Affiliations: Britton Chance Center for Biomedical Photonics, Wuhan
National Laboratory for Optoelectronics-Huazhong University of Science and
Technology, Wuhan, China
Note: [] Corresponding author: Shangbin Chen, Britton Chance Center for
Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong
University of Science and Technology, Wuhan 430074, China. Tel.: +86 27
87792033; Fax: +86 27 87792034; E-mail: [email protected]
Abstract: The real-time imaging is important in automatic successive
inspection with micro-computerized tomography (micro-CT). Generally, the size
of the detector is chosen according to the most probable size of the measured
object to acquire all the projection data. Given enough imaging area and
imaging resolution of X-ray detector, the detector is larger than specimen
projection area, which results in redundant data in the Sinogram. The process
of real-time micro-CT is computation-intensive because of the large amounts of
source and destination data. The speed of the reconstruction algorithm can't
always meet the requirements of real-time applications. A preprocessing method
called adaptive region of interest (AROI), which detects the object's
boundaries automatically to focus the active Sinogram regions, is introduced
into the analytical reconstruction algorithm in this paper. The AROI method
reduces the volume of the reconstructing data and thus directly accelerates the
reconstruction process. It has been further shown that image quality is not
compromised when applying AROI, while the reconstruction speed is increased as
the square of the ratio of the sizes of the detector and the specimen slice. In
practice, the conch reconstruction experiment indicated that the process is
accelerated by 5.2 times with AROI and the imaging quality is not degraded.
Therefore, the AROI method improves the speed of analytical micro-CT
reconstruction significantly.
Keywords: Adaptive region of interest (AROI), Analytical micro-computerized tomography, Filter backprojection (FBP) algorithm, Feldkamp-type (FDK) algorithm
