Efficient quasi-exact 3D image reconstruction algorithm for CT scanners
View Patent ↗A CT scanner comprises: at least one source of X-rays and a multi-row detector array of arbitrary geometry, both supported so as rotate around an axis of rotation during a scan of an object translated along the axis, wherein data for each detector is generated as a function of the X-ray energy received; and a data processor configured so as to perform resampling of the data onto curves in a virtual detector array. The curves project onto tilted lines in a virtual flat detector as to enable tangential filtering of the data.
1. A CT scanner comprising:
at least one source of X-rays and a multi-row detector array having non-flat and non-circular geometry, both supported so as rotate around an axis of rotation during a scan of an object translated along the said axis, wherein data for each detector is generated as a function of the X-ray energy received; and
a data processor configured so as to perform equiangular resampling with row dithering of the data onto curves in a virtual detector array; wherein said curves project onto tilted lines in a virtual flat detector as to enable tangential filtering of the data.
2. A data processor according to claim 1 , wherein the virtual detector array is flat with equidistant detectors.
3. A data processor according to claim 1 , wherein the virtual detector array is cylindrical with equiangular detectors.
4. A data processor according to claim 1 , wherein the data is half segment data.
5. A data processor according to claim 4 , wherein the data processor is configured so as to perform equiangular resampling of the data onto curves in a virtual detector array.
6. A data processor according to claim 4 , wherein the data processor is configured so as to perform equiangular resampling of the data with row dithering onto curves in a virtual detector array.
7. A data processor according to claim 1 , when the data processor is configured so as to perform fan-beam and cone-beam weighting of the data.
8. A data processor according to claim 1 , when the data processor is configured so as to perform redundancy weighting of the data.
9. A data processor according to claim 1 , when the data processor is configured so as to perform tangential filtering of the data.
10. A data processor according to claim 1 , when the data processor is configured so as to perform adaptive upsampling of the data.
11. A data processor according to claim 1 , wherein the data processor is configured so as to backproject the data with sparse computation so as to produce back projected image voxels.
12. A data processor according to claim 11 , when the data processor is configured so as to perform Z-axis interpolation of the back projected image voxels.