We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Mammography using low-frequency electromagnetic fields with deep learning.
- Authors
Akbari-Chelaresi, Hamid; Alsaedi, Dawood; Mirjahanmardi, Seyed Hossein; El Badawe, Mohamed; Albishi, Ali M.; Nayyeri, Vahid; Ramahi, Omar M.
- Abstract
In this paper, a novel technique for detecting female breast anomalous tissues is presented and validated through numerical simulations. The technique, to a high degree, resembles X-ray mammography; however, instead of using X-rays for obtaining images of the breast, low-frequency electromagnetic fields are leveraged. To capture breast impressions, a metasurface, which can be thought of as analogous to X-rays film, has been employed. To achieve deep and sufficient penetration within the breast tissues, the source of excitation is a simple narrow-band dipole antenna operating at 200 MHz. The metasurface is designed to operate at the same frequency. The detection mechanism is based on comparing the impressions obtained from the breast under examination to the reference case (healthy breasts) using machine learning techniques. Using this system, not only would it be possible to detect tumors (benign or malignant), but one can also determine the location and size of the tumors. Remarkably, deep learning models were found to achieve very high classification accuracy.
- Subjects
DEEP learning; ELECTROMAGNETIC fields; MAMMOGRAMS; RADIOGRAPHIC films; DIPOLE antennas; X-ray imaging
- Publication
Scientific Reports, 2023, Vol 13, Issue 1, p1
- ISSN
2045-2322
- Publication type
Article
- DOI
10.1038/s41598-023-40494-x