In X-ray interventional imaging, improved denoising enables lower X-ray dose and better visualization, resulting in increased confidence in the therapeutic act. This article focuses on the denoising of fluoroscopic image sequences in interventional cardiology. The challenge with these images is the need to preserve fine details in terms of size and contrast, representing the tools manipulated by the operator. These tools superimpose over an anatomical background. This context drives us to propose an algorithm based on spatial-temporal filtering conditioned by a feature of interest map. Based on the confidence in the feature detection our algorithm will either filter, preserve or enhance the image content. Our method is fast and compares very favorably with state of the art methods both quantitatively on synthetic data and perceptually on clinical data.