  Image denoising is getting more significance, especially in Computed
Tomography (CT), which is an important and most common modality in medical
imaging. This is mainly due to that the effectiveness of clinical diagnosis
using CT image lies on the image quality. The denoising technique for CT images
using window-based Multi-wavelet transformation and thresholding shows the
effectiveness in denoising, however, a drawback exists in selecting the closer
windows in the process of window-based multi-wavelet transformation and
thresholding. Generally, the windows of the duplicate noisy image that are
closer to each window of original noisy image are obtained by the checking them
sequentially. This leads to the possibility of missing out very closer windows
and so enhancement is required in the aforesaid process of the denoising
technique. In this paper, we propose a GA-based window selection methodology to
include the denoising technique. With the aid of the GA-based window selection
methodology, the windows of the duplicate noisy image that are very closer to
every window of the original noisy image are extracted in an effective manner.
By incorporating the proposed GA-based window selection methodology, the
denoising the CT image is performed effectively. Eventually, a comparison is
made between the denoising technique with and without the proposed GA-based
window selection methodology.
