techxriv.pdf (480.06 kB)
Download fileA Real-time Breast Hyperthermia Monitoring Scheme Based on Processing of Microwave Scattering Parameters with Deep Learning
preprint
posted on 2022-01-05, 21:09 authored by Tuba YilmazTuba Yilmaz, Mehmet Nuri Akinci, Enes Girgin, Hulusi ÖnalThis study proposes a new method based on deep learning to determine whether the temperature values are at an appropriate level during the use of microwave hyperthermia method in the treatment of breast cancer. To implement our method, we utilize the temperature dependent dielectric
properties of biological tissues to generate the heating scenarios that
simulates the thermal behavior of biological tissue during the breast cancer
hyperthermia treatment. Using the temperature-dependent dielectric properties
we designated corresponding temperature thresholds, next, we labeled the malignant
tumor region and the healthy tissue region in accordance with the pre-determined
thresholds. In addition, scattering problems are solved based on treatment (hot
or heated) and pre-treatment (cool) scenarios. Using the difference between hot
and cool states, we train, test, and validate the CNN. Our main purpose in the project is to determine whether the tissue is
heated in the desired temperature region using only the single frequency
differential scattered electric field data.
Funding
The Scientific and Technological Research Council of Turkey under grant agreement 118S074.
History
Email Address of Submitting Author
girgin15@itu.edu.trORCID of Submitting Author
0000-0002-1337-4816Submitting Author's Institution
Istanbul Technical UniversitySubmitting Author's Country
- Turkey