Major

Mathematics (M.S.)

Research Presentation Abstract

Computed tomography (CT) is image reconstruction of objects using computer processed transmission or reflection data, usually referred to as projection data, from x-ray scanning. This projection data is often modeled using line integrals, but x-rays are of finite width in reality, so the accuracy of the projection data can be improved if an area based approach is used instead. In addition emitter beam shapes affect the reconstruction e effectiveness and data collection efficiency, with the two main types of beam choice for 2-D scanning being fan beam and parallel beam. Fan beam scanning o offers some advantages over parallel beam, such as faster data collection. This presentation presents an area based fan beam projection model for CT and discusses its effectiveness based on numerical image reconstruction experiments using the proposed model, and several different reconstruction algorithms.

Keywords

Computed Tomography, Fan Beam, Projection models

Publication Type and Release Option

Presentation (Open Access)

Principal Faculty Mentor

Jiehua Zhu

Principal Faculty Mentor Email

jzhu@georgiasouthern.edu

Principal Faculty Mentor’s Department

Mathematical Sciences (COSM)

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Area Based Fan Beam Projection Model for Computed Tomography

Computed tomography (CT) is image reconstruction of objects using computer processed transmission or reflection data, usually referred to as projection data, from x-ray scanning. This projection data is often modeled using line integrals, but x-rays are of finite width in reality, so the accuracy of the projection data can be improved if an area based approach is used instead. In addition emitter beam shapes affect the reconstruction e effectiveness and data collection efficiency, with the two main types of beam choice for 2-D scanning being fan beam and parallel beam. Fan beam scanning o offers some advantages over parallel beam, such as faster data collection. This presentation presents an area based fan beam projection model for CT and discusses its effectiveness based on numerical image reconstruction experiments using the proposed model, and several different reconstruction algorithms.