Abstract: A method of analyzing a specimen using X-rays, comprising the steps of: Irradiating the specimen with input X-rays; Using a detector to detect a flux of output X-rays emanating from the specimen in response to said irradiation, which method further comprises the following steps: Using the detector to intercept at least a portion of said flux so as to produce a set {Ij} of pixeled images Ij of at least part of the specimen, whereby the cardinality of the set {Ij} is M>1. For each pixel pi in each image Ij, determining the accumulated signal strength Sij, thus producing an associated set of signal strengths {Sij}. Using the set {Sij} to calculate the following values: A mean signal strength S per pixel position i; A variance ?2S in S per pixel position i. Using these values S and ?2S to produce a map of mean X-ray photon energy E per pixel.

Abstract: Some embodiments of the invention provide a method of determining a material characteristic of material in a sample by iterative tomographic reconstruction. The method conducts one or more X-ray tomography scans of a sample, and then determines one or more estimated material characteristics, such as atomic number and density, for multiple volume elements in the sample using a tomographic reconstruction algorithm. These estimated material characteristics are then modified by reference to stored known material characteristic data. Preferably, determining the composition of the sample volume during reconstruction includes segmenting the sample into regions of common composition, the segmenting being performed during iterative reconstruction instead of being based on the voxel characteristics determined upon the completion of iterative reconstruction.

Abstract: A method of analyzing a specimen using X-rays, comprising the steps of: Irradiating the specimen with input X-rays; Using a detector to detect a flux of output X-rays emanating from the specimen in response to said irradiation, which method further comprises the following steps: Using the detector to intercept at least a portion of said flux so as to produce a set {Ij} of pixeled images Ij of at least part of the specimen, whereby the cardinality of the set {Ij} is M>1. For each pixel piin each image Ij, determining the accumulated signal strength Sij, thus producing an associated set of signal strengths {Sij}. Using the set {Sij} to calculate the following values: A mean signal strength S per pixel position i; A variance ?2S in S per pixel position i. Using these values S and ?2S to produce a map of mean X-ray photon energy E per pixel.

Abstract: Some embodiments of the invention provide a method of determining a material characteristic of material in a sample by iterative tomographic reconstruction. The method conducts one or more X-ray tomography scans of a sample, and then determines one or more estimated material characteristics, such as atomic number and density, for multiple volume elements in the sample using a tomographic reconstruction algorithm. These estimated material characteristics are then modified by reference to stored known material characteristic data. Preferably, determining the composition of the sample volume during reconstruction includes segmenting the sample into regions of common composition, the segmenting being performed during iterative reconstruction instead of being based on the voxel characteristics determined upon the completion of iterative reconstruction.

Abstract: Disclosed is a method of reconstructing a multi-dimensional data set representing a dynamic sample at a series of reconstruction instants. The multi-dimensional data set comprises a static component and a dynamic component. The method comprises acquiring a plurality of projection images of the dynamic sample; reconstructing a static component of the multi-dimensional data set from the acquired projection images; acquiring a further plurality of projection images of the dynamic sample; and reconstructing a dynamic component of the multi-dimensional data set at each reconstruction instant from the further plurality of acquired projection images using a priori information about the sample. The multi-dimensional data set is the sum of the static component and the dynamic component at each reconstruction instant.

Abstract: Disclosed is a method of reconstructing a multi-dimensional data set representing a dynamic sample at a series of reconstruction instants. The multi-dimensional data set comprises a static component and a dynamic component. The method comprises acquiring a plurality of projection images of the dynamic sample; reconstructing a static component of the multi-dimensional data set from the acquired projection images; acquiring a further plurality of projection images of the dynamic sample; and reconstructing a dynamic component of the multi-dimensional data set at each reconstruction instant from the further plurality of acquired projection images using a priori information about the sample. The multi-dimensional data set is the sum of the static component and the dynamic component at each reconstruction instant.