Younes Farouj

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We present an algorithm and its fully data-driven extension for noise reduction in ultrasound imaging. The proposed method computes the hyperbolic wavelet transform of the image, before applying a multiscale variance stabilization technique, via a Fisz transformation. This adapts the wavelet coefficients statistics to the wavelet thresholding paradigm. The(More)
In medical applications, stent segmentation in the abdominal aorta has to be carried out in challenging conditions, since one has to deal with noise, low contrast, objects having similar appearances and missing or blurred edges. Variational segmentation methods eases this task by carrying prior information on the target region or on the regularity of its(More)
We present an optical flow technique in a differential projected framework adapted to local myocardial motion estimation from MR Tagged images. The algorithm is based on The Dual Tree design of Hilbert transform pairs of wavelet bases. Such a design allows one to construct several orientationsensitive wavelet filters for better analysis of the complex(More)
We present an optical flow technique in a differential projected framework adapted to local myocardial motion estimation from MR Tagged images. The algorithm is based on the Dual Tree design of Hilbert transform pairs of wavelet bases. Such a design allows one to construct several orientation-sensitive wavelet filters for better analysis of the complex(More)
Resting-state fMRI provides challenging data that needs to be analyzed without knowledge about timing or duration of neuronal events. The “total activation” framework is one recent approach that combines temporal and spatial regularization to deconvolve the fMRI signals; i.e., undo them from the influence of the hemodynamic response. The temporal(More)
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