A Measure of Prior Information of a Pathology in an EIT Anatomical Atlas

摘要

One approach to solve the Electric Impedance Tomography inverse problem is the Bayesian Inference. The use of Bayes' Rule of conditional posterior probability density functions requires the definition of two probability density functions, a prior probability density function and a likelihood. The prior probability density function is often called Anatomical Atlas when the information is based on anatomy and physiology. Sufficient prior information of a pathology is necessary in order to have this pathology correctly represented in the tomographic image. A measure of how much a particular pathology is represented in an anatomical atlas is proposed.