Abstract: Image segmentation can include a pre-initialization image analysis of image data using an image analysis algorithm to generate a modified image, and the modified image can be presented on a display. An initialization can be performed on the modified image that includes user input on the modified image. The modified image can be segmented using a segmentation algorithm that evaluates the user input. Upon evaluating the user input, the segmentation algorithm can cause a segmented image to be produced which can be presented on the display.

Abstract: The present disclosure relates to an image processing method including the following steps: receiving a deformation or displacement image; defining a meshing of the deformation image; assigning a respective pair of unknown variables to each node of the meshing; detecting one (or more) node(s) located at the boundary between two different materials of the body studied; enriching the node(s) detected; calculating a basic matrix for each basic cell of the meshing; assembling the basic matrixes in order to obtain an overall structural matrix; calculating a resilience image of the body based on the overall structural matrix.

Abstract: An image processing method enables an elasticity image of a body including a cavity to be produced on the basis of the material(s) forming the body, wherein the method includes the steps of: receiving a deformation image illustrating a field of movement of the points of the body on the basis of a pressure difference in the body, estimating a shape function of the body from the deformation image, calculating an elasticity image of the body on the basis of the shape function, of the pressure difference and of the deformation image.

Abstract: Image segmentation can include a pre-initialization image analysis of image data using an image analysis algorithm to generate a modified image, and the modified image can be presented on a display. An initialization can be performed on the modified image that includes user input on the modified image. The modified image can be segmented using a segmentation algorithm that evaluates the user input. Upon evaluating the user input, the segmentation algorithm can cause a segmented image to be produced which can be presented on the display.

Abstract: A method for characterizing ultrasound scatterers in a medium comprising providing ultrasound data representing a region of interest comprising a plurality of scatterers in a medium, the plurality of scatterers including clusters of scatterer sub-units, the scatterers having a physical property value to be estimated and the scatterer sub-units having at least one known physical parameter value; modelling the ultrasound data using an at least second order function of a spatial organization parameter defining the spatial organization of the scatterers; and estimating the physical property value of the scatterers from the modelled ultrasound data and the at least one known physical parameter of the sub-units by a regression of the spatial organization parameter as a function of frequency. A system for characterizing ultrasound scatterers is also included.

Abstract: The present disclosure relates to an image processing method including the following steps: receiving a deformation or displacement image; defining a meshing of the deformation image; assigning a respective pair of unknown variables to each node of the meshing; detecting one (or more) node(s) located at the boundary between two different materials of the body studied; enriching the node(s) detected; calculating a basic matrix for each basic cell of the meshing; assembling the basic matrixes in order to obtain an overall structural matrix; calculating a resilience image of the body based on the overall structural matrix.

Abstract: An image processing method enables an elasticity image of a body including a cavity to be produced on the basis of the material(s) forming the body, wherein the method includes the steps of: receiving a deformation image illustrating a field of movement of the points of the body on the basis of a pressure difference in the body, estimating a shape function of the body from the deformation image, calculating an elasticity image of the body on the basis of the shape function, of the pressure difference and of the deformation image.

Abstract: A method for characterizing ultrasound scatterers in a medium comprises receiving ultrasound data representing a region of interest comprising a plurality of scatterers in a medium, the plurality of scatterers including aggregates of the scatterers. The ultrasound data is modeled data using an effective medium theory combined with the structure factor model, the structure factor model defining the spatial organization and concentration of the aggregates. The modeled ultrasound data is compared to theoretical data obtained with the effective medium theory combined with the structure factor model. From the comparison, dimensional data of the aggregates of the scatterers and the volume concentration of scatterers in the medium is determined.

Abstract: A method for characterizing ultrasound scatterers in a medium comprises receiving ultrasound data representing a region of interest comprising a plurality of scatterers in a medium, the plurality of scatterers including aggregates of the scatterers. The ultrasound data is modeled data using an effective medium theory combined with the structure factor model, the structure factor model defining the spatial organization and concentration of the aggregates. The modeled ultrasound data is compared to theoretical data obtained with the effective medium theory combined with the structure factor model. From the comparison, dimensional data of the aggregates of the scatterers and the volume concentration of scatterers in the medium is determined.

Abstract: A method for segmenting an image comprising: determining an initial estimation of a boundary between at least two components in a region of an image to be segmented; providing image data from the region of the image to be segmented, the image data representing gray level values of a plurality of image elements of the components; modelling the image data on a mixture of at least two statistical distributions, each statistical distribution having more than one parameter, and each component being associated with certain weights of the statistical distributions in the mixture; estimating the parameters of the statistical distributions in the mixture; for each component, estimating the weights of the statistical distributions in the mixture based on the estimated parameters and the image data of each image element; and optimizing the initial estimation of the boundary between the components based on the estimated parameters and estimated weights.

Abstract: The present relates to a device, a system and a method for generating radiation forces in a region of interest. For doing so, a plurality of additive shear waves are generated in the region of interest.

Abstract: A system and a method for inducing resonance of a heterogeneity or a sample within a body, the system comprising a shear wave generator, and a detection unit; the shear wave generator generating shear waves applied to the body and selectively inducing mechanical resonances of the heterogeneity, the detection unit detecting the induced mechanical resonances. The induced resonance of the heterogeneity is achieved by applying to the body one of: i) shear waves substantially parallel to a longitudinal axis of the heterogeneity; ii) shear waves polarised substantially perpendicularly to said longitudinal axis; iii) shear waves substantially circumferential to the heterogeneity; and iv) planar shear waves.

Abstract: A method for characterizing ultrasound scatterers in a medium comprising providing ultrasound data representing a region of interest comprising a plurality of scatterers in a medium, the plurality of scatterers including clusters of scatterer sub-units, the scatterers having a physical property value to be estimated and the scatterer sub-units having at least one known physical parameter value; modelling the ultrasound data using an at least second order function of a spatial organization parameter defining the spatial organization of the scatterers; and estimating the physical property value of the scatterers from the modelled ultrasound data and the at least one known physical parameter of the sub-units by a regression of the spatial organization parameter as a function of frequency. A system for characterizing ultrasound scatterers is also included.

Abstract: The present invention generally relates to intravascular ultrasound (IVUS) image segmentation methods, and is more specifically concerned with an intravascular ultrasound image segmentation method for characterizing blood vessel vascular layers. The proposed image segmentation method for estimating boundaries of layers in a multi-layered vessel provides image data which represent a plurality of image elements of the multi-layered vessel. The method also determines a plurality of initial interfaces corresponding to regions of the image data to segment and further concurrently propagates the initial interfaces corresponding to the regions to segment. The method thereby allows to estimate the boundaries of the layers of the multi-layered vessel by propagating the initial interfaces using a fast marching model based on a probability function which describes at least one characteristic of the image elements.

Abstract: The method for vascular elastography comprises: i) obtaining a sequence of radio-frequency (RF) images including pre-tissue-motion and post-tissue-motion images in digital form of a vessel delimited by a vascular wall; the pre-tissue-motion and post-tissue-motion images being representative of first and second time-delayed configuration, of the whole vessel; ii) partitioning both the pre-tissue-motion and post-tissue-motion images within the vascular wall into corresponding data windows; approximating a trajectory between the pre- and post-tissue-motion for corresponding data windows; and using the trajectory for each data window to compute the full strain tensor in each data window, which allow determining the Von Mises coefficient. The method can be adapted for non-invasive vascular elastography (NIVE), for non-invasive vascular micro-elastography (MicroNlVE) on small vessels, and for endovascular elastography (EVE).

Abstract: A method for segmenting an image comprising: determining an initial estimation of a boundary between at least two components in a region of an image to be segmented; providing image data from the region of the image to be segmented, the image data representing gray level values of a plurality of image elements of the components; modelling the image data on a mixture of at least two statistical distributions, each statistical distribution having more than one parameter, and each component being associated with certain weights of the statistical distributions in the mixture; estimating the parameters of the statistical distributions in the mixture; for each component, estimating the weights of the statistical distributions in the mixture based on the estimated parameters and the image data of each image element; and optimizing the initial estimation of the boundary between the components based on the estimated parameters and estimated weights.

Abstract: A multimodality imaging phantom is disclosed which is useful for calibrating devices for imaging vascular conduits. The phantom is compatible with X-ray, ultrasound and magnetic resonance imaging techniques. It allows testing, calibration, and inter-modality comparative study of imaging devices, in static or dynamic flow conditions. It also provides a geometric reference for evaluation of accuracy of imaging devices. The tissue-mimicking material is preferably an agar-based solidified gel. A vessel of known desired geometry runs throughout the gel and is connected to an inlet and outlet at its extremities for generating a flow circulation in the vessel. Said phantom also contains fiducial markers detectable in the above-mentioned modalities. The markers are preferably made of glass and are embedded in a layer of agar gel containing a fat component.

Abstract: A method for producing models of fibrous structure of fibrous tissue comprises obtaining a sequence of two-dimensional ultrasound images along the fibrous tissue. A three-dimensional model of an external portion of the fibrous tissue is created using the two-dimensional ultrasound images. Selected fibrous structure data is segmented from the two-dimensional ultrasound images. A three-dimensional model of the fibrous tissue is created with the fibrous structure by combining the three-dimensional model of the external portion of the fibrous tissue with the selected fibrous structure data.

Abstract: The method for vascular elastography comprises: i) obtaining a sequence of radio-frequency (RF) images including pre-tissue-motion and post-tissue-motion images in digital form of a vessel delimited by a vascular wall; the pre-tissue-motion and post-tissue-motion images being representative of first and second time-delayed configuration, of the whole vessel; ii) partitioning both the pre-tissue-motion and post-tissue-motion images within the vascular wall into corresponding data windows; approximating a trajectory between the pre- and post-tissue-motion for corresponding data windows; and using the trajectory for each data window to compute the full strain tensor in each data window, which allow determining the Von Mises coefficient. The method can be adapted for non-invasive vascular elastography (NIVE), for non-invasive vascular micro-elastography (MicroNIVE) on small vessels, and for endovascular elastography (EVE).

Abstract: The present invention generally relates to intravascular ultrasound (IVUS) image segmentation methods, and is more specifically concerned with an intravascular ultrasound image segmentation method for characterizing blood vessel vascular layers. The proposed image segmentation method for estimating boundaries of layers in a multi-layered vessel provides image data which represent a plurality of image elements of the multi-layered vessel. The method also determines a plurality of initial interfaces corresponding to regions of the image data to segment and further concurrently propagates the initial interfaces corresponding to the regions to segment. The method thereby allows to estimate the boundaries of the layers of the multi-layered vessel by propagating the initial interfaces using a fast marching model based on a probability function which describes at least one characteristic of the image elements.