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. Author manuscript; available in PMC: 2009 Jun 29.
Published in final edited form as: Med Image Comput Comput Assist Interv. 2008;11(Pt 2):271–279. doi: 10.1007/978-3-540-85990-1_33

Fig. 2.

Fig. 2

Results of the Classifier and Fieldmap Estimation Algorithm. The CT (a) is thresholded to produce an air/tissue map (b) and the T1 (c) is segmented using the MR classifier (d). The CT-derived fieldmap (e, g-top) and MR-derived fieldmap (f, g-bottom) show excellent agreement. The absolute difference in the CT and MR derived fieldmaps is given in units of voxel shift in row 1 of the table and in Hz in row 2. P90 is the 90th percentile, etc. Results of Koch et al. [14] are given in Hz in row 3. The acquired fieldmap (h,j-top) and final MR-derived fieldmap (with shim)(i,j-bottom) show good overall agreement. The scale of the fieldmaps is ±200 Hz.