Digital Twins for Development of Microwave-Based Brain Tumor Detection
Särestöniemi, Mariella; Singh, Daljeet; Heredia, Charline; Nikkinen, Juha; von und zu Fraunberg, Mikael; Myllylä, Teemu (2024-05-05)
Springer
05.05.2024
Särestöniemi, M., Singh, D., Heredia, C., Nikkinen, J., von und zu Fraunberg, M., Myllylä, T. (2024). Digital Twins for Development of Microwave-Based Brain Tumor Detection. In: Särestöniemi, M., et al. Digital Health and Wireless Solutions. NCDHWS 2024. Communications in Computer and Information Science, vol 2083. Springer, Cham. https://doi.org/10.1007/978-3-031-59080-1_18
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© 2024 The Author(s). This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
https://creativecommons.org/licenses/by/4.0/
© 2024 The Author(s). This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202405133352
https://urn.fi/URN:NBN:fi:oulu-202405133352
Tiivistelmä
Abstract
Digital twins for different healthcare applications are currently being studied actively since they could revolutionize research on customized and personalized healthcare and enable realistic evaluations of new medical devices and applications in early phase. This paper presents a study on the development of digital twins aiming to be utilized for the development of microwave technique-based brain tumor detection. Realistic anatomical models of the digital twins were designed based on magnetic resonance images (MRI) scanned from the brain with brain tumor. These twins aim to correspond to the human brain and brain tumor in terms of size, shape, and tissue dielectric properties. Furthermore, developed digital twins include both phantom models for measurement emulation as well as corresponding simulation models designed using electromagnetic simulation software. By using the developed digital twins, our aim is to evaluate microwave-based sensing technique for brain tumor detection. Evaluations were carried out using flexible ultrawideband (UWB) antennas which would be beneficial for practical solutions. Our simulation and emulation results show that microwave technique with flexible antennas has high potential for brain tumor detection.
Digital twins for different healthcare applications are currently being studied actively since they could revolutionize research on customized and personalized healthcare and enable realistic evaluations of new medical devices and applications in early phase. This paper presents a study on the development of digital twins aiming to be utilized for the development of microwave technique-based brain tumor detection. Realistic anatomical models of the digital twins were designed based on magnetic resonance images (MRI) scanned from the brain with brain tumor. These twins aim to correspond to the human brain and brain tumor in terms of size, shape, and tissue dielectric properties. Furthermore, developed digital twins include both phantom models for measurement emulation as well as corresponding simulation models designed using electromagnetic simulation software. By using the developed digital twins, our aim is to evaluate microwave-based sensing technique for brain tumor detection. Evaluations were carried out using flexible ultrawideband (UWB) antennas which would be beneficial for practical solutions. Our simulation and emulation results show that microwave technique with flexible antennas has high potential for brain tumor detection.
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