Recognition of lung nodules from x-ray CT images using 3D Markov random field models

Abstract

In this paper we propose a new recognition method of lung nodules from x-ray CT images using 3D Markov random field (MRF) models. Pathological shadow candidates are detected by our Quoit filter which is a kind of mathematical morphology filter, and volume of interest (VOI) areas which include the shadow candidates are extracted. The probabilities of the hypotheses that the VOI areas come from nodules (which are candidates of cancers) and blood vessels are calculated using nodule and blood vessel models evaluating the relations between these object models using 3D MRF models. If the probabilities for the nodule models are higher, the shadow candidates are determined to be abnormal. Otherwise, they are determined to be normal. Experimental results for 38 samples (patients) are shown.