Deep learning based denoising methods can significantly reduce image noise at the cost of producing unnaturally smooth images. Typically, natural-looking images are produced by blending a fraction of the acquired noisy image with the denoised image. The blending ratio is set based on visual inspection. This approach impedes workflow and is prone to inter-operator variability. We propose a method to analytically calculate the blending ratio based on a desired SNR value. The proposed method is demonstrated to produce natural-looking denoised images with consistent SNR across head, spine and knee applications.