Tissue characterization from X-ray images

The study of the fine-scale structure of biological tissues is crucial for diagnosing a wide number of different diseases. In X-ray images, fine structures usually induce a correlation among image gray levels and are commonly perceived as textures. In this paper, we report on a Computer Vision approach to the characterization of biological tissues as imaged by standard X-ray techniques. In particular, using features derived from co-occurrence matrices, we have assessed spatial gray-level dependence of bone tissue and lung parenchyma images. A hybrid neural network was adopted to distinguish pathological tissues from normal ones and to classify different pathologies.