A two-level classifier for automatic medical objects classification

The goal of this paper is to describe the approach for automatic identifying human organs from a medical CT images and discuss results of its comparison to different classification methods. The main premise of this approach is the use of data sets together with the relevant domain knowledge. We test our approach on multiple CT images of chest organs (trachea, lungs, bronchus) and demonstrate usefulness and effectiveness of the resulting classifications. The presented approach can be used to assist in solving more complex medical problems.