Author:
Jeon Duhee,Kim Woosung,Cho Hyosung,Park Myeongkyu
Abstract
Abstract
One-dimensional linear X-ray grids are typically used in clinical practice to reduce the
number of scattered X-rays reaching the detector surface, thus improving image contrast in
radiography. However, such grids can only remove scattered X-rays in one direction. Additionally,
the primary challenge in using X-ray grids in digital radiography is the presence of grid
artifacts, such as grid strip shadows and moiré, which can reduce image quality. To overcome these
difficulties, in this study, we developed a prototype two-dimensional (2D) crisscrossed grid with
a strip density of 1.724 lines/mm by adopting a high-precision sawing process to further improve
its scatter radiation removal ability and implemented it in a cone-beam computed tomography (CBCT)
system to enhance image quality. We propose a new software-based method called the grid artifact
reduction (GAR) algorithm to efficiently eliminate grid artifacts of a 2D grid in CBCT. The GAR
algorithm involves three main steps: 1) preprocessing for flat-field compensation, 2)
postprocessing for GAR, and 3) CBCT reconstruction. To verify the efficacy of the proposed
approach, we conducted an experiment on a CT quality control phantom (Pro-CT MK
II™) and quantitatively evaluated the CBCT image quality using the
contrast-to-noise ratio (CNR) and Hounsfield unit (HU) accuracy error. The CNR value measured in
the CBCT image obtained using the 2D grid and proposed GAR algorithm was 3.22, which is
approximately 4.4 times of the value obtained without GAR. Furthermore, the corresponding HU
accuracy error was 30.47, an improvement of approximately 1.3 times. These results indicate that
the proposed approach is highly efficient in eliminating scattered X-rays, thereby improving the
quality of CBCT images. Consequently, high-quality CBCT images were obtained using the proposed
approach (i.e., using a 2D crisscrossed grid in CBCT and the proposed GAR algorithm).