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Published in:
2022 | OriginalPaper | Chapter
Offer Proprietary Algorithms Still Protection of Intellectual Property in the Age of Machine Learning?
A Case Study Using Dual Energy CT Data
Authors : Andreas Maier, Seung Hee Yang, Farhad Maleki, Nikesh Muthukrishnan, Reza Forghani
Published in: Bildverarbeitung für die Medizin 2022
Publisher: Springer Fachmedien Wiesbaden
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In the domain of medical image processing, medical device manufacturers protect their intellectual property in many cases by shipping only compiled software, i.e. binary code which can be executed but is difficult to be understood by a potential attacker. In this paper, we investigate how well this procedure is able to protect image processing algorithms. In particular, we investigate whether the computation of mono-energetic images and iodine maps from dual energy CT data can be reverse-engineered by machine learning methods. Our results indicate that both can be approximated using only one single slice image as training data at a very high accuracy with structural similarity greater than 0.98 in all investigated cases.