Texture Analysis and Tissue Segmentation of Cryosection Images

This paper outlines the exploration of two methods to detect texture in a digital cryosection image from the Visible Human Project. For the purpose of this research, texture is defined as a regular or irregular placement of color in an image. A higher-level decision-making algorithm was employed to extract different body tissues: fat, muscle, and bone. This algorithm was designed on the premise that each body tissue has a different visible texture. Another method utilized an artificial intelligence approach, a neural net, to extract textured tissues. Each problem demands a unique neural net; hence, this neural net is customized in terms of the image dataset and the goal of texture detection.