guest ::
| Home > Publications database > Mask-Adapted Background Field Removal for Artifact Reduction in Quantitative Susceptibility Mapping of the Prostate. > print |
| Home > Publications database > Mask-Adapted Background Field Removal for Artifact Reduction in Quantitative Susceptibility Mapping of the Prostate. > print |
| 001 | 181419 | ||
| 005 | 20240301130857.0 | ||
| 024 | 7 | _ | |a 10.18383/j.tom.2017.00005 |2 doi |
| 024 | 7 | _ | |a pmid:30042974 |2 pmid |
| 024 | 7 | _ | |a pmc:PMC6024456 |2 pmc |
| 024 | 7 | _ | |a 2379-1381 |2 ISSN |
| 024 | 7 | _ | |a 2379-139X |2 ISSN |
| 037 | _ | _ | |a DKFZ-2022-01987 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Straub, Sina |0 P:(DE-He78)4e04dcea1b6a4449a8fa005bcf36322b |b 0 |e First author |u dkfz |
| 245 | _ | _ | |a Mask-Adapted Background Field Removal for Artifact Reduction in Quantitative Susceptibility Mapping of the Prostate. |
| 260 | _ | _ | |a Ann Arbor, Michigan |c 2017 |b Grapho Publications |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1661330848_30652 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
| 336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a We propose an alternative processing method for quantitative susceptibility mapping of the prostate that reduces artifacts and enables better visibility and quantification of calcifications and other lesions. Three-dimensional gradient-echo magnetic resonance data were obtained from 26 patients at 3 T who previously received a planning computed tomography of the prostate. Phase images were unwrapped using Laplacian-based phase unwrapping. The background field was removed with the V-SHARP method using tissue masks for the entire abdomen (Method 1) and masks that excluded bone and the rectum (Method 2). Susceptibility maps were calculated with the iLSQR method. The quality of susceptibility maps was assessed by one radiologist and two physicists who rated the data for visibility of lesions and data quality on a scale from 1 (poor) to 4 (good). The readers rated susceptibility maps computed with Method 2 to be, on average, better for visibility of lesions with a score of 2.9 ± 1.1 and image quality with a score of 2.8 ± 0.8 compared with maps computed with Method 1 (2.4 ± 1.2/2.3 ± 1.0). Regarding strong artifacts, these could be removed using adapted masks, and the susceptibility values seemed less biased by the artifacts. Thus, using an adapted mask for background field removal when calculating susceptibility maps of the prostate from phase data reduces artifacts and improves visibility of lesions. |
| 536 | _ | _ | |a 315 - Imaging and radiooncology (POF3-315) |0 G:(DE-HGF)POF3-315 |c POF3-315 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
| 650 | _ | 7 | |a artifact reduction |2 Other |
| 650 | _ | 7 | |a background field removal |2 Other |
| 650 | _ | 7 | |a calcification |2 Other |
| 650 | _ | 7 | |a prostate cancer |2 Other |
| 650 | _ | 7 | |a quantitative susceptibility mapping |2 Other |
| 700 | 1 | _ | |a Emmerich, Julian |0 P:(DE-He78)cb524d7857f62988258612fc095c2ae0 |b 1 |
| 700 | 1 | _ | |a Schlemmer, Heinz-Peter |0 P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec |b 2 |u dkfz |
| 700 | 1 | _ | |a Maier-Hein, Klaus H |0 P:(DE-He78)33c74005e1ce56f7025c4f6be15321b3 |b 3 |u dkfz |
| 700 | 1 | _ | |a Ladd, Mark E |0 P:(DE-He78)022611a2317e4de40fd912e0a72293a8 |b 4 |u dkfz |
| 700 | 1 | _ | |a Röthke, Matthias |0 P:(DE-He78)3d11afed6b72f876ad1bba9418e30dac |b 5 |
| 700 | 1 | _ | |a Bonekamp, David |0 P:(DE-He78)ea098e4d78abeb63afaf8c25ec6d6d93 |b 6 |u dkfz |
| 700 | 1 | _ | |a Laun, Frederik |0 P:(DE-He78)b709e6df1ec6b63e5ffad4c8131f6f4d |b 7 |e Last author |
| 773 | _ | _ | |a 10.18383/j.tom.2017.00005 |g Vol. 3, no. 2, p. 96 - 100 |0 PERI:(DE-600)2857000-5 |n 2 |p 96 - 100 |t Tomography |v 3 |y 2017 |x 2379-1381 |
| 909 | C | O | |o oai:inrepo02.dkfz.de:181419 |p VDB |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 0 |6 P:(DE-He78)4e04dcea1b6a4449a8fa005bcf36322b |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 1 |6 P:(DE-He78)cb524d7857f62988258612fc095c2ae0 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 2 |6 P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 3 |6 P:(DE-He78)33c74005e1ce56f7025c4f6be15321b3 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 4 |6 P:(DE-He78)022611a2317e4de40fd912e0a72293a8 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 5 |6 P:(DE-He78)3d11afed6b72f876ad1bba9418e30dac |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 6 |6 P:(DE-He78)ea098e4d78abeb63afaf8c25ec6d6d93 |
| 910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 7 |6 P:(DE-He78)b709e6df1ec6b63e5ffad4c8131f6f4d |
| 913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF3-310 |0 G:(DE-HGF)POF3-315 |3 G:(DE-HGF)POF3 |2 G:(DE-HGF)POF3-300 |4 G:(DE-HGF)POF |v Imaging and radiooncology |x 0 |
| 914 | 1 | _ | |y 2017 |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b TOMOGRAPHY : 2019 |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1030 |2 StatID |b Current Contents - Life Sciences |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0160 |2 StatID |b Essential Science Indicators |d 2021-02-04 |
| 915 | _ | _ | |a WoS |0 StatID:(DE-HGF)0113 |2 StatID |b Science Citation Index Expanded |d 2021-02-04 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2021-02-04 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2021-02-04 |
| 920 | 1 | _ | |0 I:(DE-He78)E020-20160331 |k E020 |l E020 Med. Physik in der Radiologie |x 0 |
| 920 | 1 | _ | |0 I:(DE-He78)E010-20160331 |k E010 |l E010 Radiologie |x 1 |
| 920 | 1 | _ | |0 I:(DE-He78)E132-20160331 |k E132 |l Medizinische Bildverarbeitung |x 2 |
| 920 | 1 | _ | |0 I:(DE-He78)E230-20160331 |k E230 |l E230 Medizinische Bildverarbeitung |x 3 |
| 980 | _ | _ | |a journal |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-He78)E020-20160331 |
| 980 | _ | _ | |a I:(DE-He78)E010-20160331 |
| 980 | _ | _ | |a I:(DE-He78)E132-20160331 |
| 980 | _ | _ | |a I:(DE-He78)E230-20160331 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|