Abstract: In the field of obesity related disease, identification of patients with nonalcoholic steatohepatitis (NASH) would be useful to counsel them more intensively on diet and lifestyle changes and propose new pharmacological treatments. As a consequence, the inventors worked on a method for post-processing images of a region of interest of the liver for reconstructing a map of the internal magnetic susceptibility by using a Bayesian regularization approach to inverse the internal magnetic field. Such method can be implemented on computer and provides better results than other known methods for obesity related disease. This method may be applied for predicting that a subject is at risk of suffering from such disease, diagnosing a disease, identifying a therapeutic or a biomarker and screening compounds useful as a medicine.

Abstract: In the field of obesity related disease, identification of patients with nonalcoholic steatohepatitis (NASH) would be useful to counsel them more intensively on diet and lifestyle changes and propose new pharmacological treatments. As a consequence, the inventors worked on a method for post-processing images of a region of interest of the liver for reconstructing a map of the internal magnetic susceptibility by using a Bayesian regularization approach to inverse the internal magnetic field. Such method can be implemented on computer and provides better results than other known methods for obesity related disease. This method may be applied for predicting that a subject is at risk of suffering from such disease, diagnosing a disease, identifying a therapeutic or a biomarker and screening compounds useful as a medicine.

Abstract: The present invention relates to obesity related diseases, such as cancer of non-alcoholic fatty liver disease (NAFLD). Tissue perfusion is currently investigated by using dynamic contrast-enhanced magnetic resonance imaging which is an invasive technique and does not provide enough accuracy. As a result, the inventors worked on post-processing images of subcutaneous adipose tissue or the epididymal adipose tissue taken with a magnetic resonance imaging technique and a multifrequency magnetic resonance elastography technique to obtain parameters such as loss modulus and storage modulus which are more accurate for a diagnosing purpose. This post-processing method may be applied for a method for predicting that a subject is at risk of suffering from said disease, identifying a therapeutic target or a biomarker and screening compounds useful as medicine.

Abstract: It is proposed a method for post-processing images of an region of interest in a subject, the images being acquired with a magnetic resonance imaging technique, the method for post-processing comprising at least the step of: —unwrapping the phase of each image, —extracting a complex signal over echo time for at least one pixel of the unwrapped images, and —calculating fat characterization parameters by using a fitting technique applied on a model, the model being a function which associates to a plurality of parameters each extracted complex signal, the plurality of parameters comprising at least two fat characterization parameters, the magnitude error and the phase error generated by the use of the bipolar readout gradients, the fitting technique being a non-linear least-square fitting technique using pseudo-random initial conditions.

Abstract: Disclosed is the use of magnetic resonance imaging in the medical field. One issue addressed is the compensating of respiratory movements in the obtained images with magnetic resonance imaging. For this, the method proposes to choose a reference image in the initial set, the determined position for the reference image being a reference position and to compensate the difference between the determined position and the reference position to obtain a corrected set of images for each image of the initial set. Such method can be implemented in a computer and may be used to provide additional functionalities to magnetic resonance imager and renders the taking of images by a magnetic resonance imager easier.

Abstract: The invention relates to liver diseases. Liver diseases notably encompass chronic liver disease and liver cancer (a liver primitive cancer or metastasis). There is therefore a need to be able to extract biomarkers for subjects to suffer from this disease. As a consequence, the inventors worked on a method for post-processing images of a region of interest to obtain at least one perfusion parameter and at least one transport parameter. Such method enables to obtain a method which can be implemented on computer and provides access to relevant parameters for liver diseases in an easier and more accurate way. This method may be applied for predicting that a subject is at risk of suffering from such disease, diagnosing a disease, identifying a therapeutic or a biomarker and screening compounds useful as a medicine.

Abstract: A method for post-processing images of a region of interest in a subject, the images being acquired with a magnetic resonance imaging technique, the method for post-processing comprising at least the step of: unwrapping the phase of each image, extracting a real signal over echo time for at least one pixel of the unwrapped images, and calculating fat characterization parameters by using a fitting technique applied on a model, the model being a function which associates to a plurality of parameters each extracted real signal, the plurality of parameters comprising at least two fat characterization parameters and at least one parameter obtained by a measurement, the fitting technique being a non-linear least-square fitting technique using pseudo-random initial conditions.

Abstract: A method for post-processing images of a region of interest in a subject, the images being acquired with a magnetic resonance imaging technique, the method for post-processing comprising at least the step of: unwrapping the phase of each image, extracting a real signal over echo time for at least one pixel of the unwrapped images, and calculating fat characterization parameters by using a fitting technique applied on a model, the model being a function which associates to a plurality of parameters each extracted real signal, the plurality of parameters comprising at least two fat characterization parameters and at least one parameter obtained by a measurement, the fitting technique being a non-linear least-square fitting technique using pseudo-random initial conditions.

Abstract: It is proposed a method for post-processing images of an region of interest in a subject, the images being acquired with a magnetic resonance imaging technique, the method for post-processing comprising at least the step of:—unwrapping the phase of each image,—extracting a complex signal over echo time for at least one pixel of the unwrapped images, and—calculating fat characterization parameters by using a fitting technique applied on a model, the model being a function which associates to a plurality of parameters each extracted complex signal, the plurality of parameters comprising at least two fat characterization parameters, the magnitude error and the phase error generated by the use of the bipolar readout gradients, the fitting technique being a non-linear least-square fitting technique using pseudo-random initial conditions.

Abstract: A method for post-processing images of a region of interest in a subject, the images being acquired with a magnetic resonance imaging technique, the method for post-processing comprising at least the step of: unwrapping the phase of each image, extracting a real signal over echo time for at least one pixel of the unwrapped images, and calculating fat characterization parameters by using a fitting technique applied on a model, the model being a function which associates to a plurality of parameters each extracted real signal, the plurality of parameters comprising at least two fat characterization parameters and at least one parameter obtained by a measurement, the fitting technique being a non-linear least-square fitting technique using pseudo-random initial conditions.