Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2022, Cilt: 15 Sayı: 2, 622 - 635, 31.08.2022
https://doi.org/10.18185/erzifbed.1130305

Öz

Kaynakça

  • American Cancer Society. Cancer Facts & Figures 2021; American Cancer Society: Atlanta, GA, USA, 2021. Available online: https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2021.html (accessed on 21 April 2022)
  • S. Kwon, S. Lee, “Recent advances in microwave imaging for breast cancer detection”, Int. J. Biomed. Imaging. 2016, 5054912
  • S.G. Orel, M.D. Schnall, “MR imaging of the breast for the detection, diagnosis, and staging of breast cancer”, Radiology 2001, 220, 13–30
  • M.A. Aldhaeebi, T.S. Almoneef, H. Attia, O.M. Ramahi, “Near-Field Microwave Loop Array Sensor for Breast Tumor Detection”, IEEE Sens. J. 2019, 19, 11867-11872
  • B. Bocquet, J. Van de Velde, A. Mamouni, Y. Leroy, G. Giaux, J. Delannoy, D. Delvalee, “Microwave radiometric imaging at 3 GHz for the exploration of breast tumours”, IEEE Trans. Microw. Theory Tech. 1990, 38, 791–793
  • S. Mouty, B. Bocquet, R. Ringot, N. Rocourt, P. Devos, “Microwave radiometric imaging (MWI) for the characterisation of breast tumours”, Eur. Phys. J. Appl. Phys. 2000, 10, 73–78
  • P.M. Meaney, M.W. Fanning, D. Li, S.P. Poplack, K.D. Paulsen, “A clinical prototype for active microwave imaging of the breast”, IEEE Trans. Microw. Theory Tech. 2000, 48, 1841–1853
  • M. Ambrosanio, P. Kosmas, V. Pascazio, “A Multithreshold Iterative DBIM-Based Algorithm for the Imaging of Heterogeneous Breast Tissues”, IEEE Trans. Biomed. Eng. 2018, 66, 509–520
  • M. Maffongelli, S. Poretti, A. Salvadè, R. Monleone, C. Pagnamenta, A. Fedeli, M. Pastorino, A. Randazzo, “Design and experimental test of a microwave system for quantitative biomedical imaging”, Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Rome, Italy, 11–13 June 2018; pp. 1–6
  • S.P. Rana, M. Dey, G. Tiberi, L. Sani, A. Vispa, G. Raspa, M. Duranti, M. Ghavami, S. Dudley, “Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging”, Clinical Data. Sci. Rep. 2019, 9, 10510
  • O.M. Bucci, G. Bellizzi, A. Borgia, S. Costanzo, L. Crocco, G. Di Massa, R. Scapaticci, “Experimental framework for magnetic nanoparticles enhanced breast cancer microwave imaging”, IEEE Access 2017, 5, 16332–16340
  • S. C. Hagness, A. Taflove, J. E. Bridges, “Two-Dimensional FDTD Analysis of a pulsed Microwave Confocal System for Breast Cancer Detection: Fixed-Focus and Antenna-Array Sensors,” in IEEE Trans. On Biomed. Eng., vol. 45, no. 12, pp. 1470-1479, Dec. 1998
  • S. C. Hagness, A. Taflove, J. E. Bridges, “Three-Dimensional FDTD Analysis of a pulsed Microwave Confocal System for Breast Cancer Detection: Design of an Antenna-Array Element,” in IEEE Trans. On Antennas Propagat., vol. 47, no. 5, pp. 783-791, May 1999
  • X. Li, S. C. Hagness, “A Confocal Microwave Imaging Algorithm for Breast Cancer Detection,” in IEEE Microwave and Wireless Letters, vol. 11, no. 3, pp. 130-132, Mar. 2001
  • S. Coarsi, A. Massa, M. Pastorino, “Numerical Assessments Concerning a Focused Microwave Diagnostic Method for Medical Applications,” in IEEE Trans. On Microwave Theory and Tech., vol. 48, no. 11, pp. 1815-1830, Nov. 2000
  • K. R. Foster, and H. P. Schwan, “Dielectric properties of tissues and biological materials: A critical review,” Critical Reviews Biomed. Eng., vol. 17, no. 1, pp. 25-102, 1989
  • K. R. Foster, and J. L. Schepps, “Dielectric properties of tumor and normal tissues at radio through microwave frequencies,” Journal Microwave Power, vol. 16, no. 2, pp. 107-119, 1981
  • E. C. Fear, M. A. Stuchly, “Microwave Detection of Breast Cancer,” in IEEE Trans. On Microwave Theory and Tech., vol.48, no. 11, pp. 1854-1863, Nov. 2000
  • J. Shea, P. Kosmas, B. Van Veen, S. Hagness, “Contrast-enhanced microwave imaging of breast tumours: A computational study using 3D realistic numerical phantoms”, Inverse Probl. 2010, 26, 074009
  • D. Byrne, M. O’Halloran, M. Glavin, E. Jones, “Data independent radar beamforming algorithms for breast cancer detection”, Prog. Electromagn. Res. 2010, 107, 331–348
  • D. Byrne, M. Sarafianou, I.J. Craddock, “Compound radar approach for breast imaging”, IEEE Trans. Biomed. Eng. 2017, 64, 40–51
  • T. Yin, F.H. Ali, C.C. Reyes-Aldasoro, “A robust and artifact resistant algorithm of ultra-wideband imaging system for breast cancer detection”, IEEE Trans. Biomed. Eng. 2015, 62, 1514–1525
  • S. Kubota, X. Xiao, N. Sasaki, Y. Kayaba, K. Kimoto, W. Moriyama, T. Kozaki, M. Hanada, T. Kikkawa, “Confocal imaging using ultra wideband antenna array on Si substrates for breast cancer detection”, Jpn. J. Appl. Phys. 2010, 49, 097001
  • I. Ünal, B. Türetken, C. Canbay, “Spherical Conformal Bow-Tie Antenna for Ultra-Wide Band Microwave Imaging of Breast Cancer Tumour”, Appl. Comput. Electromagn. Soc. J. 2014, 29
  • G.N. Bindu, S.J. Abraham, A. Lonappan, V. Thomas, C.K. Aanandan, K. Mathew, “Active microwave imaging for breast cancer detection”, Prog. Electromagn. Res. 2006, 58, 149–169
  • E. C. Fear, X. Li, S. C. Hagness, M. A. Stuchly, “Confocal Microwave Imaging for Breast Cancer Detection: Localization of Tumors in Three Dimensions,” IEEE Trans. On Biomed. Eng., vol. 49, no. 8, pp. 812-822, Aug. 2002

Breast Tumor Detection and Classification Based on Microwave Imaging

Yıl 2022, Cilt: 15 Sayı: 2, 622 - 635, 31.08.2022
https://doi.org/10.18185/erzifbed.1130305

Öz

Limitations caused by traditional breast cancer detection and screening techniques have encouraged researchers to investigate alternative solutions. This study examines the use of a microwave-based approach for tumor detection in breast tissue and related tumor type classification using matched-filtering. Radar-like confocal microwave imaging (CMI) method constructs the foundation of such tumor detection approach. In particular, a microwave pulse is first transmitted, then back-scattered pulses are collected. All major reflective sites in the breast tissue are detected by repeating this procedure on a microwave pulse transmission-reception grid, aligning captured signals in-time to focus on a particular region in the breast tissue and superimposing such time-shifted signals to improve signal-to-clutter level. In the observed signals, clutter is originated by the heterogeneity of the breast tissue while signal is originated by a tumor site as a function of its water content.
All calculations, in the study, were performed computationally in terms of a 3D Finite-Difference Time-Domain (FDTD) simulation models. For the antenna system, two cross-polarized resistively loaded bow-ties antennas were used in the computational model, and the tumor site was modeled using five different size and morphologies. Matched-filtering, on the other hand, was performed matching such obtained observations with that of a homogenous breast tissue, namely clutter-free model. Performance of the proposed approach was tested for two different antenna array resolutions, and it was observed that this parameter is important for successful detection and classification of a tumor-site in a realistic heterogenous breast tissue model.

Kaynakça

  • American Cancer Society. Cancer Facts & Figures 2021; American Cancer Society: Atlanta, GA, USA, 2021. Available online: https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/cancer-facts-figures-2021.html (accessed on 21 April 2022)
  • S. Kwon, S. Lee, “Recent advances in microwave imaging for breast cancer detection”, Int. J. Biomed. Imaging. 2016, 5054912
  • S.G. Orel, M.D. Schnall, “MR imaging of the breast for the detection, diagnosis, and staging of breast cancer”, Radiology 2001, 220, 13–30
  • M.A. Aldhaeebi, T.S. Almoneef, H. Attia, O.M. Ramahi, “Near-Field Microwave Loop Array Sensor for Breast Tumor Detection”, IEEE Sens. J. 2019, 19, 11867-11872
  • B. Bocquet, J. Van de Velde, A. Mamouni, Y. Leroy, G. Giaux, J. Delannoy, D. Delvalee, “Microwave radiometric imaging at 3 GHz for the exploration of breast tumours”, IEEE Trans. Microw. Theory Tech. 1990, 38, 791–793
  • S. Mouty, B. Bocquet, R. Ringot, N. Rocourt, P. Devos, “Microwave radiometric imaging (MWI) for the characterisation of breast tumours”, Eur. Phys. J. Appl. Phys. 2000, 10, 73–78
  • P.M. Meaney, M.W. Fanning, D. Li, S.P. Poplack, K.D. Paulsen, “A clinical prototype for active microwave imaging of the breast”, IEEE Trans. Microw. Theory Tech. 2000, 48, 1841–1853
  • M. Ambrosanio, P. Kosmas, V. Pascazio, “A Multithreshold Iterative DBIM-Based Algorithm for the Imaging of Heterogeneous Breast Tissues”, IEEE Trans. Biomed. Eng. 2018, 66, 509–520
  • M. Maffongelli, S. Poretti, A. Salvadè, R. Monleone, C. Pagnamenta, A. Fedeli, M. Pastorino, A. Randazzo, “Design and experimental test of a microwave system for quantitative biomedical imaging”, Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Rome, Italy, 11–13 June 2018; pp. 1–6
  • S.P. Rana, M. Dey, G. Tiberi, L. Sani, A. Vispa, G. Raspa, M. Duranti, M. Ghavami, S. Dudley, “Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging”, Clinical Data. Sci. Rep. 2019, 9, 10510
  • O.M. Bucci, G. Bellizzi, A. Borgia, S. Costanzo, L. Crocco, G. Di Massa, R. Scapaticci, “Experimental framework for magnetic nanoparticles enhanced breast cancer microwave imaging”, IEEE Access 2017, 5, 16332–16340
  • S. C. Hagness, A. Taflove, J. E. Bridges, “Two-Dimensional FDTD Analysis of a pulsed Microwave Confocal System for Breast Cancer Detection: Fixed-Focus and Antenna-Array Sensors,” in IEEE Trans. On Biomed. Eng., vol. 45, no. 12, pp. 1470-1479, Dec. 1998
  • S. C. Hagness, A. Taflove, J. E. Bridges, “Three-Dimensional FDTD Analysis of a pulsed Microwave Confocal System for Breast Cancer Detection: Design of an Antenna-Array Element,” in IEEE Trans. On Antennas Propagat., vol. 47, no. 5, pp. 783-791, May 1999
  • X. Li, S. C. Hagness, “A Confocal Microwave Imaging Algorithm for Breast Cancer Detection,” in IEEE Microwave and Wireless Letters, vol. 11, no. 3, pp. 130-132, Mar. 2001
  • S. Coarsi, A. Massa, M. Pastorino, “Numerical Assessments Concerning a Focused Microwave Diagnostic Method for Medical Applications,” in IEEE Trans. On Microwave Theory and Tech., vol. 48, no. 11, pp. 1815-1830, Nov. 2000
  • K. R. Foster, and H. P. Schwan, “Dielectric properties of tissues and biological materials: A critical review,” Critical Reviews Biomed. Eng., vol. 17, no. 1, pp. 25-102, 1989
  • K. R. Foster, and J. L. Schepps, “Dielectric properties of tumor and normal tissues at radio through microwave frequencies,” Journal Microwave Power, vol. 16, no. 2, pp. 107-119, 1981
  • E. C. Fear, M. A. Stuchly, “Microwave Detection of Breast Cancer,” in IEEE Trans. On Microwave Theory and Tech., vol.48, no. 11, pp. 1854-1863, Nov. 2000
  • J. Shea, P. Kosmas, B. Van Veen, S. Hagness, “Contrast-enhanced microwave imaging of breast tumours: A computational study using 3D realistic numerical phantoms”, Inverse Probl. 2010, 26, 074009
  • D. Byrne, M. O’Halloran, M. Glavin, E. Jones, “Data independent radar beamforming algorithms for breast cancer detection”, Prog. Electromagn. Res. 2010, 107, 331–348
  • D. Byrne, M. Sarafianou, I.J. Craddock, “Compound radar approach for breast imaging”, IEEE Trans. Biomed. Eng. 2017, 64, 40–51
  • T. Yin, F.H. Ali, C.C. Reyes-Aldasoro, “A robust and artifact resistant algorithm of ultra-wideband imaging system for breast cancer detection”, IEEE Trans. Biomed. Eng. 2015, 62, 1514–1525
  • S. Kubota, X. Xiao, N. Sasaki, Y. Kayaba, K. Kimoto, W. Moriyama, T. Kozaki, M. Hanada, T. Kikkawa, “Confocal imaging using ultra wideband antenna array on Si substrates for breast cancer detection”, Jpn. J. Appl. Phys. 2010, 49, 097001
  • I. Ünal, B. Türetken, C. Canbay, “Spherical Conformal Bow-Tie Antenna for Ultra-Wide Band Microwave Imaging of Breast Cancer Tumour”, Appl. Comput. Electromagn. Soc. J. 2014, 29
  • G.N. Bindu, S.J. Abraham, A. Lonappan, V. Thomas, C.K. Aanandan, K. Mathew, “Active microwave imaging for breast cancer detection”, Prog. Electromagn. Res. 2006, 58, 149–169
  • E. C. Fear, X. Li, S. C. Hagness, M. A. Stuchly, “Confocal Microwave Imaging for Breast Cancer Detection: Localization of Tumors in Three Dimensions,” IEEE Trans. On Biomed. Eng., vol. 49, no. 8, pp. 812-822, Aug. 2002
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Emin Argun Oral 0000-0002-8120-9679

Alan V. Sahakian Bu kişi benim 0000-0003-3090-0328

Erken Görünüm Tarihi 29 Ağustos 2022
Yayımlanma Tarihi 31 Ağustos 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 15 Sayı: 2

Kaynak Göster

APA Oral, E. A., & Sahakian, A. V. (2022). Breast Tumor Detection and Classification Based on Microwave Imaging. Erzincan University Journal of Science and Technology, 15(2), 622-635. https://doi.org/10.18185/erzifbed.1130305