An estimation method for improved extraction of the decay curve signal from CPMG-like measurements with a unilateral scanner

Unilateral NMR devices are valuable tools used to study non-invasively arbitrarily-sized objects. They have been utilized in various applications, including non-destructive testing and well logging. However, measurements with such scanners are characterized by a low sensitivity, which is mainly the result of the low and inhomogeneous magnetic field B₀. The resulting poor signal to noise ratio (SNR) is a prominent limitation, as it deteriorates the accuracy of data analysis. Improving the SNR is typically done by the use of averaging repetitions that result in too long scan times. This work presents a statistical signal-processing method that can improve the sensitivity of a Carr-Purcell-Meiboom-Gill (CPMG)-like sequence for measurements of transverse-relaxation with unilateral scanners. The method improves the extraction of the decay curve from the noisy data. This is done by exploiting the redundancy in the acquired signal and by the use of the noise characteristics, which are both incorporated into a weighted least-squares estimation approach. This technique is especially effective in applications where RF shielding is not in use, and the measurements are corrupted by dominant non-white noise. The method performance was evaluated with a series of CPMG-like measurements applied on two samples. Decay curves were extracted from each measurement with the proposed method and were compared to a conventional extraction of the decay curve. All measurements showed a significant improvement in the accuracy of estimation of the decaying signal. Thus, the improvement in the sensitivity can be translated into a reduction in the acquisition times (by reducing the need in averaging repetitions) or to a more accurate fitting process of the traverse relaxation distribution.