A KNOWLEDGE-BASED APPROACH TO MINIMIZE BASE-LINE ROLL IN CHEMICAL-SHIFT IMAGING

A method has been developed to minimize baseline roll in chemical shif t imaging (CSI). The technique is fully automated and employs knowledg e based data processing in the frequency domain. The key feature of th e algorithm is the computation of the ''trough'' and ''ripple'' compon ents in the CSI data. The baseline roll can be regarded as an artifact that appears as a result of the summation of several sinc functions. Using prior knowledge, a mirror component corresponding to the artifac t is created and added to the delayed spectrum. The method compensates for noise and zero-order phase error when computing the roll artifact . The results obtained on implementing the baseline roll minimization procedure on simulated time-delayed spectra indicated that the peak he ights and areas were between 91% and 97% in magnitude when compared wi th the same peaks in the nondelayed spectra. The correction procedure was also assessed on clinical in vivo spectra. Nonlocalized P-31 MR sp ectra of the liver were obtained with and without an acquisition delay of 2.1 ms, and the time delayed spectra subjected to the baseline min imization routine. Metabolite peak heights and areas in the corrected spectra were approximately 94% in magnitude when compared with the sam e peaks in the original nondelayed whole volume spectra. Implementatio n of the baseline minimization procedure on in vivo localized spectra with varying signal to noise ratios produced good results. It takes ap proximately 13 s to implement the baseline roll minimization procedure . In this paper, the technique will be referred to as BaseLine Artifac t Suppression Technique BLAS routine.