The Fractal Lab - Fractal Geometry in Medicine and Biology

It is well known that fractal analysis of images is dependent by several aspects correlated to the image analysis, such as resolution, luminosity, threshold to segment the object, and so on.
In Magnetic Resonance images the intensity of the signal can be influenced by the features of the object (tumor borders, for example, or intratumoral signal), as well by the different post-processing parameters, the number of multiplied phase masks, etc. The choice of the threshold to segment the MR images can influence the value of fractal dimension, in special way when different thresholds are required to extract the same object from different slices of the same patient or from different images'series. Many methods and filters have been proposed to automatically "normalize" some characteristic of the image, as luminosity. The BPN was developed by the computer scientist of the vFL to normalize the luminosity of the images of brain tumors in ultra-high field (7 Tesla) - MR imaging. The actual parameters of the program are imposed to normalize the intratumoral SWI-patterns in 7T-SWI-MR images. After the normalization, it was possible to use the same threshold to extract the object and quantify by means of the fractal dimension the intratumoral SWI-patterns (Di Ieva A. et al. Fractal Analysis of the susceptibility weighted imaging patterns in malignant brain tumors during antiangiogenic treatment: technical report of four cases serially imaged by 7 T magnetic resonance during a period of four weeks. World Neurosurg. 77:785.e11-21, 2012).

Software doesn't need installation. Just download the Zip file, unzip in any folder and run the BrightNorm application. Please follow instruction in Readme.txt included in the Zip file.

Brightness Progressive Normalization