Hypodensity extractor: A phantom study

Abstract

We report on the extraction procedures of low-contrast symptomatic hypodensity optimized for a computed tomography-based diagnosis. The specific application is brain imaging with enhanced perception of hypodense areas which are direct symptoms of acute ischemia. A standard low-contrast phantom, as commonly employed in dosimetry and imaging quality evaluation, was used to derive numeric criteria for assessing the extraction effectiveness. Our proposed procedure is based on multiscale analysis of the image data expanded over the frames of wavelets, curvelets or complex wavelets, followed by nonlinear approximation of the symptom signatures. Apparent subtle density changes in the phantom were evaluated using computational metrics and subjective ratings. We discuss the advantages and disadvantages of our proposed optimized hypodensity extraction procedures.