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Denoising is a crucial step used to increase image quality and to improve performance of all the tasks needed for quantitative imaging analysis. The main challenge is to remove noise component while keeping the integrity of relevant image information. This later aspect is important especially in context of medical image processing. To address this issue, the well-known Non-local Means filter (NLM) has been adapted to medical image analysis. First, the NLM filter has been extended to 3D Magnetic Resonance images (MRI) and diffusion-weighted MRI (DWI). MRI specificities have been taken into account such as Rician noise, non-stationary noise and image dimensionality. Second, a Bayesian definition of the NLM filter has been proposed in order to adapt the NLM filter to ultrasound imaging. Finally, a new collaborative framework has been proposed to multi-photon image filtering.

Magnetic Resonance Image Denoising

Speckle Reduction for Ultrasound Imaging

Multi-photon Microscopy Filtering