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Development of Stand-Alone Filtered Backprojection and Iterative Reconstruction Methods Using the Raw CT Data Exported From Clinical Lung Screening Scans


S Young

S Young1, J Hoffman1, F Noo2, M McNitt-Gray1, (1) UCLA School of Medicine, Los Angeles, CA (2) University of Utah, Salt Lake City, UT.

Presentations

SU-E-I-35 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall


Purpose: We are developing a research pipeline for generating CT image series that represent a wide variety of acquisition and reconstruction conditions. As part of this effort, we need stand-alone filtered backprojection (FBP) and iterative reconstruction methods that: (1) can operate on the raw CT data from clinical scans and (2) can be integrated into an acquisition/reconstruction pipeline for evaluating effects of acquisition and reconstruction settings on Quantitative Imaging metrics and CAD algorithms.

Methods: Two reconstruction methods were developed: (1) a weighted FBP method, and (2) an iterative method based on sequential minimization of a penalized least-squares objective function (i.e. iterative coordinate descent). Both methods were adapted from previously-published algorithms. Using information about the raw CT data format obtained through a research agreement with Siemens Healthcare, we extracted the sinogram from a low-dose lung screening case acquired on a Sensation 64 scanner as part of the National Lung Screening Trial. We reconstructed the raw data on the scanner with a B50 kernel and again with each of our stand-alone reconstruction methods. A relatively sharp kernel was used in our FBP method to match the appearance of the B50 kernel. The iterative method used a regularization parameter of 1 and a stopping criterion of 200 iterations. The reconstructed field of view was 29 cm for all methods.

Results: Reconstructed images from our FBP method agreed very well with images reconstructed at the scanner. Computation speed was a limiting factor for the iterative method, but initial downsampled results and images of a thin slab of the scanned volume demonstrated substantial potential. Various artifacts should be addressed before direct comparisons of image quality can be made.

Conclusion: Our stand-alone FBP and iterative reconstruction methods show potential for developing a general acquisition/reconstruction research pipeline that can be applied to Quantitative Imaging and CAD applications.

Funding Support, Disclosures, and Conflict of Interest: NCI grant U01 CA181156 (Quantitative Imaging Network) and Tobacco Related Disease Research Project grant 22RT-0131.


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