Computer Aided Tomography Picture Analysis on the base of Stage-By-Stage Binarization and its Software Implementation
Introduction: Computed tomography shots of a body contain big amounts of information and require complex comprehensive analysis which takes a long time and often is difficult for a diagnostician. The diagnostics accuracy can be improved by the use of contrast dye, but this method is more expensive and has a number of contraindications. Purpose: Developing an automated object detection method for computed tomography shots which would provide physicians with the necessary information. Results: A parameterization method is proposed for objects on the layers of a CT shot. It performs sequential analysis of the layers and determines the area related to the examined object. In the course of the further analysis, the object is considered as an array of voxels, each of them characterizing an average density of the object in a particular zone. Furthermore, the areas of each layer are calculated, resulting in the total volume of the object. The determination of the selective dispersion for the density values of the object zones along with the density values histogram allow the diagnostician to make conclusions about the object properties and to evaluate the possibility of pathologies. Filtering the object voxels by their density values makes it possible to localize areas of the object with certain properties and to estimate the degree of symmetry for new growths in order to judge about their possible pathological nature. Practical relevance: The developed method along with its software implementation allows you to partially automate CT shot analysis by providing the medical specialists with the values of the examined object parameters: areas of each layer, total volume, sample variance of the density values, and symmetry estimation. This method makes it possible to localize the object zones with particular density values and to detect possible pathologic growths without the use of contrast dye.