the filtering of the images above described does not require an actual conversion of the images into frequency space and operation on the frequency space data but that other mathematical techniques such as convolution may be employed to perform the same function in the object space referring now again to fig5 and vector diagram 92 it will be recognized that the filtering process of the data within the cone 64 will attenuate some small amount of non artifact data f i t and thus will not completely eliminate the artifact data f a for example for a given element of the frequency space the component f i t may cancel a portion of f a and thus the filtering of f a f i t will not completely eliminate f a at that point ideally the data within the cone 64 of frequency space data 96 for the soft tissue image 86 would not merely be zeroed but would be augmented somehow to ensure the complete elimination of data comprising the artifact spectra f a augmentation of f a may be accomplished by noting that f a is approximately equal to f i b a that is the in cone data of the frequency space transformation of the bone and air image 88 the reason for this equivalence is the above assumption that the value of f i t is extremely small and that f i f a f i b a f i t accordingly the amount of image artifact f a can be estimated from the value f i b a referring to fig7 this augmentation is performed.