Abstract: A method and computer program for segmentation of an MRI image of tissue in presence of partial volume effects, include storing the MRI image in K-space representation as raw dataset, reconstructing N images, each represented by N sets of voxels and N sets of light intensity values, dividing each voxel into a fixed number of subvoxels equal in size, assigning the light intensity value of the voxel to its subvoxels, classifying each subvoxel according to light intensity value, identifying a totality of subvoxels classified with equal probability for a totality of tissue types, labeling the subvoxels as partial volume subvoxels, shifting N?1 images starting with the second image by one subvoxel relatively to the preceding image and gene-rating a new set of overlay subvoxels, determining a new set of probability values for the new set of overlay subvoxels and creating an overlay image of the new set of overlaid subvoxels.

Abstract: A method for quality control assessment in single time-point in-vivo imaging data related to imaging of objects, includes acquiring an in-vivo image of the object with imaging apparatus, defining a background image corresponding to an imaged air of the in-vivo image, defining an object image corresponding to the in-vivo image from which the background image has been removed, obtaining the background and object images by atlas-based registration, reflecting an intensity distribution of the background image with a histogram, fitting a noise mathematical model to part of the histogram intensity distribution, deriving background quality characteristics from the noise mathematical model, reflecting an intensity distribution of the object image with a further histogram, fitting a signal mathematical model to the further histogram intensity distribution, deriving object quality characteristics from the signal mathematical model, and automatically deriving signal-to-noise and contrast-to-noise ratios of in-vivo imagi

Abstract: A method for detecting, in single time-point, in-vivo imaging data related to artifacts in the imaging of objects, includes acquiring at least one in-vivo image with imaging apparatus. A background image corresponds to imaged air of the in-vivo image. The background image is obtained in two steps. A first step includes establishing an object-air boundary and a second step is an atlas-based refinement of a background volume of interest. A histogram reflects an intensity distribution of the background image. The background image is formed of a set of voxels where artifacts are detected. Intensities above a definable intensity value provide an initial estimate of a range of artifacts intensities. A modified morphological opening operation is executed, formed of an erosion of a set of voxels and a dilation, performed iteratively and constrained to voxels intensity above the intensity value, so that the opening operation provides natural definition of artifacts regions.

Abstract: A method for quality control assessment in single time-point in-vivo imaging data related to imaging of objects, includes acquiring an in-vivo image of the object with imaging apparatus, defining a background image corresponding to an imaged air of the in-vivo image, defining an object image corresponding to the in-vivo image from which the background image has been removed, obtaining the background and object images by atlas-based registration, reflecting an intensity distribution of the background image with a histogram, fitting a noise mathematical model to part of the histogram intensity distribution, deriving background quality characteristics from the noise mathematical model, reflecting an intensity distribution of the object image with a further histogram, fitting a signal mathematical model to the further histogram intensity distribution, deriving object quality characteristics from the signal mathematical model, and automatically deriving signal-to-noise and contrast-to-noise ratios of in-vivo imagi

Abstract: A method for detecting, in single time-point, in-vivo imaging data related to artifacts in the imaging of objects, includes acquiring at least one in-vivo image with imaging apparatus. A background image corresponds to imaged air of the in-vivo image. The background image is obtained in two steps. A first step includes establishing an object-air boundary and a second step is an atlas-based refinement of a background volume of interest. A histogram reflects an intensity distribution of the background image. The background image is formed of a set of voxels where artifacts are detected. Intensities above a definable intensity value provide an initial estimate of a range of artifacts intensities. A modified morphological opening operation is executed, formed of an erosion of a set of voxels and a dilation, performed iteratively and constrained to voxels intensity above the intensity value, so that the opening operation provides natural definition of artifacts regions.

Abstract: A method and computer program for segmentation of an MRI image of tissue in presence of partial volume effects, include storing the MRI image in K-space representation as raw dataset, reconstructing N images, each represented by N sets of voxels and N sets of light intensity values, dividing each voxel into a fixed number of subvoxels equal in size, assigning the light intensity value of the voxel to its subvoxels, classifying each subvoxel according to light intensity value, identifying a totality of subvoxels classified with equal probability for a totality of tissue types, labeling the subvoxels as partial volume subvoxels, shifting N?1 images starting with the second image by one subvoxel relatively to the preceding image and gene-rating a new set of overlay subvoxels, determining a new set of probability values for the new set of overlay subvoxels and creating an overlay image of the new set of overlaid subvoxels.