Learn More
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(More)
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(More)
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(More)
The exposure index (EI) gives a feedback to radiographers on the image quality in digital radiography, but its estimation on clinical images raises many challenges. In this paper we provide a critical overview of state of the art methods that address this problem and we show that more robust results can be obtained by detecting anatomical structures. This(More)
Marginal, often contaminated, sites exist in large areas across the world as a result of historic activities such as industry, transportation and mineral extraction. Remediation, or other improvements, of these sites is typically only considered for sites with high exploitation pressure and those posing the highest risks to human health or the environment.(More)
  • 1