Medical image is often rich in pixels with the same intensity as the impulse noise so that medical image restoration in the presence of impulse noise is remarkably difficult.To gain a better capability of impulse noise reduction and structure preservation for medical image than the state-of-the-art filters in literatures,we propose a dual iterative equidistant mean filter (DIEMF) for medical image restoration.In the proposed method,an equidistant neighborhood is proposed for noise detection and removal processing;the noise detector discriminates noisy pixel from noise free ones by the averaged absolute difference between the neighboring non-extreme pixels and central pixel circularly,as well as majority rule;the noise removal technique uses adaptive and dual iterative method,takes the mean of noise free pixels and previous restored pixels in equidistant neighborhood as the estimated intensity of central noisy pixel,taking full advantage of the nearest previous restored pixels.Experimental results shown that the proposed method outperforms the state-of-the-art methods in noise reduction and structure preservation,especially for low noise level,it shows remarkable superiority over the state-of-the-art filters.