A reconstruction method for cone-beam computed laminography based on projection transformation. (15th February 2021)

• Record Type: Journal Article
• Authors: Sun, Liang; Zhou, Guangjin; Qin, Zerui; Yuan, Songmei; Lin, Qiang; Gui, Zhiguo; Yang, Min
• Is Part Of: Measurement science & technology. Volume 32:Number 4(2021)
• Publication Date: 2021-02-15
• Subjects: computed tomography (CT) -- computed laminography (CL) -- projection transformation -- image reconstruction; Physical measurements -- Periodicals; Scientific apparatus and instruments -- Periodicals; Equipment and Supplies -- Periodicals; Science -- instrumentation -- Periodicals; Technology -- instrumentation -- Periodicals; Mesures physiques -- Périodiques; Physical measurements; Scientific apparatus and instruments; Periodicals; 502.87
• DOI: 10.1088/1361-6501/abc965
• Languages: English
• ISSNs: 0957-0233

Abstract

Abstract: X-ray computed tomography (CT) is a widely popular nondestructive testing technique for engineering and medical purposes, but its limitation is openly recognized in the inspection of large components, particularly for plate-type structures. Computed laminography (CL) avoids this defect. Nowadays, most of the existing analytical CL reconstruction approaches ignore the problem that the projection data under the CL scanning structure does not strictly meet the conditions of the standard filtered back-projection (FBP) or Feldkamp–Davis–Kress (FDK) method. Since the original CL data are directly filtered without considering the influence of the tilt angle of the CL rotation axis, this will affect the quality of the reconstructed images. In view of this situation, a conversion method of cone-beam CL data based on projection transformation is proposed, which is also referred to as the CL re-projection (CLRP). The collected CL projections can be corrected to satisfy the filtering requirements. We establish a virtual CT detector and use the CLRP to convert the known CL data into the projection on the virtual detector. Then, the FDK method commonly used in cone-beam CT is applied to reconstruct the converted data. Through the above two steps to achieve CL reconstruction. Computer simulations and experimental results show that the CLRP algorithm can accurately convert the raw CL data into those which satisfying the FDK method. The CLRP can decline the information aliasing to a certain extent. Compared with the existing CL-FBP algorithm, the CLRP-FDK method for CL reconstruction can effectively reduce image artifacts. The CLRP algorithm provides a new idea for CL reconstruction and plays an important role in practical engineering applications.