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Modelling and Objectification of Secondary X ray Irradiation on Skiagraphy Images in Clinical Conditions

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Intelligent Information and Database Systems (ACIIDS 2018)

Abstract

Secondary, also called scattered irradiation is directly linked with each clinical X ray examination. In the principle, the secondary irradiation spreads itself to all directions. Thus, besides the scanned skiagraphy image, other stored images in surrounding are affected as well. More frequently are skiagraphy images affected, worse image features the skiagraphy image has. In this paper, we have proposed the multiregional segmentation model which is able to classify and extract areas corresponding with the secondary X-ray deterioration. On the base of the segmentation model, we have defined four significantly important features well reflecting the secondary irradiation through tested distances of the X-ray source and the skiagraphy records. Those features allow for modelling of the secondary irradiation effect in a dependence of respective distance. Such predictive model is well usable in the clinical conditions for an assessment of the deterioration level of the skiagraphy image. The prediction model also shows significant differences between mobile and fixed X ray in a sense of the amount of the scattered irradiation.

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Acknowledgment

The work and the contributions were supported by the project SV4507741/2101, ‘Biomedicínské inženýrské systémy XIII’. This study was supported by the research project The Czech Science Foundation (GACR) No. 17-03037S, Investment evaluation of medical device development.

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Correspondence to Jan Kubicek .

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Kubicek, J., Augustynek, M., Vodakova, A., Penhaker, M. (2018). Modelling and Objectification of Secondary X ray Irradiation on Skiagraphy Images in Clinical Conditions. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10752. Springer, Cham. https://doi.org/10.1007/978-3-319-75420-8_35

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  • DOI: https://doi.org/10.1007/978-3-319-75420-8_35

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