Refining a region-of-interest within an available CT image

This paper describes a numerical method for refining the image of a region-of-interest (RoI) within an existing tomographic slice, provided that projection data are stored along with the image. Using the attributes of the image, projection values (ray-sums) are adjusted to compensate for the material outside the RoI. Advantage is taken of the high degree of overdetermination of common computed tomography systems to reconstruct an RoI image over smaller pixels. The smaller size of a region-of-interest enables the use of iterative methods for RoI image reconstruction, which are less prone to error propagation. Simulation results are shown for an anthropomorphic head phantom, demonstrating that the introduced approach enhances both the spatial resolution and material contrast of RoI images; without the need to acquire any additional measurements or to alter existing imaging setups and systems.

► A method for refining the image of a region-of-interest within an existing tomographic image. ► Refined spatial-resolution within the region-of-interest, due to high redundancy of CT data. ► Enhancement in image contrast by the use of iterative image reconstruction, made possible by the smaller problem size. ► No need for additional measurements, no alteration of existing imaging setups and systems.