조승룡 교수

PURPOSE: As computed tomography (CT) imaging is the most commonly used modality for treatment planning in radiation therapy, metal artifacts in the planning CT images may complicate the target delineation and reduce the dose calculation accuracy. Although current CT scanners do provide certain correction steps, it is a common understanding that there is not a universal solution yet to the metal artifact reduction (MAR) in general. Particularly noting the importance of MAR for radiation treatment

Dual-energy X-ray imaging can provide material-specific image information, which is very useful in inspection tasks. Accurate and efficient material decomposition is desirable in such tasks, and we developed a fast and efficient dual-energy calibration method for high-energy X-ray cargo inspection. We designed a calibration phantom consisting of a half cylinder of lead and a half cylinder of carbon. We used a least-squares method to determine the material decomposition formula from the calibrati

We conducted a feasibility study using a total-variation minimization algorithm for image reconstruction in prospectively gated micro computed tomography (micro-CT). The total-variation (TV) minimization algorithm exploits the sparseness of the image’s gradient magnitude and can successfully reconstruct CT images from undersampled data for which conventional analytic reconstruction algorithms fail. We implemented the algorithm and applied it to sparsely-sampled data for a mouse by using a prospe

Various strategies have been developed to reduce metal artifacts in CT images, yet reduction of artifacts is successful to varying degrees. We proposed an image-based metal artifact reduction (MAR) approach incorporating an inpainting step, extraction of metal artifact-corrupted sinogram, and acquisition of a metal artifact-only image to reduce metal artifacts in an uncorrected image. In this work, a simulation study was conducted using a numerical pelvic phantom with bilateral metal inserts to