Processing Thin Section Photos with Neural Networks and Computer Vision

The neural network, which was designed for diagnosing cardiovascular diseases was trained to identify and analyze grains at thin section photos. Identifying pores and pore throats is done with computer vision. About 150 thin section photos were processed in about 20 minutes. The output contains grain sizes and mineral composition for more than 10000 grains, and pores and pore throat diameters for several thousand of pores. Comparison with alternative methods of determining pore size distribution like Cap Curves and NMR is presented.