Computed tomography medical image reconstruction on affordable equipment by using Out-Of-Core technique
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Otros documentos de la autoría: Chillarón, Mónica; Quintana-Ortí, Gregorio; Vidal, Vicente; Verdú, Gumersindo
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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Título
Computed tomography medical image reconstruction on affordable equipment by using Out-Of-Core techniqueFecha de publicación
2020-09Editor
ElsevierISSN
0169-2607Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/pii/S0169260719316190Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Background and objective: As Computed Tomography scans are an essential medical test, many techniques have been proposed to reconstruct high-quality images using a smaller amount of radiation. One approach is to employ ... [+]
Background and objective: As Computed Tomography scans are an essential medical test, many techniques have been proposed to reconstruct high-quality images using a smaller amount of radiation. One approach is to employ algebraic factorization methods to reconstruct the images, using fewer views than the traditional analytical methods. However, their main drawback is the high computational cost and hence the time needed to obtain the images, which is critical in the daily clinical practice. For this reason, faster methods for solving this problem are required.
Methods: In this paper, we propose a new reconstruction method based on the QR factorization that is very efficient on affordable equipment (standard multicore processors and standard Solid-State Drives) by using Out-Of-Core techniques.
Results: Combining both affordable hardware and the new software proposed in our work, the images can be reconstructed very quickly and with high quality. We analyze the reconstructions using real Computed Tomography images selected from a dataset, comparing the QR method to the LSQR and FBP. We measure the quality of the images using the metrics Peak Signal-To-Noise Ratio and Structural Similarity Index, obtaining very high values. We also compare the efficiency of using spinning disks versus Solid-State Drives, showing how the latter performs the Input/Output operations in a significantly lower amount of time. Conclusions: The results indicate that our proposed me thod and software are valid to efficiently solve large-scale systems and can be applied to the Computed Tomography reconstruction problem to obtain high-quality images. [-]
Publicado en
Computer Methods and Programs in Biomedicine, 2020, vol. 193Derechos de acceso
info:eu-repo/semantics/openAccess
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