1. A method for iteratively reconstructing an image of a subject from undersampled image data, the steps of the method comprising: a) acquiring, with an imaging system, undersampled image data from a subject; b) reconstructing from the acquired undersampled image data, an image of the subject; c) producing from the image of the subject, a number of similarity clusters; d) iteratively reconstructing a target image of the subject by: i) processing the similarity clusters; ii) producing a number of weighting values that are related to the processing used in step i); iii) producing an estimate image of the subject by combining the processed similarity clusters using the number of weighting values; iv) evaluating a stopping criterion; v) storing the estimate image of the subject as a target image of the subject when the stopping criterion is satisfied and when the stopping criterion is not satisfied: updating the estimate image by enforcing a consistency condition on the estimate image by forward projecting the estimate image into estimate image data, forming combined data by combining the estimate image data with the undersampled image data acquired in step a), and reconstructing the updated estimate image from the combined data; and repeating steps i)-iv) until the stopping criterion is satisfied; whereby the target image of the subject is substantially free of artifacts attributable to aliasing and noise.