Methods for calculating multiple point T₁ relaxation images are described and compared. A robust line fitting method is presented and its relevance to high resolution relaxation imaging discussed. Selective removal of data points is demonstrated to reduce systematic errors in linear models. A non-linear least squares iterative method is also developed and implemented. The results include simulated data, clinical images and a phantom study. Several of the methods are substantial improvements on existing linear techniques. The increased quality and consistency of the calculated images make them particularly appropriate for automated pattern recognition.