Читать книгу Machine Learning for Tomographic Imaging - Professor Ge Wang - Страница 38

In chapter 2, we have introduced tomographic reconstruction based on a learned structural dictionary in which the prior information of low-level image features is expressed as atoms, which are over-complete basis functions. This prior information is actually a result of image information extraction. Indeed, it is an essential task to find an efficient measure to express the information for various images contents. In the development of deep learning techniques, it has become a common belief now that multi-layer neural networks extract image information from different semantic levels, thereby representing image features effectively and efficiently, which is consistent with the principle of the human vision system (HVS) perceiving natural images. Therefore, in this chapter we will focus on the basic knowledge of artificial neural networks, providing the foundation for feature representation and reconstruction of medical images using deep neural networks.