A Virtual Training System for Chest Radiogram Interpretations using Anatomical Human Structures in High-Resolution CT Images

T. Hara, X. Zhou, H. Fujita, I. Kurimoto, T. Kiryu, R. Yokoyama, and H. Hoshi (Japan)

Keywords

CT images, radiogram interpretation, training system

Abstract

We have developed a virtual system for interpretation training of chest radiograms. Chest radiograms are widely used in clinic medicine, because it can be acquired and then display the internal region of human body quickly, conveniently and inexpensively. However, the overlap of the different human organ regions in chest radiograms prevents doctors (especially for trainee doctor) from understanding 3-D anatomical structures and find out abnormality of human body (patient). A system has been developed to help mainly trainee doctors to understand anatomical structures and view the different organ regions in chest radiograms more easily. The system recognized the different organ and tissue regions from the high-resolution CT images firstly, and then generates resembling conventional chest radiograms by projecting the 3-D CT images into a 2-D plane. By adjusting the projection coefficient of each organ region, we can easily reduce the obscurity problems of human organs in chest radiograms. In conclusion, the sophisticated prototype virtual training system for interpreting chest radiograms may be useful and we are now investigating the effect of actual thoracic abnormalities on the training with this system.

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