Voxel-based comparative analysis of lung lesions in CT for therapeutic purposes.

Lung cancer remains as one of the most incident types of cancer throughout the world. Temporal evaluation has become a very useful tool when one wishes to analyze some malignancy-indicating behavior. The objective of the present work is to detect changes in the local densities of lung lesions over time (follow-up analysis). From the detected changes, local information as well as extent region of changes can complement the studies regarding the malignant or benign nature of the lesion. Based on this idea, we attempt to use techniques that allow the observation of changes in the lesion over time, based on remote sensing techniques which highlight changes occurring in the environment. The techniques used were the image differencing, image rationing, median filtering, image regression and the fuzzy XOR operator. Based on the global measurement of change percentage in the density, we found density variations which were considered significant in a range from 2.22 to 36.57 % of the volume of the lesion. The results achieved are promising since, besides the visual aspects of the changes in density of the lung lesion over time, we managed to quantify these changes and compare them by volumetric analysis, a more commonly used technique for analysis of changes in lung lesions.