Cone beam spotlight imaging using multi-resolution area detector

Claim 1

A computerized tomography system comprising: a multi-resolution array detector having a fine resolution zone with a density df of first detector elements and a coarse resolution zone with a density dc of second detector elements, and said density dc being less than said density df; a source of imaging energy for applying imaging energy to at least a region of interest including a spotlight region of an object such that imaging energy passes to said array detector; scanning means to move said source relative to the object about a rotation axis substantially centered with respect to said spotlight region; data acquisition means connected to said array detector for acquiring multi-resolution sensed data from said array detector; a data processor connected to said data acquisition means for providing multi-resolution image data from said multi-resolution sensed data, said data processor including means for calculating Radon derivative data at a plurality of fine resolution points in Radon space and at a plurality of coarse resolution points in Radon space, said data processor further including means for obtaining Radon data for the fine and coarse resolution points and means for inverting the Radon data to provide the multi-resolution image data; said means for calculating and said means for obtaining each using weighted integration; and a display connected to said data processor for displaying multi-resolution CT images based on said multi-resolution image data.

Claim 7

A method of computerized tomography comprising the steps of: applying imaging energy from a source to at least a region of interest including a spotlight region of an object; moving the source relative to the object about a rotation axis substantially centered with respect to said spotlight region in a data scan path; acquiring multi-resolution sensed data representative of the region of interest using a multi-resolution two-dimensional array detector having a fine resolution zone with a density df of first detector elements and a coarse resolution zone with a density dc of second detector elements, and said density dc being less than said density df, said multi-resolution sensed data having a higher density relative to the spotlight region than outside of the spotlight region; converting the multi-resolution sensed data to multi-resolution image data, said converting step including the substeps of calculating Radon derivative data at a plurality of fine resolution points in Radon space and at a plurality of coarse resolution points in Radon space, obtaining Radon data for the fine and coarse resolution points, and inverting the Radon data to provide the multi-resolution image data; said calculating and obtaining substeps using weighted integration; and displaying an image of the region of interest based on said multi-resolution image data, said image having a higher resolution relative to the spotlight region than outside of the spotlight region.

Claim 8

A method of computerized tomography comprising the steps of: applying imaging energy from a source to at least a region of interest including a spotlight region of an object; moving the source relative to the object about a rotation axis substantially centered with respect to said spotlight region in a data scan path; acquiring multi-resolution sensed data representative of the region of interest using a multi-resolution two-dimensional array detector having a fine resolution zone with a density df of first detector elements and a coarse resolution zone with a density dc of second detector elements, and said density dc being less than said density df, said multi-resolution sensed data having a higher density relative to the spotlight region than outside of the spotlight region; converting the multi-resolution sensed data to multi-resolution image data, said converting step including the substeps of calculating Radon derivative data at a plurality of fine resolution points in Radon space and at a plurality of coarse resolution points in Radon space, obtaining Radon data for the fine and coarse resolution points, and inverting the Radon data to provide the multi-resolution image data; said calculating and obtaining substeps using weighted integration; and displaying an image of the region of interest based on said multi-resolution image data, said image having a higher resolution relative to the spotlight region than outside of the spotlight region.