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Robust estimation of diffusion models in presence of local artefacts that corrupt only a subset of gradient directions is essential in diffusion weighted imaging to accurately assess the brain connectivity and white-matter characteristics. In this work we investigate the estimation of diffusion tensors in the Random Sample Consensus (RANSAC) paradigm. First, we show that it enables robust estimation...
The amount of visceral abdominal fat is correlated with the risk for hypertension and diabetes. In this work, an obesity study is monitored with continuously moving table whole body MRI equipped with surface coils and using the Dixon fat/water contrast and reconstruction. A method is presented for the repeatable and reliable differentiation of the imaged abdominal fat into subcutaneous and visceral...
Ultrasound image resolution enhancement is an ongoing challenge to date. Though many works have been performed using device-based approach, there exists few works dealing with post-processing methods. This paper investigates a technique based on the Alternating Direction Method of Multipliers for the resolution enhancement in ultrasound imaging, which includes the deblurring and denoising tasks. We...
In this article, we are interested in restoring images from 3D fluorescence microscopy. In fact, these images are affected by a depth-variant blur due to light refraction phenomenon. We present and compare two different restoration strategies for that problem. The first one is based on multiple deconvolutions with depth-invariant blur functions and the second one consists in using a depth-variant...
We investigate a non quadratic regularizer that is based on the Hessian operator for dealing with the restoration of 3-D images in a variational framework. We show that the regularizer under study is a valid extension of the total-variation (TV) functional, in the sense that it retains its favorable properties while following a similar underlying principle. We argue that the new functional is well...
In this paper we propose a blind deconvolution algorithm for wide field fluorescence microscopy. The 3D PSF is modeled after a parametrized pupil function. The PSF parameters are estimated jointly with the object in a maximum a posteriori framework. We illustrate the performances of our algorithm on experimental data and show significant resolution improvement notably along the depth. Quantitative...
In this simulation study, an engineered point-spread function (PSF) with reduced depth variability (due to depth-induced aberrations) was applied to three-dimensional computational optical-sectioning microscopy (COSM) imaging to investigate its impact on image restoration. Intermediate synthetic images from PSF-engineered COSM in the presence of aberrations were computed and then processed using a...
The Richardson-Lucy algorithm is one of the most important algorithms in the image deconvolution area. However, one of its drawbacks is slow convergence. A very significant acceleration is obtained by the technique proposed by Biggs and Andrews (BA), which is implemented in the deconvlucy function of the Image Processing MATLAB toolbox. The BA method was developed heuristically with no proof of convergence...
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