equation and added to the phase image creating fig6 d where x y are image coordinates in the range 0 1 the original wells and guillemaud algorithms were run independently and then in conjunction with the van leemput enhancements the resulting root mean square u201c rms u201d error between the extracted water signal and known water signal were calculated and are displayed in table 1 the original dixon technique is also included in the table because the algorithm does not estimate the bias field it is not included in the results the guillemaud algorithm provided the most accurate performance on the mathematical phantom data and the addition of the u201c other u201d class improved the original wells results in the phantom study this improvement is demonstrated quantitatively in the volunteer data described herein below images of two normal healthy volunteers were acquired one dataset was of the head and another was of the legs as illustrated in fig7 the head dataset was acquired using a gre sequence on a 1 5 t ge signa scanner with te tr of 6 1 msec 700 msec and 42 degrees flip angle magnitude real and imaginary images were saved by the scanner the leg dataset was acquired on the same scanner.