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Denoising and contrast enhancement play key roles in optimizing the trade-off between image quality and X-ray dose. However, these tasks present multiple challenges raised by noise level, low visibility of fine anatomical structures, heterogeneous conditions due to different exposure parameters, and patient characteristics. This work proposes a new method to address these challenges. We first introduce...
A multi-scale (MS) decomposition method for contrast enhancement of Micro Dose (MD) X-ray images is presented in this paper. First, we get a denoised version of the input exploiting a non-local means filter with adaptable parameters setting that we defined in a former approach. Then, the MS representations of the input and of its de-noised version are combined to obtain an optimal image in terms of...
A denoising method is proposed for full body X-ray images, acquired under low dose conditions. The suggested algorithm is based on a non local means filter adapted to the statistics of Poisson noise. A new feature of the method is to locally set the filtering parameters in order to denoise while preserving details in low absorption regions. Thus, we propose to adapt the denoising parameters for each...
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