Computational cancer cells identification by fractal dimension analysis

In the present work a software to identify cell anomaly through their fractal dimension calculation is introduced. The cell electronic microscopic image is imported to the software in gray scale and transformed to a black and white pattern in order to eliminate possible noise due to organic material close to the cell during the acquisition of the image. The number of pixels on the image contour is determined and the box-counting method is used to obtain the fractal dimension of the cell. Results for the fractal dimension have shown in very good agreement with other calculations with the advantage that the software is user-friendly, avoiding human analysis mistakes.