Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (4/4 displayed)

  • 2021Submillimeter-Wave Permittivity Measurements of Bound Water in Collagen Hydrogels via Frequency Domain Spectroscopy13citations
  • 2018Terahertz biophotonics as a tool for studies of dielectric and spectral properties of biological tissues and liquids254citations
  • 2015A dielectric model of human breast tissue in terahertz regime60citations
  • 2015The Potential of the Double Debye Parameters to Discriminate between Basal Cell Carcinoma and Normal Skin33citations

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Chart of shared publication
Salkola, Mika
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Taylor, Zachary D.
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Sun, Qiushuo
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Anttila, Juha
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Baggio, Mariangela
1 / 3 shared
Brown, Elliot R.
1 / 1 shared
Pickwell-Macpherson, Emma
1 / 1 shared
Deng, Sophie X.
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Ala-Laurinaho, Juha
1 / 16 shared
Tamminen, Aleksi
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Maloney, Thaddeus
1 / 6 shared
Nefedova, Irina
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Tuchin, V. V.
1 / 1 shared
Vaks, V. L.
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Son, J. H.
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Konovko, A. A.
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Feldman, Yu
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Chernomyrdin, N. V.
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Smolyanskaya, O. A.
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Cheon, H.
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Nazarov, M. M.
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Mounaix, P.
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Cherkasova, O. P.
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Coutaz, J. L.
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Yaroslavsky, A. N.
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Ozheredov, I. A.
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Shkurinov, A. P.
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Zaytsev, K. I.
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Kistenev, Yu V.
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Kozlov, S. A.
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Guillet, J. P.
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Popov, I.
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Nguyen, H. T.
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Fitzgerald, Anthony
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Tuan, H.
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Truong, B. C. Q.
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Nguyen, Hung T.
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Fitzgerald, Anthony J.
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Tuan, Hoang Duong
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Truong, Bao C. Q.
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Chart of publication period
2021
2018
2015

Co-Authors (by relevance)

  • Salkola, Mika
  • Taylor, Zachary D.
  • Sun, Qiushuo
  • Anttila, Juha
  • Baggio, Mariangela
  • Brown, Elliot R.
  • Pickwell-Macpherson, Emma
  • Deng, Sophie X.
  • Ala-Laurinaho, Juha
  • Tamminen, Aleksi
  • Maloney, Thaddeus
  • Nefedova, Irina
  • Tuchin, V. V.
  • Vaks, V. L.
  • Son, J. H.
  • Konovko, A. A.
  • Feldman, Yu
  • Chernomyrdin, N. V.
  • Smolyanskaya, O. A.
  • Cheon, H.
  • Nazarov, M. M.
  • Mounaix, P.
  • Cherkasova, O. P.
  • Coutaz, J. L.
  • Yaroslavsky, A. N.
  • Ozheredov, I. A.
  • Shkurinov, A. P.
  • Zaytsev, K. I.
  • Kistenev, Yu V.
  • Kozlov, S. A.
  • Guillet, J. P.
  • Popov, I.
  • Nguyen, H. T.
  • Fitzgerald, Anthony
  • Tuan, H.
  • Truong, B. C. Q.
  • Nguyen, Hung T.
  • Fitzgerald, Anthony J.
  • Tuan, Hoang Duong
  • Truong, Bao C. Q.
OrganizationsLocationPeople

article

A dielectric model of human breast tissue in terahertz regime

  • Nguyen, H. T.
  • Wallace, Vincent
  • Fitzgerald, Anthony
  • Tuan, H.
  • Truong, B. C. Q.
Abstract

© 2014 IEEE. The double Debye model has been used to understand the dielectric response of different types of biological tissues at terahertz (THz) frequencies but fails in accurately simulating human breast tissue. This leads to limited knowledge about the structure, dynamics, and macroscopic behavior of breast tissue, and hence, constrains the potential of THz imaging in breast cancer detection. The first goal of this paper is to propose a new dielectric model capable of mimicking the spectra of human breast tissue's complex permittivity in THz regime. Namely, a non-Debye relaxation model is combined with a single Debye model to produce a mixture model of human breast tissue. A sampling gradient algorithm of nonsmooth optimization is applied to locate the optimal fitting solution. Samples of healthy breast tissue and breast tumor are used in the simulation to evaluate the effectiveness of the proposed model. Our simulation demonstrates exceptional fitting quality in all cases. The second goal is to confirm the potential of using the parameters of the proposed dielectric model to distinguish breast tumor from healthy breast tissue, especially fibrous tissue. Statistical measures are employed to analyze the discrimination capability of the model parameters while support vector machines are applied to assess the possibility of using the combinations of these parameters for higher classification accuracy. The obtained analysis confirms the classification potential of these features.

Topics
  • impedance spectroscopy
  • simulation