Deep Learning Enhanced Contrast Source Inversion for Microwave Breast Cancer Imaging Modality

被引：6
|
作者：
Hirose, Umita [1 ]
Zhu, Peixian [1 ]
Kidera, Shouhei [1 ]
机构：
[1] Univ Electrocommun, Grad Sch Informat & Engn, Chofu, Tokyo 1828585, Japan
来源：
IEEE JOURNAL OF ELECTROMAGNETICS RF AND MICROWAVES IN MEDICINE AND BIOLOGY | 2022年 / 6卷 / 03期
关键词：
Image reconstruction; Training; Microwave imaging; Permittivity; Transmitters; Receivers; Microwave theory and techniques; Convolutional auto-encoder (CAE); contrast source inversion (CSI); deep learning; inverse scattering analysis; microwave ultra wide-band (UWB) breast cancer detection; CONVOLUTIONAL NEURAL-NETWORK; SCATTERING;
D O I：
10.1109/JERM.2021.3127110
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This study presents a deep-learning (DL) based contrast source inversion (CSI) algorithm for quantitative microwave breast cancer imaging. Inverse scattering analysis for quantitative dielectric profile reconstruction is promising for a higher recognition rate for cancer detection, especially for malignant breast tumors. We focus on CSI as a low complexity approach, and implement a deep convolutional autoencorder (CAE) scheme using radar raw-data, which enhances the convergence speed and reconstruction accuracy. Numerical tests using MRI-derived realistic phantoms demonstrate that the proposed method significantly enhances the reconstruction performance of the CSI.
引用
收藏
页码：373 / 379
页数：7
相关论文
共 50 条
  • [1] Contrast Source Inversion Enhanced Confocal Imaging for Highly Heterogeneous Breast Media in Microwave Mammography
    Umezu, Gaku
    Yamauchi, Yoshihiro
    Kidera, Shouhei
    IEEE JOURNAL OF ELECTROMAGNETICS RF AND MICROWAVES IN MEDICINE AND BIOLOGY, 2022, 6 (04): : 494 - 500
  • [2] Deep-Learning-Based Calibration in Contrast Source Inversion Based Microwave Subsurface Imaging
    Hanabusa, Takahiro
    Morooka, Takahide
    Kidera, Shouhei
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [3] ROI Limited Unknowns Reduction-Based Contrast Source Inversion for Microwave Breast Imaging
    Sato, Hiroki
    Kidera, Shouhei
    IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, 2020, 19 (12): : 2285 - 2289
  • [4] Noise-Robust Microwave Breast Imaging Applied to Multi-Frequency Contrast Source Inversion
    Sato, Hiroki
    Kidera, Shouhei
    IEEE JOURNAL OF ELECTROMAGNETICS RF AND MICROWAVES IN MEDICINE AND BIOLOGY, 2021, 5 (02): : 187 - 193
  • [5] Polarimetry Effect in Three-dimensional Contrast Source Inversion for Microwave Breast imaging
    Zhu, Peixian
    Morimoto, Hayatomomaru
    Kidera, Shouhei
    2021 IEEE USNC-URSI RADIO SCIENCE MEETING (JOINT WITH AP-S SYMPOSIUM), 2021, : 75 - 76
  • [6] Contrast Source Inversion-Enhanced Synthetic Aperture Approach for Microwave Multilayered Subsurface Imaging
    Yamauchi, Yoshihiro
    Kidera, Shouhei
    IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2023, 71 (09) : 7538 - 7552
  • [7] Deep Learning Enhanced Microwave Imaging for Brain Diagnostics
    Ninkovic, Darko
    Ruiz, Alvaro Yago
    Cavagnaro, Marta
    Kolundzija, Branko
    Crocco, Lorenzo
    Stevanovic, Marija Nikolic
    2023 17TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION, EUCAP, 2023,
  • [8] Transfer Deep Learning for Dielectric Profile Reconstruction in Microwave Medical Imaging
    Xue, Fei
    Guo, Lei
    Bialkowski, Alina
    Abbosh, Amin M.
    IEEE JOURNAL OF ELECTROMAGNETICS RF AND MICROWAVES IN MEDICINE AND BIOLOGY, 2024, 8 (04): : 344 - 354
  • [9] MICROWAVE BREAST IMAGING VIA DEEP LEARNING
    Ambrosanio, M.
    Autorino, M. M.
    Franceschini, S.
    Baselice, F.
    Pascazio, V
    2022 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (IEEE ISBI 2022), 2022,
  • [10] Improved Deep Learning-Based Microwave Inversion With Experimental Training Data
    Cathers, Seth
    Martin, Ben
    Stieler, Noah
    Jeffrey, Ian
    Gilmore, Colin
    IEEE OPEN JOURNAL OF ANTENNAS AND PROPAGATION, 2025, 6 (02): : 522 - 534
12345