Abstract: 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.

Abstract: The invention relates to a neurological feedback device comprising a memory (4) for receiving electroencephalogram data and raw functional and metabolic magnetic resonance imaging data, an electroencephalogram block (10) comprising at least one electroencephalogram processing unit (14, 16, 18) arranged so as to process raw electroencephalogram data and to calculate a value linked to a brain wave, a functional magnetic resonance imaging block (20) comprising at least one functional and metabolic magnetic resonance imaging processing unit (24, 26, 28) arranged so as to process raw functional magnetic resonance imaging data and to calculate a value of perfusion or oxygenation of certain zones of the brain, a synchroniser (30) arranged so as to synchronise temporally the electroencephalogram data and raw functional magnetic resonance imaging data and the processing thereof in the electroencephalogram block (10) and the functional magnetic resonance imaging block (20), and a calculator (40) arranged so as to deter

Abstract: 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.

Abstract: Method to extract a diffusion direction from DW-MR signals, in which a magnetic field gradient qi is applied to a body part, a magnetic resonance signal Si is measured and a diffusion direction ?j is determined, wherein for a predetermined positive number m of diffusion direction(s) ?j, the signals Si are linked to the probability density function of the random vector X of water molecules displacements represented as a mixture of m probability density functions pXj of random vectors Xj characterizing the diffusion along ?j, the Xj being decomposed into a first component modelling directional variability of the water molecules displacements with ?j as mean direction, and into a second component modelling the length variability of the water molecules displacements along ?j.

Abstract: 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.

Abstract: An image processing device comprises a store (110) for receiving image data (8) with a pixel identifier and at least one piece of associated intensity data and a pilot (100) which is provided to call a reduction unit (120) 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 (130), in order to obtain a weighting value for the second neighborhood with a weighting unit (140) 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.

Abstract: The invention concerns a method to extract a diffusion direction from DW-MR signals, in which a magnetic held gradient qi is applied to a body part, a magnetic resonance signal Si is measured and a diffusion direction ?j is determined. The invention is characterized in that for a predetermined positive number m of diffusion direction(s) ?j, the signals Si are linked to the probability density function of the random vector X of water molecules displacements represented as a mixture of m probability density functions pXj of random vectors Xj characterizing the diffusion along ?j, the Xj being decomposed into a first component modelling directional variability of the water molecules displacements with ?j as mean direction, and into a second component modelling the length variability of the water molecules displacements along ?j.

Abstract: An image processing device comprises a store (110) for receiving image data (8) with a pixel identifier and at least one piece of associated intensity data and a pilot (100) which is provided to call a reduction unit (120) with pixels to be weighted and, for each pixel, in order to define a first neighbourhood and a plurality of second neighbourhoods with a neighbourhood selection unit (130), in order to obtain a weighting value for the second neighbourhood with a weighting unit (140) with the first neighbourhood and a neighbourhood among the plurality of second neighbourhoods, in order to define each time a piece of weighted intensity data of a working pixel as the weighting value of the second neighbourhood 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.

Abstract: According to the invention, a device (D) is dedicated to the processing of data consisting of images of a portion or portions of a body, the device (D) includes processing means (MT) capable of, in the presence of first data representative of the elementary portions of an image obtained by magnetic resonance in a region of the body and of second data representative of the elementary portions of images obtained by ultrasounds in a portion of that region: 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 maximising 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