Texture Analysis of Aggressive and Nonaggressive Lung Tumor CE CT Images

  • O.S. Al-Kadi, D. Watson
  • IEEE Transactions on Biomedical Engineering, July 2008, Institute of Electrical & Electronics Engineers (IEEE)
  • DOI: 10.1109/tbme.2008.919735

Fractal analysis of CT lung tumors

What is it about?

Differentiating between aggressive and non-aggressive CT lung tumors by fractal analysis.

Why is it important?

This paper presents the potential for fractal analysis of time sequence contrast-enhanced (CE) computed tomography (CT) images to differentiate between aggressive and nonaggressive malignant lung tumors (i.e., high and low metabolic tumors). The aim is to enhance CT tumor staging prediction accuracy through identifying malignant aggressiveness of lung tumors. As branching of blood vessels can be considered a fractal process, the research examines vascularized tumor regions that exhibit strong fractal characteristics. The analysis is performed after injecting 15 patients with a contrast agent and transforming at least 11 time sequence CE CT images from each patient to the fractal dimension and determining corresponding lacunarity. The fractal texture features were averaged over the tumor region and quantitative classification showed up to 83.3% accuracy in distinction between advanced (aggressive) and early-stage (nonaggressive) malignant tumors. Also, it showed strong correlation with corresponding lung tumor stage and standardized tumor uptake value of fluoro deoxyglucose as determined by positron emission tomography.


Dr Omar S Al-Kadi
University of Jordan

The results indicate that fractal analysis of time sequence CE CT images of malignant lung tumors could provide additional information about likely tumor aggression that could potentially impact on clinical management decisions in choosing the appropriate treatment procedure.

Read Publication


The following have contributed to this page: Dr Omar S Al-Kadi