1 research outputs found
Clinical Micro-CT Empowered by Interior Tomography, Robotic Scanning, and Deep Learning
While micro-CT systems are instrumental in preclinical research, clinical
micro-CT imaging has long been desired with cochlear implantation as a primary
example. The structural details of the cochlear implant and the temporal bone
require a significantly higher image resolution than that (about 0.2 mm)
provided by current medical CT scanners. In this paper, we propose a clinical
micro-CT (CMCT) system design integrating conventional spiral cone-beam CT,
contemporary interior tomography, deep learning techniques, and technologies of
micro-focus X-ray source, photon-counting detector (PCD), and robotic arms for
ultrahigh resolution localized tomography of a freely-selected volume of
interest (VOI) at a minimized radiation dose level. The whole system consists
of a standard CT scanner for a clinical CT exam and VOI specification, and a
robotic-arm based micro-CT scanner for a local scan at much higher spatial and
spectral resolution as well as much reduced radiation dose. The prior
information from global scan is also fully utilized for background compensation
to improve interior tomography from local data for accurate and stable VOI
reconstruction. Our results and analysis show that the proposed hybrid
reconstruction algorithm delivers superior local reconstruction, being
insensitive to the misalignment of the isocenter position and initial view
angle in the data/image registration while the attenuation error caused by
scale mismatch can be effectively addressed with bias correction. These
findings demonstrate the feasibility of our system design. We envision that
deep learning techniques can be leveraged for optimized imaging performance.
With high resolution imaging, high dose efficiency and low system cost
synergistically, our proposed CMCT system has great potentials in temporal bone
imaging as well as various other clinical applications.Comment: 10 pages, 13 figures, 3 table