Centre National De La Recherche Scientifique

Inria Institut National De Recherche En Informatique Et En Automatique

Université De Rennes 1

Institut National De La Sante Et De La Recherche Medicale

Institut National De Recherche En Informatique Et En Automatique

Université De Rennes

Institut National De Recherche En Agronomie

Christian Barillot

Patrick Perez

Pierre Hellier

Aymeric Stamm

Pierrick Coupe

Xavier Morandi

Olivier Commowick

Charles Kervrann

A computer-implemented method of characterizing molecular diffusion within a body from a set of diffusion-weighted magnetic resonance signals by computing a weighted average of a plurality of multi-compartment diffusion models comprises a same number of compartments, fitted to a set of diffusion-weighted magnetic resonance signals, the weighted average being computed using weights representative of a performance criterion of each of the models; wherein each of the multi-compartment diffusion models comprises a different number of subsets of compartments, the compartments of a same subset being identical to each other.

Method of characterizing molecular diffusion within a body from a set of diffusion-weighted magnetic resonance signals and apparatus for carrying out such a method

Method to extract a diffusion direction from DW-MR signals, in which a magnetic field gradient qis applied to a body part, a magnetic resonance signal Sis measured and a diffusion direction &#x3bc;is determined, wherein for a predetermined positive number m of diffusion direction(s) &#x3bc;, the signals Sare linked to the probability density function of the random vector X of water molecules displacements represented as a mixture of m probability density functions pof random vectors Xcharacterizing the diffusion along &#x3bc;, the Xbeing decomposed into a first component modelling directional variability of the water molecules displacements with &#x3bc;as mean direction, and into a second component modelling the length variability of the water molecules displacements along &#x3bc;.

Method and MRI device to detect a direction of at least one fiber in a body

A device for processing of data including images of a portion of a body includes processing means capable of processing first data representative of elementary portions of an image obtained by magnetic resonance in a region of the body and second data representative of elementary portions of images obtained by ultrasounds in a portion of that region, by performing: i) generating first and second maps of the probability that the elementary portions belong to structures of interest of the portion of the region based at least on the intensities associated thereto and respectively defined by the first and second data; ii) estimating a conversion for shifting from one of the first and second maps to the other while maximizing for each of their elementary portion the joined probability that it belongs to a same structure of interest; and iii) resetting the structures of interest of one of the first and second maps relative to those of the other by the conversion.

Image processing device for matching images of a same portion of a body obtained by magnetic resonance and ultrasounds

An image processing device comprises a store () for receiving image data () with a pixel identifier and at least one piece of associated intensity data and a pilot () which is provided to call a reduction unit () with pixels to be weighted and, for each pixel, in order to define a first neighborhood and a plurality of second neighborhoods with a neighborhood selection unit (), in order to obtain a weighting value for the second neighborhood with a weighting unit () with the first neighborhood and a neighborhood among the plurality of second neighborhoods, in order to define each time a piece of weighted intensity data of a working pixel as the weighting value of the second neighborhood multiplied by the intensity data of the associated working pixel, and in order to define a piece of weighted intensity data of the pixel to be weighted by adding each of the pieces of weighted intensity data of a working pixel. The weighting unit () is provided to calculate the distance between first and second neighborhoods on the basis of a sum, where each square of the difference between the respective intensity data of these neighborhoods is modulated by a quantity which is inversely proportional to the intensity data in the second neighborhood.

Image denoising device

Growing community of inventors

Laille, France

Christian Barillot