Each of the currently used helical reconstruction algorithms represents one tradeoff selection of the image noise or mA requirement and resultant artifacts versus the width of the section profile. For many applications, the performance tradeoffs different from those existed are desired. In this paper, we present a general framework of incorporating the longitudinal (z) filtration in helical CT reconstruction, which leads to a new class of helical reconstruction algorithms with tunable performance characteristics to suit various applications. The z-filtering algorithm enables us to derive the performance curve of image noise or mA requirement versus the width of the section profile, whereas the existing helical reconstruction algorithms only represent limited discrete samples of the curve. We demonstrate that using a new helical reconstruction algorithm derived from this general framework, a substantial reduction in image noise or mA requirement can be achieved with a slight increase of FWHM of the section profile. Thus for many applications requiring both compact section profile and low image noise or mA requirement, the new algorithm represents a better tradeoff than both the 180 degrees and 360 degrees interpolation algorithms. The new algorithm also offers the following potential clinical benefits: (1) longer x-ray tube life; (2) longer scan duration with less x-ray tube cooling delays--longer volume coverage and/or longer thin-slice scan; (3) less radiation to patient; (4) less image noise; and (5) less helical artifacts. Initial clinical results are also presented.