A Reconstruction Algorithm for Helical Cone-Beam SPECT
نویسندگان
چکیده
Cone-beam SPECT provides improved sensitivity for imaging small organs like the brain and heart. However, current cone-beam tomography with the focal point traversing a planar orbit does not acquire sufficient data to give an accurate reconstruction. In this paper, we employ a data-acquisition method which obtains complete data for cone-beam SPECT by simultaneously rotating the gamma camera and translating the patient bed, so that cone-beam projections can be obtained with the focal point traversing a helix surrounding the patient. An implementation of Grangeat’s algorithm for helical cone-beam projections is developed. The algorithm requires a rebinning step to convert cone-beam data to parallel-beam data which are then reconstructed using the 3D Radon inversion. A fast new rebinning scheme is developed which uses all of the detected data to reconstruct the image and properly normalizes any multiply scanned data. This algorithm is shown to produce less artifacts than the commonly used Feldkamp algorithm when applied to either a circular planar orbit or a helical orbit acquisition. The algorithm can easily be extended to any arbitrary orbit.
منابع مشابه
Exact Reconstruction From Uniformly Attenuated Helical Cone-Beam Projections in SPECT
In recent years the development of cone-beam reconstruction algorithms has been an active research area in x-ray computed tomography (CT), and significant progress has been made in the advancement of algorithms. Theoretically exact and computationally efficient analytical algorithms can be found in the literature. However, in single photon emission computed tomography (SPECT), published cone-be...
متن کاملFast hierarchical backprojection for helical cone-beam tomography
Existing algorithms for exact helical cone beam (HCB) tomographic reconstruction are computationally infeasible for clinical applications. Their computational cost is dominated by 3-D backprojection, which is generally an operation. We present a fast hierarchical 3-D backprojection algorithm, generalizing fast 2-D parallel beam and fan beam algorithms, which reduces the overall complexity of th...
متن کاملPI-line-based image reconstruction in helical cone-beam computed tomography with a variable pitch.
Current applications of helical cone-beam computed tomography (CT) involve primarily a constant pitch where the translating speed of the table and the rotation speed of the source-detector remain constant. However, situations do exist where it may be more desirable to use a helical scan with a variable translating speed of the table, leading a variable pitch. One of such applications could aris...
متن کاملCone-Beam Iterative Reconstruction of a Segment of a Long Object
This study was performed to investigate the iterative reconstruction of a segment of a long object using cone-beam projections acquired with a practical-sized detector. This reconstruction problem is commonly called the cone-beam long object problem. The cone-beam focal-point trajectories studied were either helical or helical with planar arcs. We assume that the long object is confined in a ta...
متن کامل3D Image Reconstruction from Truncated Helical Cone Beam Projection Data - A Linear Prediction Approach
With the introduction of 2D flat-panel X-ray detectors, 3D image reconstruction using helical cone-beam tomography is fast replacing the conventional 2D reconstruction techniques. In 3D image reconstruction, the source orbit or scanning geometry should satisfy the data sufficiency or completeness condition for exact reconstruction. The helical scan geometry satisfies this condition and hence ca...
متن کامل