Convolution reconstruction algorithm for multislice helical CT

Jiang Hsieh; Brian Grekowicz; Piero Simoni; Jean-Baptiste Thibault; Mukta C. Joshi; Sandeep Dutta; Eugene C. Williams; Charlie Shaughnessy; Paavana Sainath

doi:10.1117/12.481158

15 May 2003 Convolution reconstruction algorithm for multi-slice helical CT

Jiang Hsieh, Brian Grekowicz, Piero Simoni, Jean-Baptiste Thibault, Mukta C. Joshi, Sandeep Dutta, Eugene C. Williams, Charlie Shaughnessy, Paavana Sainath

Author Affiliations +

Proceedings Volume 5032, Medical Imaging 2003: Image Processing; (2003) https://doi.org/10.1117/12.481158
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

One of the most recent technological advancements in computed tomography (CT) is the introduction of multi-slice CT (MSCT). The state-of-the-art MSCT contains 16 detector rows and is capable of acquiring 16 projections simultaneously. In this paper, we propose a reconstruction algorithm that makes use of nontraditional reconstruction planes and convolution weighting. To minimize the impact of interpolation on slice-sensitivity-profile (SSP), conjugate samples are used for the projection interpolation. We use multiple convex planes as teh region of construction. This allows the generated weighting function to be smooth and differentiable. In addition, we make use of the fact that projections collected from a subset of detector rows are sufficient to perform a complete reconstruction. A convolution function is applied to the weighting function of each subset to minimize the impact of cone beam effects. The convolution function is chosen so that optimal balance is achieved between image artifact, slice-sensitivity-profile (SSP), and noise. Extensive phantom and clinical studies have been conducted to validate our approach. Our study indicates that compared to other row-interpolation based reconstruction algorithms, a 30% SSP improvement can be achieved with the proposed approach. In addition, image artifact suppression achieved with the proposed approach is on par or slightly better than the existing reconstruction algorithms. Extensive clinical studies have shown that the 16-slice scanner in conjugation with this algorithm produces nearly isotropic spatial resolution and allows much improved diagnostic image quality.

Citation Download Citation

Jiang Hsieh, Brian Grekowicz, Piero Simoni, Jean-Baptiste Thibault, Mukta C. Joshi, Sandeep Dutta, Eugene C. Williams, Charlie Shaughnessy, and Paavana Sainath "Convolution reconstruction algorithm for multi-slice helical CT", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.481158

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