The pervasive presence of noise corrupts the data and their interpretation implies a solution of an ill-posed inverse problem. To ensure for a stable and unique solution, probability theory allows one to convert an ill-posed problem of deductive reasoning into a well-posed problem of inference. Bayesian probability theory provides the principles of inference required to solve the ill-posed problem in image analysis. Thus, focused on interferometric ALMA image data analysis, prototype softwares are proposed to enhance the Common Astronomy Software Applications package.