Dual scan CT image recovery from truncated projections.

There are computerized tomography (CT) scanners available commercially for imaging small objects and they are often categorized as mini-CT X-ray machines. One major limitation of these machines is their inability to scan large objects with good image quality because of the truncation of projection data. An algorithm is proposed in this work which enables such machines to scan large objects while maintaining the quality of the recovered image.

Design of a portable optical emission tomography system for microwave induced compact plasma for visible to near-infrared emission lines.

A new non-invasive diagnostic system is developed for Microwave Induced Plasma (MIP) to reconstruct tomographic images of a 2D emission profile. A compact MIP system has wide application in industry as well as research application such as thrusters for space propulsion, high current ion beams, and creation of negative ions for heating of fusion plasma. Emission profile depends on two crucial parameters, namely, the electron temperature and density (over the entire spatial extent) of the plasma system.

Error analysis of tomographic reconstructions in the absence of projection data.

Error estimates for tomographic reconstructions (using Fourier transform-based algorithm) are available for cases where projection data are available. These data are used for reconstructions with different filter functions and the reliability of these reconstructions can be checked as per guidelines of those error estimates. There are cases where projection data are large (in gigabytes or terabytes) so storage of these data becomes an issue.

Monte Carlo-based energy response studies of diode dosimeters in radiotherapy photon beams.

This study presents Monte Carlo-calculated absolute and normalized (relative to a (60)Co beam) sensitivity values of silicon diode dosimeters for a variety of commercially available silicon diode dosimeters for radiotherapy photon beams in the energy range of (60)Co-24 MV. These values were obtained at 5 cm depth along the central axis of a water-equivalent phantom of 10 cm × 10 cm field size. The Monte Carlo calculations were based on the EGSnrc code system.

Fractal characterization of brain lesions in CT images.

Fractal Dimension (FD) is a parameter used widely for classification, analysis, and pattern recognition of images. In this work we explore the quantification of CT (computed tomography) lesions of the brain by using fractal theory. Five brain lesions, which are portions of CT images of diseased brains, are used for the study.