Computed Tomography(CT)is a widely used imaging technique in medical diagnosis. It relies on collecting data about an object from multiple views representing its projections and subsequently using these data to construct an image. Among the latest advances in CT is the utilization of cone-beam geometry of x-ray projections is used instead of the usual planar fan beam.This technique is called Cone Beam CT(CBCT)and promises even faster yet safer 3D imaging compared to previous CT technologies. Present reconstruction methods are classified into two main categories, namely;analytical and iterative methods. This book studied the performance of the leading reconstruction methods from both categories and investigated modifications in their parameter selection. Book also compared their quality, speed and dose quantity of x-ray radiation using analytical phantoms. The results indicate that the reconstructed volumes produced from the iterative methods provide better quality but at the cost of a higher computational complexity.Parallel computing version of the algorithms are developed and show that the computation time can be improved and decreased more than half using multi-core processing.
3D Image Reconstruction Techniques for Cone Beam Computed Tomography
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Computed Tomography(CT)is a widely used imaging technique in medical diagnosis. It relies on collecting data about an object from multiple views representing its projections and subsequently using these data to construct an image. Among the latest advances in CT is the utilization of cone-beam geometry of x-ray projections is used instead of the usual planar fan beam.This technique is called Cone Beam CT(CBCT)and promises even faster yet safer 3D imaging compared to previous CT technologies. Present reconstruction methods are classified into two main categories, namely;analytical and iterative methods. This book studied the performance of the leading reconstruction methods from both categories and investigated modifications in their parameter selection. Book also compared their quality, speed and dose quantity of x-ray radiation using analytical phantoms. The results indicate that the reconstructed volumes produced from the iterative methods provide better quality but at the cost of a higher computational complexity.Parallel computing version of the algorithms are developed and show that the computation time can be improved and decreased more than half using multi-core processing.
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