PubMed Health⌕ Search

Biomedical subjects

M C Steckner

Publications and source records attributed to M C Steckner.

3 recordsLinked to original sources

Computing the modulation transfer function of a magnetic resonance imager.

A new method for computing the modulation transfer function (MTF) of magnetic resonance (MR) imagers is presented. Previous attempts to compute the MTF of MR images used nonlinear magnitude reconstructed images, resulting in erroneous MTFs. By using complex domain images, the new method produces predisplay MTFs which describe the spatial frequency transfer characteristics of the entire image formation process, except the magnitude operator, eliminating the artifacts previously found in MR imager MTFs. The use of complex domain images results in two-sided MTFs which differentiate the positive and negative frequencies associated with positive and negative phase encoding or positive and negative time relative to the echo formation. Experimental results are presented which confirm the theoretically predicted form of MR imager MTFs and the need for two-sided MTFs.

Magnetic Resonance Imaging↗

A cosine modulation artifact in modulation transfer function computations caused by the misregistration of line spread profiles.

Modulation transfer functions (MTFs) are used to analyze the spatial frequency transfer characteristics of medical imaging systems. By definition, accurate MTFs should not include the effects of image noise and they should not be aliased. Therefore, many techniques used to compute MTFs register and average together multiple profiles to improve both signal to noise and/or eliminate aliasing. It is demonstrated that improper registration of individual profiles can cause errors of up to 100% in the MTF. Computer modelling shows that a maximum allowable error of 2% in the MTF requires a registration precision of +/- 1/9 of a pixel for each profile, if the profile was sampled at twice the cutoff frequency of the MTF. One suggested registration method, demonstrated with experimental magnetic resonance image data, is 1.5 times more accurate than the minimum requirement.

Algorithms↗