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Samit Basu

Publications and source records attributed to Samit Basu.

3 recordsLinked to original sources

Exact filtered backprojection reconstruction for dynamic pitch helical cone beam computed tomography.

We present an exact filtered backprojection reconstruction formula for helical cone beam computed tomography in which the pitch of the helix varies with time. We prove that the resulting algorithm, which is functionally identical to the constant pitch case, provides exact reconstruction provided that the projection of the helix onto the detector forms convex boundaries and that PI lines are unique. Furthermore, we demonstrate that both of these conditions are satisfied provided the sum of the translational velocity and the derivative of the translational acceleration does not change sign. As a special case, we show that gantry tilt can also be handled by our dynamic pitch formula. Simulation results demonstrate the resulting algorithm.

Algorithms↗

Distance-driven projection and backprojection in three dimensions.

Projection and backprojection are operations that arise frequently in tomographic imaging. Recently, we proposed a new method for projection and backprojection, which we call distance-driven, and that offers low arithmetic cost and a highly sequential memory access pattern. Furthermore, distance-driven projection and backprojection avoid several artefact-inducing approximations characteristic of some other methods. We have previously demonstrated the application of this method to parallel and fan beam geometries. In this paper, we extend the distance-driven framework to three dimensions and demonstrate its application to cone beam reconstruction. We also present experimental results to demonstrate the computational performance, the artefact characteristics and the noise-resolution characteristics of the distance-driven method in three dimensions.

Algorithms↗

O(N3 log N) backprojection algorithm for the 3-D radon transform.

We present a novel backprojection algorithm for three-dimensional (3-D) radon transform data that requires O(N3 log2 N) operations for reconstruction of an N x N x N volume from O(N2) plane-integral projections. Our algorithm uses a hierarchical decomposition of the 3-D radon transform to recursively decompose the backprojection operation. Simulations are presented demonstrating reconstruction quality comparable to the standard filtered backprojection, which requires O(N5) computations under the same circumstances.

Algorithms↗