Informatica

Radiologists need to find a position of a slice of one computed tomography (CT) scan in another scan. The image registration is a technique used to transform several images into one coordinate system and to compare them. Such transversal plane images obtained by CT scans are considered, where ribs are visible, but it does not lessen the significance of our work because many important internal organs are located here: liver, heart, stomach, pancreas, lungs, etc. The new method is developed for registration based on the mathematical model describing the rib-bounded contour. Parameters of the mathematical model and of distribution of the bone tissue on the CT scan slice form a set of features describing a particular slice. The registration method applies translation, rotation, and scaling invariances. Several strategies of translation invariance and options of the unification of scales are proposed. The method is examined on real CT scans seeking for its best performance.

Filtering of feature matches is heuristic method aimed to reduce the number of feasible matches and is widely employed in different image registration algorithms based on local features. In this paper we propose to interpret the filtering process as an optimal classification of the matches into the correct or incorrect match classes. The statistics, according to which the filtering is performed, uses differences of the geometrical invariants obtained from ordered sets of local features (composite features) of proper cardinality. Further, we examine some computationally efficient implementation schemes of the classification. Under the assumption of Gaussian measurement error, the conditional distribution densities of invariants can be approximated by well-known linearization approach. Experimental evidences obtained from fingerprint identification, which confirm viability of the proposed approach, are presented.