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Briz, J. A., Nerio, A. N., Ballesteros, C., Borge, M. J. G., Martinez, P., Perea, A., et al. (2022). Proton Radiographs Using Position-Sensitive Silicon Detectors and High-Resolution Scintillators. IEEE Trans. Nucl. Sci., 69(4), 696–702.
Abstract: Proton therapy is a cancer treatment technique currently in growth since it offers advantages with respect to conventional X-ray and gamma-ray radiotherapy. In particular, better control of the dose deposition allowing to reach higher conformity in the treatments causing less secondary effects. However, in order to take full advantage of its potential, improvements in treatment planning and dose verification are required. A new prototype of proton computed tomography scanner is proposed to design more accurate and precise treatment plans for proton therapy. Our prototype is formed by double-sided silicon strip detectors and scintillators of LaBr3(Ce) with high energy resolution and fast response. Here, the results obtained from an experiment performed using a 100-MeV proton beam are presented. Proton radiographs of polymethyl methacrylate (PMMA) samples of 50-mm thickness with spatial patterns in aluminum were taken. Their properties were studied, including reproduction of the dimensions, spatial resolution, and sensitivity to different materials. Structures of up to 2 mm are well resolved and the sensitivity of the system was enough to distinguish the thicknesses of 10 mm of aluminum or PMMA. The spatial resolution of the images was 0.3 line pairs per mm (MTF-10%). This constitutes the first step to validate the device as a proton radiography scanner.
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Rodriguez-Alvarez, M. J., Sanchez, F., Soriano, A., & Iborra, A. (2010). Sparse Givens resolution of large system of linear equations: Applications to image reconstruction. Math. Comput. Model., 52(7-8), 1258–1264.
Abstract: In medicine, computed tomographic images are reconstructed from a large number of measurements of X-ray transmission through the patient (projection data). The mathematical model used to describe a computed tomography device is a large system of linear equations of the form AX = B. In this paper we propose the QR decomposition as a direct method to solve the linear system. QR decomposition can be a large computational procedure. However, once it has been calculated for a specific system, matrices Q and R are stored and used for any acquired projection on that system. Implementation of the QR decomposition in order to take more advantage of the sparsity of the system matrix is discussed.
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