THE ALGORITHM OF IMAGE PROCESSING OF THIN LAYER COMPUTED TOMOGRAPHY FOR CREATING THREE-DIMENSIONAL MODEL OF THE HUMAN BRONCHIAL TREE OUTER CONTOURS

Modern medical diagnostic methods must demonstrate the results of patients’ examination to the full extent. Among all available medical research methods most extensive amount of image data can be obtained by X-ray thin-layer computer tomography (CT). Thin-layer CT is a type of X-ray examination, during which the recording is done layer by layer at different depths with a predetermined interval between the layers. The result is a set of two-dimensional shadow flat images of the longitudinal cross section of a human body. Currently in clinical practice, this method is used widely, however, in certain medical practice only flat longitudinal sections of the image of the human body are analyzed; a three-dimensional reconstruction is rarely used. But this three-dimensional interpretation of the results has a clear advantage, and primarily increases the accuracy and speed of diagnosis. Standard methods for three-dimensional reconstruction, built into the software that comes with the equipment for tomography, have a limited capacity. The aim of this study is to search for possible broadening of opportunities of volumetric interpretation of the results with other available imaging software. The article suggests an algorithm of image processing received with the thin layer CT which includes the following steps: setting the contrast, binarization, filtering, inversion, imaging, correction and calculation. The proposed algorithm can improve the information content of the method of thin layer X-ray CT through the construction of axonometric (three-dimensional) images of outer contours of the human bronchial tree similar to real life-size anatomical parameters without intervention, that is to say, noninvasively.

computed tomography, medical diagnostics, image processing, lungs, respiratory system, bronchoscopy, bronchial tree, three-dimensional modeling, visualization, anatomy

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