Alexander A. Zamyatin

Extension of the reconstruction field of view and truncation correction using sinogram decomposition

We propose a novel truncation correction algorithm that completes unmeasured data outside of the scan field of view, which allows extending the reconstruction field of view. When a patient extends outside the detector coverage the projection data are transversely truncated, which causes severe artifacts. The proposed method utilizes the idea of sinogram decomposition, where we consider sinogram curves corresponding to image points outside the field of view. We propose two ways to estimate the truncated data, one based on the minimum value along the sinogram curve, and the other based on the data values near the edge of truncation. Both estimation methods are combined to achieve uniform image quality improvement from the edge of truncation to the outer side of the extended region. In our evaluation with simulated and real projection data we compare the proposed method with existing methods and investigate the dependence on the amount of truncation. The evaluation shows that the proposed method handles cases when truncation is present on both sides of the detector, or when a high-contrast object is located outside the field of view.

Local Tomography and the Motion Estimation Problem

In this paper we study local tomography (LT) in the motion contaminated case. It is shown that microlocally, away from some critical directions, LT is equivalent to a pseudodifferential operator of order one. LT also produces nonlocal artifacts that are of the same strength as useful singularities. If motion is not accurately known, singularities inside the object

Practical hybrid convolution algorithm for helical CT reconstruction

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Helical cone beam CT with an asymmetrical detector

being scanned spread in different directions. A single edge can become a double edge. In such a case the image of

Formulation of four katsevich algorithms in native geometry

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Exact image reconstruction for a circle and line trajectory with a gantry tilt

looks cluttered. Based on this observation we propose an algorithm for motion estimation. We propose an empiric measure of image clutter, which we call edge entropy. By minimizing edge entropy we find the motion model. The algorithm is quite flexible and is also used for solving the misalignment correction problem. The results of numerical experiments on motion estimation and misalignment correction are very encouraging.

Metal artifact reduction algorithm for single energy and dual energy CT scans

Great strides have been taken in the last few years in the development of both approximate and exact reconstruction algorithms for helical cone-beam computed tomography (CT). However, it is hard to achieve a good balance between reconstruction speed, flexibility, and image quality. We propose a new algorithm that combines the advantages of many previously published algorithms. It uses the so-called hybrid convolution, which is the sum of the ramp and Hilbert filters. In this work, we evaluate the new algorithm and compare it to other candidates in terms of spatial resolution, noise, and image artifacts. Our evaluation demonstrated that the proposed algorithm outperforms the helical Feldkamp algorithm in terms of image noise uniformity and the cone beam artifact. We also propose a simplified version for the over-scan reconstruction.

Helical CT Reconstruction with Large Cone Angle

If a multislice or other area detector is shifted to one side to cover a larger field of view, then the data are truncated on one side. We propose a method to restore the missing data in helical cone-beam acquisitions that uses measured data on the longer side of the asymmetric detector array. The method is based on the idea of complementary rays, which is well known in fan beam geometry; in this paper we extend this concept to the cone-beam case. Different cases of complementary data coverage and dependence on the helical pitch are considered. The proposed method is used in our prototype 16-row CT scanner with an asymmetric detector and a 700 mm field of view. For evaluation we used scanned body phantom data and computer-simulated data. To simulate asymmetric truncation, the full, symmetric datasets were truncated by dropping either 22.5% or 45% from one side of the detector. Reconstructed images from the prototype scanner with the asymmetrical detector show excellent image quality in the extended field of view. The proposed method allows flexible helical pitch selection and can be used with overscan, short-scan, and super-short-scan reconstructions.

Up-sampling with Shift Method for Windmill Correction

We derive formulations of the four exact helical Katsevich algorithms in the native cylindrical detector geometry, which allow efficient implementation in modern computed tomography scanners with wide cone beam aperture. Also, we discuss some aspects of numerical implementation

Dose Reduction Potential with Photon Counting Computed Tomography

We investigate image reconstruction with a circle and line trajectory with a tilted gantry. We derive new equations for reconstruction from the line data, such as equations of filtering lines, range of filtering lines and range of the line scan. We analyze the detector requirements and show that the line scan does not impose extra requirements on the cylindrical detector size with our algorithm, that is, the axial truncation of the filtering lines does not occur. We discuss full-scan and short-scan versions of the algorithm. Evaluation of our algorithm uses simulated and real 256-slice data.