GPU-based Iterative Cone Beam CT Reconstruction Using Tight Frame Regularization

X-ray imaging dose from serial cone-beam CT (CBCT) scans raises a clinical concern in most image guided radiation therapy procedures. It is the goal of this paper to develop a fast GPU-based algorithm to reconstruct high quality CBCT images from undersampled and noisy projection data so as to lower the imaging dose. For this purpose, we have developed an iterative tight frame (TF) based CBCT reconstruction algorithm. A condition that a real CBCT image has a sparse representation under a TF basis is imposed in the iteration process as regularization to the solution. To speed up the computation, a multi-grid method is employed. Our GPU implementation has achieved high computational efficiency and a CBCT image of resolution 512\times512\times70 can be reconstructed in ~5 min. We have tested our algorithm on a digital NCAT phantom and a physical Catphan phantom. It is found that our TF-based algorithm is able to reconstrct CBCT in the context of undersampling and low mAs levels. We have also quantitatively analyzed the reconstructed CBCT image quality in terms of modulation-transfer-function and contrast-to-noise ratio under various scanning conditions. The results confirm the high CBCT image quality obtained from our TF algorithm. Moreover, our algorithm has also been validated in a real clinical context using a head-and-neck patient case. Comparisons of the developed TF algorithm and the current state-of-the-art TV algorithm have also been made in various cases studied in terms of reconstructed image quality and computation efficiency.Comment: 24 pages, 8 figures, accepted by Phys. Med. Bio

Jets in Hadron-Hadron Collisions

In this article, we review some of the complexities of jet algorithms and of the resultant comparisons of data to theory. We review the extensive experience with jet measurements at the Tevatron, the extrapolation of this acquired wisdom to the LHC and the differences between the Tevatron and LHC environments. We also describe a framework (SpartyJet) for the convenient comparison of results using different jet algorithms.Comment: 68 pages, 54 figure

A Comparison of two different jet algorithms for the top mass reconstruction at the LHC

We compare the abilities of the cluster-type jet algorithm, KtJet, and a mid-point iterating cone algorithm to reconstruct the top mass at the LHC. We discuss the information contained in the merging scales of cluster-type algorithms, and how this can be used in experimental analyses, as well as the different sources of systematic errors for the two algorithms. We find that the sources of systematic error are different for the two algorithms, which may help to better constrain the systematic error on the top mass at the LHC.Comment: 21 pages, 16 figures, accepted by JHE

Energy Calibration of b-Quark Jets with Z->b-bbar Decays at the Tevatron Collider

The energy measurement of jets produced by b-quarks at hadron colliders suffers from biases due to the peculiarities of the hadronization and decay of the originating B hadron. The impact of these effects can be estimated by reconstructing the mass of Z boson decays into pairs of b-quark jets. From a sample of 584 pb-1 of data collected by the CDF experiment in 1.96 TeV proton-antiproton collisions at the Tevatron collider, we show how the Z signal can be identified and measured. Using the reconstructed mass of Z candidates we determine a jet energy scale factor for b-quark jets with a precision better than 2%. This measurement allows a reduction of one of the dominant source of uncertainty in analyses based on high transverse momentum b-quark jets. We also determine, as a cross-check of our analysis, the Z boson cross section in hadronic collisions using the b-bbar final state as sigma x B(Z->b-bbar) = 1578 +636 -410 pb.Comment: 35 pages, 9 figures, submitted to Nuclear Instruments and Methods in Physics Research Section

Computed tomography from X-rays: old 2-D results, new 3-D problems

We consider old results on 2-D computerized tomography methods and their relevance to new fully 3-D problems. We examine the 2-D filtered back-projection method (FBP) from several perspectives to better understand how it works. Based on that understanding, we question whether stable, reliable reconstruction algorithms can be found for wide-detector cone-beam 3-D machines with their resulting large-slant beams. We use a numerical method of "point response function fitting" to compute convolution kernels H(u, v) (for use with back-projection) for a model slant-beam problem. These kernels exhibit disturbing growing and spreading oscillations which would greatly amplify errors in the projection data