Abstract: Disclosed is a method for performing X-ray Computed Tomography scanning, the method including acquiring a plurality of images of an object, obtaining an initial image from the plurality of images, calculating NonLocal weight of the initial image, utilizing a current image estimation and registered prior image, performing a successive over-relaxation optimization to yield a new image estimation with an intensity of the new image estimation equal or greater than zero, performing a cycle update, generating an image of the object utilizing the new image estimation obtained from the optimization, and outputting a resultant image.

Abstract: Disclosed is a method for performing X-ray Computed Tomography scanning, the method including acquiring a plurality of images of an object, obtaining an initial image from the plurality of images, calculating NonLocal weight of the initial image, utilizing a current image estimation and registered prior image, performing a successive over-relaxation optimization to yield a new image estimation with an intensity of the new image estimation equal or greater than zero, performing a cycle update, generating an image of the object utilizing the new image estimation obtained from the optimization, and outputting a resultant image.

Abstract: A method for reconstructing an image from emission data includes generating a compressed point-spread function matrix, generating an accumulated attenuation factor; and performing at least one image projection operation on an image matrix of the emission data using the compressed point-spread function matrix and the accumulated attenuation factor. The image projection operation can include rotating an image matrix and an exponential attenuation map to align with a selected viewing angle. An accumulated attenuation image is then generated from the rotated image matrix and rotated exponential attenuation map and a projection image is generated for each voxel by multiplying the accumulated attenuation image and point spread function matrix for each voxel. The rotating and multiplying operations can be performed on a graphics processing unit, which may be found in a commercially available video processing card, which are specifically designed to efficiently perform such operations.

Abstract: A method for electronically cleansing a virtual object formed from acquired image data converted to a plurality of volume elements is provided. The present method allows individual volume elements, or voxels, to represent more than one material type. The method includes defining a partial volume image model for volume elements representing a plurality of material types based, at least in part, on the measured intensity value of the volume element. The material mixture for each of the volume elements representing a plurality of material types can be estimated using the observed intensity values and the defined partial volume image model. The volume elements representing a plurality of material types can then be classified in accordance with the estimated material mixture. For electronic colon cleansing, the method includes removing at least one classification of volume elements when displaying the virtual object.

Abstract: A method for reconstructing an image from emission data includes generating a compressed point-spread function matrix, generating an accumulated attenuation factor; and performing at least one image projection operation on an image matrix of the emission data using the compressed point-spread function matrix and the accumulated attenuation factor. The image projection operation can include rotating an image matrix and an exponential attenuation map to align with a selected viewing angle. An accumulated attenuation image is then generated from the rotated image matrix and rotated exponential attenuation map and a projection image is generated for each voxel by multiplying the accumulated attenuation image and point spread function matrix for each voxel. The rotating and multiplying operations can be performed on a graphics processing unit, which may be found in a commercially available video processing card, which are specifically designed to efficiently perform such operations.

Abstract: A method for electronically cleansing a virtual object formed from acquired image data converted to a plurality of volume elements is provided. The present method allows individual volume elements, or voxels, to represent more than one material type. The method includes defining a partial volume image model for volume elements representing a plurality of material types based, at least in part, on the measured intensity value of the volume element. The material mixture for each of the volume elements representing a plurality of material types can be estimated using the observed intensity values and the defined partial volume image model. The volume elements representing a plurality of material types can then be classified in accordance with the estimated material mixture. For electronic colon cleansing, the method includes removing at least one classification of volume elements when displaying the virtual object.