Helical interpolation or weighting functions used in most multi-slice computed tomography (MSCT) today are object independent. Although these algorithms have been shown to perform satisfactorily in most clinical settings, recent investigations have revealed significant image artifacts under special conditions. These artifacts are generated mainly when scanning objects wiht large variations at high helical pitches. In this paper, we present an adaptive interpolation approach that produces effective artifact reduction while keeping the SSP impact to a minimum. In the proposed scheme, two interplations are performed for each projection sample. The first interpolation has the property of producint excellent SSP while the second interpolation has the property of image artifacts suppression. The projection samples generated by the two interpolation processes are then compared and a differential signal is produced. The final interpolated projection is the weighted sum of the two interpolations, with the weight being derived from a scaling function. Extensive phantom and patient studies were conducted. A thin-disc phantom experiment shows that the proposed scheme produces identical SSP as compared to the first interpolation. Experiments with phantoms and clinical studies also show that the adaptive interpolation approach produces significantly reduced image artifacts as compared to the existing algorithms.