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000181419 0247_ $$2doi$$a10.18383/j.tom.2017.00005
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000181419 0247_ $$2ISSN$$a2379-1381
000181419 0247_ $$2ISSN$$a2379-139X
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000181419 041__ $$aEnglish
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000181419 1001_ $$0P:(DE-He78)4e04dcea1b6a4449a8fa005bcf36322b$$aStraub, Sina$$b0$$eFirst author$$udkfz
000181419 245__ $$aMask-Adapted Background Field Removal for Artifact Reduction in Quantitative Susceptibility Mapping of the Prostate.
000181419 260__ $$aAnn Arbor, Michigan$$bGrapho Publications$$c2017
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000181419 520__ $$aWe propose an alternative processing method for quantitative susceptibility mapping of the prostate that reduces artifacts and enables better visibility and quantification of calcifications and other lesions. Three-dimensional gradient-echo magnetic resonance data were obtained from 26 patients at 3 T who previously received a planning computed tomography of the prostate. Phase images were unwrapped using Laplacian-based phase unwrapping. The background field was removed with the V-SHARP method using tissue masks for the entire abdomen (Method 1) and masks that excluded bone and the rectum (Method 2). Susceptibility maps were calculated with the iLSQR method. The quality of susceptibility maps was assessed by one radiologist and two physicists who rated the data for visibility of lesions and data quality on a scale from 1 (poor) to 4 (good). The readers rated susceptibility maps computed with Method 2 to be, on average, better for visibility of lesions with a score of 2.9 ± 1.1 and image quality with a score of 2.8 ± 0.8 compared with maps computed with Method 1 (2.4 ± 1.2/2.3 ± 1.0). Regarding strong artifacts, these could be removed using adapted masks, and the susceptibility values seemed less biased by the artifacts. Thus, using an adapted mask for background field removal when calculating susceptibility maps of the prostate from phase data reduces artifacts and improves visibility of lesions.
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000181419 650_7 $$2Other$$aartifact reduction
000181419 650_7 $$2Other$$abackground field removal
000181419 650_7 $$2Other$$acalcification
000181419 650_7 $$2Other$$aprostate cancer
000181419 650_7 $$2Other$$aquantitative susceptibility mapping
000181419 7001_ $$0P:(DE-He78)cb524d7857f62988258612fc095c2ae0$$aEmmerich, Julian$$b1
000181419 7001_ $$0P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec$$aSchlemmer, Heinz-Peter$$b2$$udkfz
000181419 7001_ $$0P:(DE-He78)33c74005e1ce56f7025c4f6be15321b3$$aMaier-Hein, Klaus H$$b3$$udkfz
000181419 7001_ $$0P:(DE-He78)022611a2317e4de40fd912e0a72293a8$$aLadd, Mark E$$b4$$udkfz
000181419 7001_ $$0P:(DE-He78)3d11afed6b72f876ad1bba9418e30dac$$aRöthke, Matthias$$b5
000181419 7001_ $$0P:(DE-He78)ea098e4d78abeb63afaf8c25ec6d6d93$$aBonekamp, David$$b6$$udkfz
000181419 7001_ $$0P:(DE-He78)b709e6df1ec6b63e5ffad4c8131f6f4d$$aLaun, Frederik$$b7$$eLast author
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