Artificial Neural Networks and Inverse Problems of Optical Diagnostics

New possibilities of artificial neural networks (ANN) using in order to solve problems of automatic determination of inner structure and integral characteristic of object as well as outer shape and orientation of object in a case of incomplete information about object image are discussed. The new ways for solving of inverse problems of optics and its direct tasks by means ANN are represented. It is shown that in a case of known symmetry of an inhomogeneous object, ANN allow to solve inverse (tomography) problems and direct problems of optics by means of incomplete data about a function of signal distribution in a plane of the registration. It is very important when an object cannot be visualized as a whole and in a case of optically thick object as well as in a number of other cases when ordinary methods of solution of inverse problems and direct tasks can not be used. Possibilities of using of the only value of a function of signal distribution in a plane of the registration in order to determine a full distribution of local characteristics in an object with a cylindrical symmetry as well as its integral characteristics are shown. Analogous possibilities exist in a case of other known kinds of symmetry. In a case of homogeneous object, ANN allow to define a form, size and orientation of an object by means of measurement of the only value of a function of signal distribution in a plane of the registration. In prospects, this method can be used for creation of automated systems for diagnostics, testing and control in various fields of scientific and applied research as well as in industry