Maurice Delplanque

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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(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)
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