Abstract: A multi-spectral tomography imaging system includes one or more source devices configured to direct beams of radiation in multiple spectra to a region of interest (ROI), and one or more detectors configured to receive the beams of radiation. The system includes a processor configured to cause movement in at least one of the components such that a first beam of radiation with a first spectrum is directed to the ROI for less than 360 degrees of movement of the ROI. The processor is also configured to process data detected by the one or more detectors, where the data results at least in part from the first beam of radiation with the first spectrum that is directed to the ROI for less than the 360 degrees of movement of the ROI. The processor is further configured to generate an image of the ROI based on the processed data.

Abstract: A multi-spectral tomography imaging system includes one or more source devices configured to direct beams of radiation in multiple spectra to a region of interest (ROI), and one or more detectors configured to receive the beams of radiation. The system includes a processor configured to cause movement in at least one of the components such that a first beam of radiation with a first spectrum is directed to the ROI for less than 360 degrees of movement of the ROI. The processor is also configured to process data detected by the one or more detectors, where the data results at least in part from the first beam of radiation with the first spectrum that is directed to the ROI for less than the 360 degrees of movement of the ROI. The processor is further configured to generate an image of the ROI based on the processed data.

Abstract: A multi-spectral tomography imaging system includes one or more source devices configured to direct beams of radiation in multiple spectra to a region of interest (ROI), and one or more detectors configured to receive the beams of radiation. The system includes a processor configured to cause movement in at least one of the components such that a first beam of radiation with a first spectrum is directed to the ROI for less than 360 degrees of movement of the ROI. The processor is also configured to process data detected by the one or more detectors, where the data results at least in part from the first beam of radiation with the first spectrum that is directed to the ROI for less than the 360 degrees of movement of the ROI. The processor is further configured to generate an image of the ROI based on the processed data.

Abstract: A multi-spectral tomography imaging system includes one or more source devices configured to direct beams of radiation in multiple spectra to a region of interest (ROI), and one or more detectors configured to receive the beams of radiation. The system includes a processor configured to cause movement in at least one of the components such that a first beam of radiation with a first spectrum is directed to the ROI for less than 360 degrees of movement of the ROI. The processor is also configured to process data detected by the one or more detectors, where the data results at least in part from the first beam of radiation with the first spectrum that is directed to the ROI for less than the 360 degrees of movement of the ROI. The processor is further configured to generate an image of the ROI based on the processed data.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data generated from divergent beams. The method and apparatus may iteratively constrain the variation of an estimated image in order to reconstruct the image. To reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image. For example, the first estimated image may be combined with an image generated from the difference data to generate a new estimated image. To generate the image for the next iteration, the variation of the new estimated image may be constrained.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data generated from divergent beams. The method and apparatus may iteratively constrain the variation of an estimated image in order to reconstruct the image. To reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image. For example, the first estimated image may be combined with an image generated from the difference data to generate a new estimated image. To generate the image for the next iteration, the variation of the new estimated image may be constrained.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data generated from divergent beams. The method and apparatus may iteratively constrain the variation of an estimated image in order to reconstruct the image. To reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image. For example, the first estimated image may be combined with an image generated from the difference data to generate a new estimated image. To generate the image for the next iteration, the variation of the new estimated image may be constrained.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data generated from divergent beams. The method and apparatus may iteratively constrain the variation of an estimated image in order to reconstruct the image. To reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image. For example, the first estimated image may be combined with an image generated from the difference data to generate a new estimated image. To generate the image for the next iteration, the variation of the new estimated image may be constrained.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data generated from divergent beams. The method and apparatus may iteratively constrain the variation of an estimated image in order to reconstruct the image. To reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image. For example, the first estimated image may be combined with an image generated from the difference data to generate a new estimated image. To generate the image for the next iteration, the variation of the new estimated image may be constrained.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data (including exterior and interior data) generated from divergent beams. In one aspect of the invention, the method and apparatus iteratively constrains the variation of an estimated image in order to reconstruct the image. As one example, a divergent beam may be used to generate data (“actual data”). As discussed above, the actual data may be less than sufficient to exactly reconstruct the image by conventional techniques, such as FBP. In order to reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data (including exterior and interior data) generated from divergent beams. In one aspect of the invention, the method and apparatus iteratively constrains the variation of an estimated image in order to reconstruct the image. As one example, a divergent beam maybe used to generate data (“actual data”). As discussed above, the actual data may be less than sufficient to exactly reconstruct the image by conventional techniques, such as FBP. In order to reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image.

Abstract: A system and method are provided for reconstructing images from limited or incomplete data, such as few view data or limited angle data or truncated data (including exterior and interior data) generated from divergent beams. In one aspect of the invention, the method and apparatus iteratively constrains the variation of an estimated image in order to reconstruct the image. As one example, a divergent beam maybe used to generate data (“actual data”). As discussed above, the actual data may be less than sufficient to exactly reconstruct the image by conventional techniques, such as FBP. In order to reconstruct an image, a first estimated image may be generated. Estimated data may be generated from the first estimated image, and compared with the actual data. The comparison of the estimated data with the actual data may include determining a difference between the estimated and actual data. The comparison may then be used to generate a new estimated image.

Abstract: A method and apparatus for reconstruction of a region of interest for an object is provided. The reconstruction of the object may be based on chords which may fill a part, all, or more than all of the region of interest. Using chords for reconstruction may allow for reducing data acquired and/or processing for reconstructing a substantially exact image of the ROI. Moreover, various methodologies may be used in reconstructing the image, such as backprojection-filtration, and modified filtration backprojection.