artifacts motion phantom mri Medicine R Moeller Anita verfasserin aut Koch Martin A. verfasserin aut Mertins Alfred verfasserin aut In Current Directions in Biomedical Engineering De Gruyter, 2016 2(2016), 1, Seite 471-474 (DE-627)835382605 (DE-600)2835398-5 23645504 nnns volume:2 year:2016 number:1 pages:471-474 https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0 kostenfrei https://doi.org/10.1515/cdbme-2016-0104 kostenfrei https://doaj.org/toc/2364-5504 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 471-474 |
language |
English |
source |
In Current Directions in Biomedical Engineering 2(2016), 1, Seite 471-474 volume:2 year:2016 number:1 pages:471-474 |
sourceStr |
In Current Directions in Biomedical Engineering 2(2016), 1, Seite 471-474 volume:2 year:2016 number:1 pages:471-474 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
motion artifacts motion phantom mri Medicine R |
isfreeaccess_bool |
true |
container_title |
Current Directions in Biomedical Engineering |
authorswithroles_txt_mv |
Schmiedel Max @@aut@@ Moeller Anita @@aut@@ Koch Martin A. @@aut@@ Mertins Alfred @@aut@@ |
publishDateDaySort_date |
2016-01-01T00:00:00Z |
hierarchy_top_id |
835382605 |
id |
DOAJ05575368X |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ05575368X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502064248.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1515/cdbme-2016-0104</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ05575368X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Schmiedel Max</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Designing a compact MRI motion phantom</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">motion artifacts</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">motion phantom</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">mri</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Moeller Anita</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Koch Martin A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mertins Alfred</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Current Directions in Biomedical Engineering</subfield><subfield code="d">De Gruyter, 2016</subfield><subfield code="g">2(2016), 1, Seite 471-474</subfield><subfield code="w">(DE-627)835382605</subfield><subfield code="w">(DE-600)2835398-5</subfield><subfield code="x">23645504</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:2</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:471-474</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1515/cdbme-2016-0104</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1515/cdbme-2016-0104</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2364-5504</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">2</subfield><subfield code="j">2016</subfield><subfield code="e">1</subfield><subfield code="h">471-474</subfield></datafield></record></collection>
|
author |
Schmiedel Max |
spellingShingle |
Schmiedel Max misc motion artifacts misc motion phantom misc mri misc Medicine misc R Designing a compact MRI motion phantom |
authorStr |
Schmiedel Max |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)835382605 |
format |
electronic Article |
delete_txt_mv |
keep |
author_role |
aut aut aut aut |
collection |
DOAJ |
remote_str |
true |
illustrated |
Not Illustrated |
issn |
23645504 |
topic_title |
Designing a compact MRI motion phantom motion artifacts motion phantom mri |
topic |
misc motion artifacts misc motion phantom misc mri misc Medicine misc R |
topic_unstemmed |
misc motion artifacts misc motion phantom misc mri misc Medicine misc R |
topic_browse |
misc motion artifacts misc motion phantom misc mri misc Medicine misc R |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
cr |
hierarchy_parent_title |
Current Directions in Biomedical Engineering |
hierarchy_parent_id |
835382605 |
hierarchy_top_title |
Current Directions in Biomedical Engineering |
isfreeaccess_txt |
true |
familylinks_str_mv |
(DE-627)835382605 (DE-600)2835398-5 |
title |
Designing a compact MRI motion phantom |
ctrlnum |
(DE-627)DOAJ05575368X (DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0 |
title_full |
Designing a compact MRI motion phantom |
author_sort |
Schmiedel Max |
journal |
Current Directions in Biomedical Engineering |
journalStr |
Current Directions in Biomedical Engineering |
lang_code |
eng |
isOA_bool |
true |
recordtype |
marc |
publishDateSort |
2016 |
contenttype_str_mv |
txt |
container_start_page |
471 |
author_browse |
Schmiedel Max Moeller Anita Koch Martin A. Mertins Alfred |
container_volume |
2 |
format_se |
Elektronische Aufsätze |
author-letter |
Schmiedel Max |
doi_str_mv |
10.1515/cdbme-2016-0104 |
author2-role |
verfasserin |
title_sort |
designing a compact mri motion phantom |
title_auth |
Designing a compact MRI motion phantom |
abstract |
Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. |
abstractGer |
Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. |
abstract_unstemmed |
Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 |
container_issue |
1 |
title_short |
Designing a compact MRI motion phantom |
url |
https://doi.org/10.1515/cdbme-2016-0104 https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0 https://doaj.org/toc/2364-5504 |
remote_bool |
true |
author2 |
Moeller Anita Koch Martin A. Mertins Alfred |
author2Str |
Moeller Anita Koch Martin A. Mertins Alfred |
ppnlink |
835382605 |
mediatype_str_mv |
c |
isOA_txt |
true |
hochschulschrift_bool |
false |
doi_str |
10.1515/cdbme-2016-0104 |
up_date |
2024-07-03T16:49:41.998Z |
_version_ |
1803577334960226304 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ05575368X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230502064248.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1515/cdbme-2016-0104</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ05575368X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ5f1c67db7e5d41da80c12b91cece3fe0</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Schmiedel Max</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Designing a compact MRI motion phantom</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Even today, dealing with motion artifacts in magnetic resonance imaging (MRI) is a challenging task. Image corruption due to spontaneous body motion complicates diagnosis. In this work, an MRI phantom for rigid motion is presented. It is used to generate motion-corrupted data, which can serve for evaluation of blind motion compensation algorithms. In contrast to commercially available MRI motion phantoms, the presented setup works on small animal MRI systems. Furthermore, retrospective gating is performed on the data, which can be used as a reference for novel motion compensation approaches. The motion of the signal source can be reconstructed using motor trigger signals and be utilized as the ground truth for motion estimation. The proposed setup results in motion corrected images. Moreover, the importance of preprocessing the MRI raw data, e.g. phase-drift correction, is demonstrated. The gained knowledge can be used to design an MRI phantom for elastic motion.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">motion artifacts</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">motion phantom</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">mri</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Medicine</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">R</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Moeller Anita</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Koch Martin A.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Mertins Alfred</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Current Directions in Biomedical Engineering</subfield><subfield code="d">De Gruyter, 2016</subfield><subfield code="g">2(2016), 1, Seite 471-474</subfield><subfield code="w">(DE-627)835382605</subfield><subfield code="w">(DE-600)2835398-5</subfield><subfield code="x">23645504</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:2</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:471-474</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1515/cdbme-2016-0104</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/5f1c67db7e5d41da80c12b91cece3fe0</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1515/cdbme-2016-0104</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/2364-5504</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">2</subfield><subfield code="j">2016</subfield><subfield code="e">1</subfield><subfield code="h">471-474</subfield></datafield></record></collection>
|
score |
7.399351 |