SUMMARY:We have developed a new algorithm to calculate the fractal dimension of dog kidney proximal convoluted tubule section. This algorithm is intermediate between box-counting and perimeter-stepping algorithms. The result of this new algorithm and correlations found between fractal dimensions and other Euclidian values of these tubuli, suggest that this algorithm is adequate to calculate fractal dimensions by points.

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The possibility of characterizing the proximal convoluted tubuli of the dog kidney by means of a unique and objective value, is an attractive idea in order to automate its recognition in anatomy and patology. For this, we obtained a fractal dimension of the proximal convoluted tubuli in the dog kidney by mean box-counting method. The fractal value we obtained is a flat dimension, and it is different than the line fractal dimension of the dog kidney arterial pattern, which was previously calculated by us (Gil et al., 2006). Thus, from optical microscopy images, we are able to obtain a single quantitative measure to discriminate these dog kidney components. This measures can use to automate its recognition. Fractal geometry provides many advantages when examining the complex microscopical images of natural objects.

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