Pith. sign in

REVIEW 4 major objections 4 minor 105 references

Advances in Microwave Near-Field Imaging: Prototypes, Systems, and Applications

T0 review · 4 major / 4 minor · reviewed 2026-08-14 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read This survey of near-field microwave imaging prototypes shows the field shifting from simulations to real hardware across medicine, NDT, wall radar, and security.

desk verdict A useful, broad survey of microwave near-field imaging prototype hardware that is visibly unfinished in its arXiv form, with empty citations and placeholder figures that need fixing before it is trusted as an authoritative reference. read the letter →

arxiv 1909.11175 v1 pith:JIG2KC2Q submitted 2019-08-06 physics.med-ph eess.SPphysics.app-ph

Wenyi Shao This is my paper · ORCID
classification physics.med-pheess.SPphysics.app-ph
keywords near-fieldmicrowaveimagingbreasttomographyultra-widebandradartime-domainsystemsnondestructivetestingthrough-the-wallsecurityscreening
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper assembles a cross-laboratory inventory of near-field microwave imaging prototypes to establish that the field has moved from software-only simulations to working hardware in medical imaging, nondestructive testing, through-the-wall radar, and security screening. For each system it records antenna count, frequency range, acquisition hardware, and whether a coupling liquid is used, and it highlights a common architectural trend: bulky vector network analyzers (VNAs) are being replaced by compact custom receivers built from impulse generators, analog-to-digital converters, and field-programmable gate arrays. The survey reports that several breast-imaging prototypes have reached patient studies, including one with a 74% detection rate across 86 patients and 86% in dense breasts, and it identifies the attenuation-versus-resolution trade-off as the main barrier to head and torso imaging. A sympathetic reader takes away that microwave near-field imaging is a hardware reality with clinical and commercial momentum, not just a simulation topic.

What carries the argument

The organizing device is a hardware census: a table-style comparison of prototype systems grouped by application, with each entry listing the number and type of antennas, the operating frequency range, the acquisition hardware (VNA, ADC/FPGA, picoscope, or custom transceiver), and the use of coupling liquid. The review's analytical work is done by mapping every system onto those axes, which exposes recurring architectures such as multi-static rings of monopoles, 60-element conformal UWB arrays, single rotating antennas, and movable-antenna scanners. That mapping is what lets the authors claim a VNA-to-custom-receiver trend and identify attenuation versus resolution as the common physical constraint.

What would settle it

Locate the source of the empty-cited clinical sentence in the breast-imaging section and check whether it actually reports 74% sensitivity (64/86) overall and 86% in dense breasts; if no cited publication contains those numbers or re-analysis lowers them, the paper's strongest quantitative claim about clinical readiness fails.

Watch

Extended reading notes

Core claim

On its own terms, the paper's central claim is that near-field microwave imaging hardware has matured into a diverse, comparable set of prototypes, and that the design space can be organized by a few concrete parameters: antenna count (from one mechanically scanned element to 160-element arrays), operating band (roughly 0.3 to 15 GHz for medical systems, up to 104 GHz for skin probes), receiver architecture (VNA versus time-domain ADC/FPGA), and the presence or absence of a coupling medium. The survey presents this as evidence that the field's bottleneck has shifted from the unavailability of data acquisition apparatus to the integration and optimization of complete systems. It also documents a convergence: researchers in different application areas are independently dropping the VNA in favor of cheaper, faster, customized receivers, and are validating algorithms on phantoms and patients rather than only on simulated data.

Load-bearing premise

The survey's clinical-readiness conclusion rests on the accuracy of detection rates reported by prototype developers, especially the 74% (64/86) and 86% dense-breast figures, which appear with an empty citation.

Editorial extensions

If this is right

  • The reported patient studies mean that microwave breast imaging has moved beyond phantoms; if the detection rates hold, it is already a candidate screening modality.
  • The shift from VNAs to impulse-generator/ADC/FPGA receivers implies that the next commercial products will be compact and comparatively low cost.
  • For brain and lung imaging, the survey's own results show that the attenuation-versus-resolution trade-off, not antenna count, is the limiting factor, so progress there requires new physical or algorithmic approaches.
  • Rotating single-antenna and movable-pair designs avoid mutual coupling and switching matrices, making them a viable low-cost alternative to dense arrays for inspection tasks.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Beyond the paper: if the 74% dense-breast figure is confirmed in the primary literature, radar-based screening could be most valuable precisely in dense breasts, where X-ray mammography performs worst.
  • Beyond the paper: the comparison table invites a quantitative benchmark that the review does not run—using antenna count, scan time, and receiver cost as predictors of reconstruction quality to see whether sparse mechanical scanning can match dense arrays.
  • Beyond the paper: the convergence on custom time-domain receivers suggests a modular design pattern—separate RF front end, digitizer, and reconstruction software—that could let future systems upgrade components independently and push costs toward consumer electronics.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The paper is a survey of microwave near-field imaging systems, organized by application domain: breast imaging, brain imaging, other medical diagnostics, nondestructive testing, through-the-wall imaging, and security screening. It describes roughly two dozen prototype and commercial systems, comparing their antenna counts, operating frequencies, hardware choices, and use of coupling liquids, and it closes with an outlook on hardware trends. The stated purpose is to provide an overview of prototype systems from different research groups worldwide. The manuscript as posted, however, contains multiple empty citations and placeholder figures, so several hardware descriptions and quantitative claims cannot currently be traced to primary sources.

Significance. If completed with proper citations and figures, this survey would be a useful reference for researchers entering the field, consolidating information about hardware architectures, antenna configurations, frequency ranges, and data acquisition strategies across medical and non-medical applications. It is particularly valuable for documenting the transition from bulky VNA-based laboratory setups to compact time-domain and FPGA-based systems, and the comparison table facilitates cross-system study. The breadth is commendable and the organization is sensible. Nevertheless, the unresolved placeholders in the posted version prevent the reader from verifying the paper's central comparative claims, especially the clinical performance numbers for the Bristol system. The survey's trustworthiness depends on accurate secondary reporting, so these gaps must be fixed before the overview can be relied upon.

major comments (4)
  1. [Microwave Breast Imaging (University of Bristol paragraph)] The clinical performance claim for the Bristol system is given with an empty citation: "achieved a detection rate of 74% (64/86) for wide age range, and achieved 86% in dense breasts []". This is the paper's strongest quantitative evidence that microwave breast imaging is clinically competitive, and the following sentence ("comparable or even better than some widely applied clinic methods") is an interpretive claim resting entirely on that number. The authors must attach the correct primary source (likely the MARIA M4 evaluation, which appears as [28] in the reference list) and verify that the figures match the source, or remove the unsupported claim.
  2. [Multiple sections] Several other assertions carry empty citations: the Calgary second-generation system, Fear's bulk dielectric permittivity system, Rubaek et al.'s time-domain system, the Kikkawa hand-held detector, the Zoughi 20-30 GHz camera, Akduman's through-the-wall system, the initial Sheen holography work, the later Sheen holographic applications, and the Abbosh lung cancer experiments ("[]-[]"). Because this paper is a survey whose value lies in accurate secondary reporting, every such placeholder must be resolved to a numbered reference so that a reader can trace each described system to its primary source.
  3. [Microwave Breast Imaging (Kikkawa) and Nondestructive Testing (Zoughi camera)] Two hardware descriptions refer to "Fig. X" placeholders: the Kikkawa hand-held breast tumor detector and the Zoughi wideband camera. Since the paper's purpose is to overview prototype hardware, these figures are load-bearing: the text describes a 4×4 cross-shaped dome antenna array, a step motor, and a CMOS-integrated pulse generator and switching matrix, all of which need the figure to be understood. The posted version is incomplete without them.
  4. [Table 1] The reference tags in the Group column of Table 1 do not match the in-text citations for the systems actually described: the Meaney row describes the 2007 16-monopole system cited in the text as [23], but is labeled [6]; the Craddock row should cite [27] or [28] rather than [10]; the Fear row should cite [31] rather than [13]; the Persson row should cite [37] rather than [17]; the Popovic row should cite [43] rather than [22]; and the Vipianna row should cite [46] rather than [25]. As the table is the principal comparative summary, the mislabeling should be corrected.
minor comments (4)
  1. [Throughout] The manuscript contains numerous typographical errors, including "complementray" (should be complementary), "archetecture" (architecture), "frection" (friction), "procude" (produce), "pusle" (pulse), "transciever" (transceiver), "Semnov" (Semenov) in the brain imaging paragraph, "stoke" (stroke) in the Figure 9 caption, "vlo." (vol.) in reference [33], "Combridge" (Cambridge) in reference [19], and "Dialectical spectroscopy" (Dielectric spectroscopy) in reference [48]. These should be corrected in revision.
  2. [Nondestructive Testing (Zoughi camera)] The phrase "An awesome video showing the working performance of the built system" is informal for a magazine article, and a YouTube link is not a stable citable source. The authors should replace this with a reference to a published paper or supplementary material, or at least remove the informal wording.
  3. [Table 1 and text] The table lists the Craddock system frequency range as "4 GHz to 8 GHz," while the text says the system can scan "up to 8 GHz" and cites the later 60-element array; please make the table and text frequency statements consistent.
  4. [Ellumen description in Nondestructive Testing] The Ellumen system is described exclusively through the authors' own references [80]-[83] and is presented in uniformly favorable terms. The authors should add a note about limitations, such as the stated scan time of "a few minutes," which is long relative to array-based systems, so that the description is balanced.

Circularity Check

0 steps flagged · score 2.0 of 10

No circular derivation: the survey is an independent inventory of third-party systems; the authors' self-citations are minor and non-load-bearing, while the empty Bristol citation is a verifiability defect, not circularity.

full rationale

This paper is a hardware survey, not a derivation chain, so the circularity patterns based on fitted inputs or imported uniqueness theorems do not apply. The central content is an organized inventory of microwave near-field imaging systems from many independent groups, with comparisons of antenna counts, frequency bands, and instrument choices. The authors' own Ellumen system is described using four self-citations, refs [80]-[83], in the nondestructive testing section; however, removing that entry would not change any comparative conclusion, and no load-bearing claim is justified only by those self-citations. A more serious limitation is verifiability rather than circularity: the Bristol MARIA result is reported as 'achieved a detection rate of 74% (64/86) for wide age range, and achieved 86% in dense breasts []' with an empty citation, and several other passages use placeholder 'Fig. X' and '[]' references. Those omissions make some secondary claims untraceable, but they do not make the paper's argument reduce to its own inputs. No equation, fitted parameter, or prior result by the same authors is renamed as a prediction. The self-citations are a minor self-promotional cluster, not circular reasoning, so the appropriate score is low.

Assumptions & free parameters 0 free parameters · 1 assumptions · 0 invented entities

The central claim is a survey; it introduces no free parameters and no invented entities. Its only substantive assumption is that the primary literature it cites is accurate and representative, an assumption that is strained by the manuscript's unresolved citation placeholders.

assumptions (1)
  • domain assumption Cited publications accurately describe the prototype systems and results attributed to them.
    The review is a secondary source; it does not independently measure or verify any system, and its clinical performance claims rest entirely on the primary literature.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Advances in Microwave Near-Field Imaging: Prototypes, Systems, and Applications." pith.science (2026). https://pith.science/paper/JIG2KC2Q

@misc{pith2026190911175,
  author       = {Pith},
  title        = {Pith review of: Advances in Microwave Near-Field Imaging: Prototypes, Systems, and Applications},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/JIG2KC2Q}},
  note         = {Machine review of arXiv:1909.11175}
}
read the original abstract

A near-field microwave imaging system attempts to reveal the presence of an object and/or an electrical property distribution by measuring the scattered field from many positions surrounding the object. Over the past few decades, both the hardware and software components of a near-field microwave imaging system technology have attracted interest throughout the world. Due to limitations of hardware technology (unavailability of data acquisition apparatus), experimental microwave imaging is very challenging for the pioneers. However, Probably due to the hardware cost, most of the studies (operating at a few GHz) were still focused on software only. The feasibility of using microwave approaches to image different types of objects have been tested and verified by simulations in a variety of applications. Further, work has been conducted on improving both quantitative and qualitative algorithms to improve simulated reconstruction results. Nowadays, benefitting from the hardware progress and reduction of their cost, researchers are eager to pursue real experimental validations instead of simulations, and, more unique prototypes and commercial systems have been built for various applications. These prototypes and systems are a result of years of dedicated work and it is important to review the advancements in developed prototype systems. The article will provide an overview of the many of the systems designed from different research groups throughout the world, for applications of near-field microwave imaging. The article further outlines challenges faced in current microwave near-field imaging, developmental tendencies of engineers and scientists, and the future outlook.

Figures

Figures reproduced from arXiv: 1909.11175 by the authors.

Figure 3
Figure 3. Monostatic radar-based microwave breast imaging system prototype developed at the University of Calgary [31]. (a) The entire view of the prototype system. (b) Reconstructed images using a confocal imaging algorithm [32] on data collected by the system for a patient. (c) Top view and (d) side view schematics of the antenna and the laser that can move around the breast. Using a VNA (especially one with multiple ports)… view at source ↗
Figure 13
Figure 13. Microwave measurement system by Collaborators from the University of Applied Sciences of Southern Switzerland, Centro di Senologia della Svizzera, and University of Genoa [78]. (a) Setup for frequency-domain measurement. (b) Breast phantom. (c) The reconstructed image of the breast phantom object with the inversion algorithm of [79] [PITH_FULL_IMAGE:figures/full_fig_p024_13.png] view at source ↗

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

105 extracted references · 80 canonical work pages

  1. [28]

    MARIA M 4: clinical evaluation of a prototype ultrawideband radar scanner for breast cancer detection,

    A. W. Preece, I. Craddock, M. Shere, L. Jones, and H. L. Winton, “MARIA M 4: clinical evaluation of a prototype ultrawideband radar scanner for breast cancer detection,” J. Medical Imaging, vol. 3, no. 3, July 2016

    work page 2016

  2. [23]

    Initial clinical experience with microwave breast imaging in women with normal mammography,

    P. M. Meaney, et al, “Initial clinical experience with microwave breast imaging in women with normal mammography,” Acad. Radiol., vol. 14, no. 2, pp. 207–218, Feb. 2007

    2007

  3. [6]

    Quantitative microwave imaging with a 2.45-GHz planar microwave camera,

    A. Franchois, A. Joisel, C. Pichot, and J.-C. Bolomey, “Quantitative microwave imaging with a 2.45-GHz planar microwave camera,” IEEE Trans. Med. Imaging, vol. 17, no. 4, pp. 550–561, Aug. 1998

    1998

  4. [27]

    Development and testing of a 60- element UWB conformal array for breast cancer imaging,

    M. Klemm, D. Gibbins, J. Leendertz, T. Horseman, A. W. Preece, R. Benjamin and I. J. Craddock, “Development and testing of a 60- element UWB conformal array for breast cancer imaging,” in Proc. 5th European Conf. Antennas and Propag. (EuCAP), Apr. 2011, pp. 3077–3079

    work page 2011

  5. [10]

    Radiometric sensing: An adjuvant to mammography to determine breast biopsy,

    K. L. Carr, P. Cevasco, P. Dunlea, and J. Shaeffer, “Radiometric sensing: An adjuvant to mammography to determine breast biopsy, ” in Proc. IEEE MTT-S Int. Microw. Symp. Dig., Jun. 2000, pp. 929–932

    2000

  6. [31]

    Microwave breast imaging with a monostatic radar-based system: A study of application to patients,

    E. C. Fear, J. Bourqui, C. Curtis, D. Mew, B. Docktor, and C. Romano, “Microwave breast imaging with a monostatic radar-based system: A study of application to patients,” IEEE Trans. Microw. Theory Techn., vol. 61, no. 5, pp. 2119–2128, May 2013. This paper has been accepted by IEEE Microwave Magazine and published on a future issue

    work page 2013

  7. [13]

    Microwave imaging techniques,

    B. D. Steinberg and H. M. Subbaram, “Microwave imaging techniques,” Wiley Series in Remote Sensing, 1991

    1991

  8. [37]

    Development of a time domain microwave system for medical diagnostics,

    X. Zeng, A. Fhager, Z. He, M. Persson, P. Linner, and H. Zirath, “ Development of a time domain microwave system for medical diagnostics,” IEEE Trans. Instrum. Meas., vol. 63, no. 12, pp. 2931–2939, Dec. 2014

    work page 2014

  9. [17]

    Microwave holography using measured point -spread functions,

    R.K. Amineh, J. McCombe, A. Khalatpour, and N.K. Nikolova, "Microwave holography using measured point -spread functions," IEEE Trans. Instrum.&Meas., vol. 64, no. 2, pp. 403-417, Feb. 2015

    2015

  10. [43]

    A wearable microwave antenna array for time-domain breast tumor screening,

    E. Porter, H. Bahrami, A. Santorelli, B. Gosselin, L. A. Rusch, and M. Popovic, “A wearable microwave antenna array for time-domain breast tumor screening,” IEEE Trans. Med. Imag., vol. 35, no. 6, pp. 1501–1509, Jun. 2016

    work page 2016

  11. [22]

    Complex permittivities of breast tumor tissues obtained from cancer surgeries,

    T. Sugitani et al., "Complex permittivities of breast tumor tissues obtained from cancer surgeries," Applied Phys. Lett. , vol. 104, 253702, June 2014

    2014

  12. [46]

    A cots-based microwave imaging system for breast cancer detection,

    M. R. Casu, M. Vacca, J. A. Tobon, A. Pulimeno, I. Sarwar, R. Solimene, and F. Vipiana, “ A cots-based microwave imaging system for breast cancer detection,” IEEE Trans. Biomed. Circuits Syst., vol. 11, no. 4, pp. 804–814, Aug. 2017

    work page 2017

  13. [25]

    Clinical trials of a UWB imaging radar for breast cancer,

    M. Klemm, I. J. Craddock, J. A. Leendertz, A. Preece , D. R. Gibbins, M. Shere, and R. Benjamin, “Clinical trials of a UWB imaging radar for breast cancer,” in Proc. 4th European Conf. Antennas and Propag. (EuCAP), Apr. 2010

    2010

Show all 105 references
  1. [1]

    Microwave interrogation of dielectric targets. Part I: By scattering parameters,

    L. E. Larsen and J. H. Jacobi, “Microwave interrogation of dielectric targets. Part I: By scattering parameters,” Med. Phys., vol. 5, no. 6, pp. 500–508, 1978

    1978

  2. [2]

    Microwave interrogation of dielec tric targets. Part II: By microwave time delay spectroscopy,

    L. E. Larsen and J. H. Jacobi, “Microwave interrogation of dielec tric targets. Part II: By microwave time delay spectroscopy,” Med. Phys., vol. 5, no. 6, pp. 509–513, 1978

    1978

  3. [3]

    L. E. Larsen and J. H. Jacobi, Eds., Medical Applications of Microwave Imaging. New York: IEEE Press, 1986

    1986

  4. [4]

    Active microwave imaging of inhomogeneous bodies,

    C. Pichot, L. Jofre, G. Peronnet , and J. -C. Bolomey, “Active microwave imaging of inhomogeneous bodies,” IEEE Trans. Antennas Propagat., vol. AP-33, no. 4, pp. 416–425, Apr. 1985

    1985

  5. [5]

    Microwave tomography: From theory to practical imaging systems,

    J. C. Bolomey and C. Pichot, “Microwave tomography: From theory to practical imaging systems,” Int. J. Imagi ng Systems and Technology, vol. 2, pp. 144-156, 1990

    1990

  6. [7]

    On the imaging of hot spots using correlation radiometers and a circular aperture,

    G. Schaller, “On the imaging of hot spots using correlation radiometers and a circular aperture,” IEEE Trans. Microw. Theory Techn., vol. 37, no. 8, pp. 1210–1216, Aug. 1989

    1989

  7. [8]

    Microwave radiometry: Its importance to the detection of cancer,

    K. L. Carr, “ Microwave radiometry: Its importance to the detection of cancer,” IEEE Trans. Microw. Theory Techn., vol. 37, no. 12, pp. 1862–1869, Dec. 1989

    1989

  8. [9]

    Microwave radiometric imaging for the characterization of breast tumors,

    S. Mouty, B. Bocquet, R. Ringot, N. Rocourt, and P. Devos, “Microwave radiometric imaging for the characterization of breast tumors,” Eur. Phys. J.: Appl. Phys., vol. 10, pp. 73–78, 2000

    2000

  9. [11]

    A clinical prototype for active microwave imaging of the breast,

    P. M. Meaney, M. W. Fanning, D. Li, S. P. Poplack , and K. D. Paulsen, “A clinical prototype for active microwave imaging of the breast,” IEEE Trans. Microw. Theory Techn., vol. 48, no. 11, pp. 1841 –1853, Nov. 2000

    2000

  10. [12]

    Enhancing breast tumor detection with near -field imaging

    E. C. Fear, et al, "Enhancing breast tumor detection with near -field imaging." IEEE Microwave magazine, vol. 3, no.1, pp. 48 -56, March 2002

    2002

  11. [14]

    Microwave imaging,

    M. Pastorino, “Microwave imaging,” John Wiley & Sons, 2010

    2010

  12. [15]

    Microwave imaging for breast cancer,

    N. K. Nikolova, “Microwave imaging for breast cancer,” IEEE Microwave magazine, vol. 12, no.7, pp. 78-94, Dec. 2011

    2011

  13. [16]

    Microwave biomedical imaging,

    N. K. Nikolova, “Microwave biomedical imaging,” Wiley Encyclopedia of Electrical and Electronics Engineering, pp 1-22, 2014

    2014

  14. [18]

    Recent advances in microwave imaging for breast cancer detection,

    S. Kwon and S. Lee, "Recent advances in microwave imaging for breast cancer detection," Int. J. Biomedical Imaging, vol. 2016, Article ID 5054912, 26 pages, 2016

    2016

  15. [19]

    Introduction to Microwave Imaging,

    Nikolova, “Introduction to Microwave Imaging,” Combridge University Press, 2017

    2017

  16. [20]

    Microwave breast imaging: clinical advances and remaining c hallenges,

    D. O'Loughlin, et al, “ Microwave breast imaging: clinical advances and remaining c hallenges,” IEEE Transactions on Biomedical Engineering, pp. 1, Feb 2018

    2018

  17. [21]

    High-resolution microwave imaging,

    Yang, et al, “High-resolution microwave imaging,” Springer Singapore, 2018

    2018

  18. [24]

    Experimental and clinical results of breast cancer detection using UWB microwave radar,

    M. Klemm, I. Craddock, J. Leendertz, A. Preece, and R. Benjamin, “Experimental and clinical results of breast cancer detection using UWB microwave radar,” in Proc. IEEE Antennas and Propag. Society Int. Symp., Jul. 2008

    2008

  19. [26]

    Microwave radar-based differential breast cancer imaging: Imaging in homogeneous breast phantoms and low contrast scenarios,

    M. Klemm, J. A. Leendertz, D. Gibbins, I. J. Craddock, A. Preece, and R. Benjamin, “ Microwave radar-based differential breast cancer imaging: Imaging in homogeneous breast phantoms and low contrast scenarios,” IEEE Trans. Antennas Propag., vol. 58, no. 7, pp. 2337 – 2344, Jul. 2010

    2010

  20. [29]

    Balanced antipodal Vivaldi antenna with dielectric director for near-field microwave imaging,

    J. Bourqui, M. Okoniewski, and E. C. Fear, “Balanced antipodal Vivaldi antenna with dielectric director for near-field microwave imaging,” IEEE Trans. Antennas Propag., vol. 58, no. 7, pp. 2318–2326, Jul. 2010

    2010

  21. [30]

    Laser surface estimation for microwave breast imaging systems,

    T. C. William, J. Bourqui, T. R. Cameron, M. Okoniewski, and E. C. Fear, “Laser surface estimation for microwave breast imaging systems,” IEEE Trans. Biomed. Eng., vol. 58, no. 5, pp. 1193–1199, May 2011

    2011

  22. [32]

    A confocal microwave imaging algorithm for breast cancer detection,

    X. Li and S. C. Hagness, “A confocal microwave imaging algorithm for breast cancer detection,” IEEE Microw. Wireless Compon. Lett., vol. 11, no. 3, pp. 130–132, Mar. 2001

    2001

  23. [33]

    Adaptive monostatic system for measuring microwave reflections from the breast,

    J. Bourqui, , M. Kuhlmann, D. J. Kurrant, B. R. Lavoie, and E. C. Fear, “Adaptive monostatic system for measuring microwave reflections from the breast,” Sensors, vlo. 18, no. 5, pp. 1-13, May 2018

    2018

  24. [34]

    System for bulk dielectric permittivity estimation of breast tissues at microwave frequencies,

    J. Bourqui and E. C. Fear, “System for bulk dielectric permittivity estimation of breast tissues at microwave frequencies,” IEEE Trans. Microw. Theory Techn., vol. 64, no. 9, pp. 3001-3009, Sep. 2016

    2016

  25. [35]

    Experimental investigation of the accuracy of an ultrawideband time-domain microwave-tomographic system,

    X. Zeng, A. Fhager, P. Linner, M. Persson, and H. Zirath, “ Experimental investigation of the accuracy of an ultrawideband time-domain microwave-tomographic system,” IEEE Trans. Instrum. Meas., vol. 60, no. 12, pp. 3939–3949, Dec. 2011

    2011

  26. [36]

    Accuracy evaluation of ultrawideband time domain systems for microwave imaging,

    X. Zeng, A. Fhager, M. Persson, P. Linner, and H. Zirath, “ Accuracy evaluation of ultrawideband time domain systems for microwave imaging,” IEEE Trans. Antennas Propag., vol. 59, no. 11, pp. 4279–4285, Nov. 2011

    2011

  27. [38]

    Design and realization of a microwave three -dimensional imaging system with application to breast-cancer detection,

    V. Zhurbenko, T. Rubaek, V. Krozer, and P. Meincke, “ Design and realization of a microwave three -dimensional imaging system with application to breast-cancer detection,” IET Microw. Antennas Propag. vol. 4, no. 12, pp. 2200-2211, Mar. 2010

    2010

  28. [39]

    An experimental system for time -domain microwave breast imaging,

    E. Porter, A. Santorelli, M. Coates, and M. Popovic, “ An experimental system for time -domain microwave breast imaging,” in Proc. 5th European Conf. Antennas and Propag. (EuCAP), Apr. 2011, pp. 2906–2910

    2011

  29. [40]

    Microwave scanning system and miniaturized microwave antenna,

    M. Popovic and H. Kanj, “Microwave scanning system and miniaturized microwave antenna,” U.S. Patent 8 089 417, Jan. 3, 2012

    2012

  30. [41]

    Time-domain multistatic radar system for microwave breast screen,

    E. Porter, E. Kirshin, A. Santorelli, M. Coates, and M. Popovic, “Time-domain multistatic radar system for microwave breast screen,” IEEE Antennas Wireless Propag. Lett., vol. 12, pp. 229–232, 2013

    2013

  31. [42]

    An early clinical study of time-domain microwave radar for breast health monitoring,

    E. Porter, M. Coates, and M. Popovic, “An early clinical study of time-domain microwave radar for breast health monitoring,” IEEE Trans. Biomed. Eng., vol. 63, no. 3, pp. 530–539, Mar. 2016

    2016

  32. [44]

    Microwave imaging for early breast cancer detection: Experimental testing of a low-cost portable system,

    J. A. Tobon Vasques, F. Vipiana, M. R. Casu, and A. Pulimeno, “Microwave imaging for early breast cancer detection: Experimental testing of a low-cost portable system,” in Proc. IEEE Int. Symp. Antennas and Propag. (APSURSI), July 2016, pp. 1479–1480

    2016

  33. [45]

    Experimental testing of a low-cost microwave imaging system for early breast cancer detection,

    J. A. Tobon Vasques, F. Vipiana, M. R. Casu, M. Vacca, and A. Pulimeno, “Experimental testing of a low-cost microwave imaging system for early breast cancer detection,” in Proc. 10th European Conf. on Antennas and Propag. (EuCAP), Apr. 2016

    2016

  34. [47]

    Detectability of breast tumor by a hand -held impulse-radar detector: performance evaluation and pilot clinical study,

    H. Song et al., “Detectability of breast tumor by a hand -held impulse-radar detector: performance evaluation and pilot clinical study,” Scientific Reports, vol. 7, no. 1, pp. 16353, Nov. 2017

    2017

  35. [48]

    Dialectical spectroscopy of canine myocardium during acute ischemia and hypoxia at frequency spectrum from 100 kHz to 6 GHz,

    S. Y. Semenov et al., “Dialectical spectroscopy of canine myocardium during acute ischemia and hypoxia at frequency spectrum from 100 kHz to 6 GHz,” IEEE Trans. Med. Imag., vol. 21, no. 6, pp. 703–707, Jun. 2002

    2002

  36. [49]

    Microwave imaging of cerebral edema,

    J. C. Lin and M. J. Clark, “Microwave imaging of cerebral edema,” Proc. IEEE, vol. 70, no. 5, pp. 523–524, May 1982

    1982

  37. [50]

    Microwave tomography for brain imaging: Feasibility assessment for stroke detection,

    S. Y. Semenov and D. R. Corfield, “Microwave tomography for brain imaging: Feasibility assessment for stroke detection,” Int. J. Antennas Propag., vol. 2008, 2008

    2008

  38. [51]

    Antenna array design for brain monitoring,

    H. Trefna and M. Persson, “Antenna array design for brain monitoring,” in Proc. IEEE Antennas and Propag. Society Int. Symp., Jul. 2008

    2008

  39. [52]

    Microwave tomography: A two-dimensional Newton iterative scheme,

    A. E. Souvorov, A. E. Bulyshev, S. Y. Semenov, R. H. Svenson, A. G. Nazarov, Y. E. Sizov, and G. P. Tatsis, “Microwave tomography: A two-dimensional Newton iterative scheme,” IEEE Trans. Microw. Theory Techn., vol. 46, no. 11, pp. 1654–1659, Nov. 1998

    1998

  40. [53]

    Microwave-based stroke diagnosis making global prehospital thrombolytic treatment possible,

    M. Persson, A. Fhager, H. D. Trefna, Y. Yu, T. McKelvey, G. Pegenius, J. -E. Karlsson, and M. Elam, “Microwave-based stroke diagnosis making global prehospital thrombolytic treatment possible,” IEEE Trans. Biomed. Eng., vol. 61, no. 11, pp. 2806–2817, Nov. 2014

    2014

  41. [54]

    Novel preprocessing techniques for accurate microwave imaging of human brain ,

    S. Mustafa, B. Mohammed, and A. Abbosh, “ Novel preprocessing techniques for accurate microwave imaging of human brain ,” IEEE Antennas Wireless Propag. Lett., vol. 12, pp. 460–463, 2013

    2013

  42. [55]

    Microwave imaging for brain stroke detection using Born iterative method,

    D. Ireland, K. Bialkowski, and A. Abbosh, “Microwave imaging for brain stroke detection using Born iterative method,” IET Microw., Antennas Propag., vol. 7, no. 11, pp. 909–915, May 2013

    2013

  43. [56]

    Microwave system for head imaging,

    B. J. Mohammed, A. M. Abbosh, S. Mustafa, and D. Ireland, “Microwave system for head imaging,” IEEE Trans. Instrum. Meas., vol. 63, no. 1, pp. 117–123, Jan. 2014

    2014

  44. [57]

    Microwave system to detect traumatic brain injuries using compact unidirectional antenna and wideband transceiver with verification on realistic head phantom,

    A. T. Mobashsher, A. M. Abbosh, and Y. Wang, “Microwave system to detect traumatic brain injuries using compact unidirectional antenna and wideband transceiver with verification on realistic head phantom,” IEEE Trans. Microw. Theory Techn., vol. 62, no. 9, pp. 1826–1836, Sep. 2014

    2014

  45. [58]

    Compact 3 -D slot -loaded folded dipole antenna with unidir ectional radiation and low impulse distortion,

    A. T. Mobashsher and A. M. Abbosh, “ Compact 3 -D slot -loaded folded dipole antenna with unidir ectional radiation and low impulse distortion,” IEEE Trans. Antennas Propag., vol. 64, no. 7, pp. 3245–3250, Jul. 2016

    2016

  46. [59]

    Microwave tomography for brain stroke imaging,

    P.-H. Touriner, F. Hecht, F. Nataf, S. Semenov, M. Bonazzoli, F. Rapetti, V. Dolean, I. El Kanfoud, I. Aliferis, C. Migliaccio, C. Pichot, “Microwave tomography for brain stroke imaging,” in Proc. IEEE Int. Symp Antennas and Propag. USNC/URSI National Radio Sci. Meeting, July ...

    2017

  47. [60]

    Numerical modeling and high -speed parallel computing: New perspectives on tomographic microwave imaging for brain stroke detection and monitoring,

    P.-H. Tournier et al, “Numerical modeling and high -speed parallel computing: New perspectives on tomographic microwave imaging for brain stroke detection and monitoring,” IEEE Antennas Propag. Magazine, vol. 59, no. 5, pp. 98–110, Oct. 2017

    2017

  48. [61]

    Microwave imaging of the knee: On sensitivity, resolution and multiple tears detection,

    S. M. Salvador, E. C. Fear, M. Okoniewski, and J. R. Matyas, “Microwave imaging of the knee: On sensitivity, resolution and multiple tears detection,” in Proc. 13th Int. Symp. Antenna Technol. Appl. Electromagn. Can. Radio Sci. Meeting, Feb. 2009, pp. 1–4

    2009

  49. [62]

    Exploring joint tissues with microwave imaging,

    S. M. Salvador, E. C. Fear, M. Okoniewski, and J. R. Matyas, “ Exploring joint tissues with microwave imaging,” IEEE Trans. Microw. Theory Techn., vol. 58, no. 8, pp. 2307–2313, Aug. 2010

    2010

  50. [63]

    Microwave imaging of the knee: Application to ligaments and tendons,

    S. M. Salvador, E. C. Fear, M. Okoniewski, and J. R. Matyas, “Microwave imaging of the knee: Application to ligaments and tendons,” in Proc. IEEE MTT-S Int. Microw. Symp. Dig., pp. 1437–1440, Jul. 2009

    2009

  51. [64]

    Microwave reflectometry as a novel diagnostic method for detection of skin cancers,

    K. Chand, P. Mehta, D. G. Beetner, R. Zoughi, and W. V. Stoecker, “Microwave reflectometry as a novel diagnostic method for detection of skin cancers,” in Proc. IEEE Instrum. Meas. Technol. Conf. Proc., May 2005, pp. 1425–1428

    2005

  52. [65]

    Microwave reflectometry as a novel diagnostic tool for detection of skin cancers,

    P. Mehta, K. Chand, D. Narayanswamy, D. G. Beetner, R. Zoughi, and W. V. Stoecker, “Microwave reflectometry as a novel diagnostic tool for detection of skin cancers,” IEEE Trans. Instrum. Meas., vol. 55, no. 4, pp. 1309–1316, Aug. 2006

    2006

  53. [66]

    Millimetre-wave waveguide reflectometers for early detection of skin cancer,

    A. Taeb, S. Gigoyan, and S. Safavi -Naeini, “Millimetre-wave waveguide reflectometers for early detection of skin cancer,” IET Microw. Antennas Propag., vol. 7, no. 14, pp. 1182–1186, Nov. 2013. This paper has been accepted by IEEE Microwave Magazine and published on a future issue

    2013

  54. [67]

    Millimeter-wave near-field probe designed for high -resolution skin cancer diagnosis,

    F. Topfer, S. Dudorov, and J. Oberhammer, “ Millimeter-wave near-field probe designed for high -resolution skin cancer diagnosis,” IEEE Trans. Microw. Theory Techn., vol. 63, no. 6, pp. 2050–2059, Jun. 2015

    2015

  55. [68]

    Millimeter wave reflectometry and imaging for noninvasive diagnosis of skin burn injuries,

    Y. Gao and R. Zoughi, “ Millimeter wave reflectometry and imaging for noninvasive diagnosis of skin burn injuries,” IEEE Trans. Instrum. Meas., vol. 66, no. 1, pp. 77–84, Jan. 2017

    2017

  56. [69]

    Lung cancer detection using frequency-domain microwave imaging,

    A. Zamani, S. A. Rezaeieh, and A. M. Abbosh, “ Lung cancer detection using frequency-domain microwave imaging,” Electronics Lett. vol. 51, no. 10, pp. 740-741, May 2015

    2015

  57. [70]

    Novel microwave torso scanner for thoracic fluid accumulation diagnosis and monitoring,

    S. A. Rezaeieh, A. Zamani, K. S. Bialkowski, and A. M. Abbosh, “Novel microwave torso scanner for thoracic fluid accumulation diagnosis and monitoring,” Scientific Reports, vol. 7, no.1, pp. 304, Mar. 2017

    2017

  58. [71]

    J. Hinken. (2016, July). Microwave Testing (µT): an overview . FI Test- und Messtechnik GmbH . [Online] Available: http://fitm.de/wp- content/uploads/2017/07/N38e-Microwave-Testing_An-Overview.pdf

    2016

  59. [72]

    Piecewise and wiener filter -based SAR techniques for monostatic microwave imaging of layered structures,

    M. Fallahpour, J. T. Case, M. T. Ghasr, and R. Zoughi, “ Piecewise and wiener filter -based SAR techniques for monostatic microwave imaging of layered structures,” IEEE Trans. Antennas Propag., vol. 62, no. 1, pp. 282–294, Jan. 2014

    2014

  60. [73]

    Wideband microwave camera for real -time 3-D imaging,

    M. T. Ghasr, M. J. Horst, M. R. Dvorsky, and R Zoughi, “Wideband microwave camera for real -time 3-D imaging,” IEEE Trans. Antennas Propag., vol. 65, no. 1, pp. 258-268, Jan. 2017

    2017

  61. [74]

    Microwave Breast Imaging System Prototype with Integrated Numerical Characterization,

    M. Haynes, J. Stang, and M. Moghaddam, “Microwave Breast Imaging System Prototype with Integrated Numerical Characterization,” Int. J. Biomed. Imaging, vol. 2012, 2012

    2012

  62. [75]

    Real-time Microwave Imaging of Differential Temperature for Thermal Therapy Monitoring,

    M. Haynes, J. Stang, and M. Moghaddam, “ Real-time Microwave Imaging of Differential Temperature for Thermal Therapy Monitoring,” IEEE Trans. Biomed. Eng., vol. 61, no. 6, pp. 1787-1796, June. 2014

    2014

  63. [76]

    A New Microwave Axial Tomograph for the Inspection of Dielectric Materials,

    A. Salvade, M. Pastorino, R. Monleone, G. Bozza, and A. Randazzo, “A New Microwave Axial Tomograph for the Inspection of Dielectric Materials,” IEEE Trans. Instrum. Meas., vol. 58, no. 7, pp. 2072-2079, Jul. 2009

    2009

  64. [77]

    A multistatic tomographic approach to mic rowave imaging of dielectric targets,

    A. Randazzo, M. Pastorino, A. Salvade, R. Monleone, M. Maffongelli, and M. Lanini, “A multistatic tomographic approach to mic rowave imaging of dielectric targets,” Proc. 5th European 5th European Conf. Antennas and Propag. (EUCAP), Apr. 2011, pp. 2790-2794

    2011

  65. [78]

    Preliminary Test of a Prototype of Microwave Axial Tomograph for Medical Applications,

    M. Maffongelli, S. Poretti, A. Salvade, R. D. Monleone, F. Meani, A. Fedeli, M. Pastorino, and A. Randazzo, “Preliminary Test of a Prototype of Microwave Axial Tomograph for Medical Applications,” Proc. Int. Symp. Medical Measurements and Applicat. (MeMeA), May. 2015

    2015

  66. [79]

    Short -Range Image -Based Method for the Inspection of Strong Scatterers Using Microwaves,

    G. Bozza, C. Estatico, A. Massa, M. Pastorino, and A. Randazzo, “Short -Range Image -Based Method for the Inspection of Strong Scatterers Using Microwaves,” IEEE Trans. Instrum. Meas., vol. 56, no. 4, pp. 1181-1188, Aug. 2007

    2007

  67. [80]

    Experimental microwave near -field detection with moveable antennas,

    W. Shao, A. Edalati, T. R. McCollough, W. J. McCollough, “Experimental microwave near -field detection with moveable antennas,” i n Proc. IEEE Int. Symp Antennas and Propag. USNC/URSI National Radio Sci. Meeting, July 2017, pp. 2387–2388

    2017

  68. [81]

    A time-domain measurement system for UWB microwave imaging,

    W. Shao, A. Edalati, T. R. McCollough, W. J. McCollough, “A time-domain measurement system for UWB microwave imaging,” IEEE Trans. Microw. Theory Techn., vol. 66, no. 5, pp. 2265–2275, Feb. 2018

    2018

  69. [82]

    Microwave imaging device,

    W. J. McCollough, T. R. McCollough, W. Shao, A. Edalati, and J. R. Leslie, “Microwave imaging device,” U.S. Patent 9 869 641, Jan. 16, 2018

    2018

  70. [83]

    A phase confocal method for near -field microwave imaging,

    W. Shao, A. Edalati, T. R. McCollough, W. J. McCollough, “A phase confocal method for near -field microwave imaging,” IEEE Trans. Microw. Theory Techn., vol. 65, no. 7, pp. 2508–2515, Jul. 2017

    2017

  71. [84]

    Microwave Imaging using Normal Electric-Field Components Inside Metallic Resonant Chambers,

    M. Asefi, A. Zakaria, and J. LoVetri, “Microwave Imaging using Normal Electric-Field Components Inside Metallic Resonant Chambers,” IEEE Trans. Microw. Theory Techn., vol. 65, no. 3, pp. 923-933, Mar. 2017

    2017

  72. [85]

    A Near -Field Dual Polarized (TE–TM) Microwave Imaging System,

    M. Ostadrahimi, A. Zakaria, J. LoVetri, and L. Shafai, “A Near -Field Dual Polarized (TE–TM) Microwave Imaging System,” IEEE Trans. Microw. Theory Techn., vol. 61, no. 3, pp. 1376-1384, Mar. 2013

    2013

  73. [86]

    Wideband synthetic aperture beamforming for through-the-wall imaging,

    M. G. Amin and F. Ahmad, “Wideband synthetic aperture beamforming for through-the-wall imaging,” IEEE Signal Processing Mag., vol. 25, no. 4, pp. 110–113, Jul. 2008

    2008

  74. [87]

    Target detection in single-and-multiple-view through-the-wall radar imaging ,

    C. Debes, M. G. Amin, and A. M. Zoubir, “ Target detection in single-and-multiple-view through-the-wall radar imaging ,” IEEE Trans. Geosci. Remote Sens., vol. 47, no. 5, pp. 1349–1361, May 2009

    2009

  75. [88]

    Enhanced detection using target polarization signatures in through-the-wall radar imaging,

    C. Debes, A. M. Zoubir, and M. G. Amin, “Enhanced detection using target polarization signatures in through-the-wall radar imaging,” IEEE Trans. Geosci. Remote Sens., vol. 50, no. 5, pp. 1968–1979, May 2012

    1968

  76. [89]

    Effect of wall parameters on ultra -wideband synthetic aperture through -the-wall radar imaging,

    X. Liu, H. Leung, and G. A. Lampropoulos, “ Effect of wall parameters on ultra -wideband synthetic aperture through -the-wall radar imaging,” IEEE Trans. Aerosp. Electron. Syst., vol. 48, no. 4, pp. 3435–3449, Oct. 2012

    2012

  77. [90]

    Through-wall detection of human being’s movement by UWB radar,

    J. Li, Z. Zeng, J. Sun, and F. Liu, “ Through-wall detection of human being’s movement by UWB radar,” IEEE Geosci. Remote Sens. Lett., vol. 9, no. 6, pp. 1079–1083, Nov. 2012

    2012

  78. [91]

    Improved human respiration detection method via ultra -wideband radar in through-wall or other similar conditions,

    S. Wu, K. Tan, Z. Xia, J. Chen, S. Meng, and F. Guangyou, “Improved human respiration detection method via ultra -wideband radar in through-wall or other similar conditions,” IET Radar Sonar Navigation, vol. 10, no. 3, pp. 468–476, Feb. 2016

    2016

  79. [92]

    An improved algo rithm for through -wall target detection using ultra -wideband impulse radar,

    X. Liang, H. Zhang, G. Fang, S. Ye, and T. A. Gulliver, “ An improved algo rithm for through -wall target detection using ultra -wideband impulse radar,” IEEE Access, vol. 5, pp. 22101–22118, Oct. 2017

    2017

  80. [93]

    Experimental validation of a simple system for through -the-wall inverse scattering ,

    I. Akduman, L. Crocco, and F. Soldovieri, “Experimental validation of a simple system for through -the-wall inverse scattering ,” IE EE Geosci. Remote Sens. Lett., vol. 8, no. 2, pp. 258-262, Mar. 2011

    2011

  81. [94]

    Detection of concealed individuals based on their vital signs by using a see-through-wall imaging system with a self -injection-locked radar,

    F. Wang, T. Horng, K.-C. Peng, J.-K. Jau, J.-Y. Li, and C.-C. Chen, “Detection of concealed individuals based on their vital signs by using a see-through-wall imaging system with a self -injection-locked radar,” IEEE Trans. Microw. Theory Techn ., vol. 61, no. 1, pp. 696 –704,...

    2013

  82. [95]

    Frequency -modulated interrupted continuous wave as wall removal technique in through -the- wall imaging,

    F. Fioranelli, S. Salous, and X. Raimundo, “Frequency -modulated interrupted continuous wave as wall removal technique in through -the- wall imaging,” IEEE Trans. Geosci. Remote Sens., vol. 52, no. 10, pp. 6272–6283, Oct. 2014

    2014

  83. [96]

    Simulation framework for compressive sensing-based through-wall detection of moving targets,

    V. Dang and O. Kilic, “Simulation framework for compressive sensing-based through-wall detection of moving targets,” IET Radar, Sonar Navigation, vol. 11, no. 9, pp. 1349–1358, Sep. 2017

    2017

  84. [97]

    Time reversal technique based on spatiotemporal windows for through the wall imaging,

    V. C. Odedo, M. E. Yavuz, F. Costen, R. Himeno, and H. Yokota, “Time reversal technique based on spatiotemporal windows for through the wall imaging,” IEEE Trans. Antennas Propag., vol. 65, no. 6, pp. 3065–3072, Jun. 2017

    2017

  85. [98]

    Sparse tomographic inverse scattering approach for through -the-wall radar imaging,

    F. Soldovieri, R. Solimene, and F. Ahmad, “ Sparse tomographic inverse scattering approach for through -the-wall radar imaging,” IEEE Trans. Instrum. Meas., vol. 61, no. 12, pp. 3340–3350, Dec. 2012

    2012

  86. [99]

    Three -dimensional millimeter-wave imaging for concealed weapon detection,

    D. M. Sheen, D. L. McMakin, and T. E. Hall, “Three -dimensional millimeter-wave imaging for concealed weapon detection,” IEEE Trans. Microw. Theory Techn., vol. 49, no. 9, pp. 1581-1592, Sep. 2001

    2001

  87. [100]

    Near -field three-dimensional radar imaging techniques and applications,

    D. M. Sheen, D. L. McMakin, and T. E. Hall, “Near -field three-dimensional radar imaging techniques and applications,” Applied Optics, vol. 49, no. 19, pp. E83-E93, 2010. This paper has been accepted by IEEE Microwave Magazine and published on a future issue

    2010

  88. [101]

    A sparse aperture MIMO -SAR-based UWB imaging system for concealed weapon detection,

    X. Zhuge and A. G. Yarovoy, “A sparse aperture MIMO -SAR-based UWB imaging system for concealed weapon detection,” IEEE Trans. Geosci. Remote Sens., vol. 49, no. 1, pp. 509–518, Jan. 2011

    2011

  89. [102]

    Automatic target recognition in ultra -wideband 3 -D images for concealed weapon detection,

    X. Zhuge and A. Yarovoy, “ Automatic target recognition in ultra -wideband 3 -D images for concealed weapon detection,” in Proc. 9 th European Conf. Synthetic Aperture Radar, Apr. 2012, pp. 186–188

    2012

  90. [103]

    Non-invasive concealed weapon detection and identification using V band millimeter wave imaging radar system,

    S. Agarwal, B. Kumar, and D. Singh, “Non-invasive concealed weapon detection and identification using V band millimeter wave imaging radar system,” in Proc. National Conf. Recent Advances Electron. and Comput. Eng. (RAECE), Feb. 2015

    2015

  91. [104]

    Ray -based reconstruction algorithm for multi -monostatic radar in imaging system,

    K. P. Jaisle and C. M. Rappaport, “Ray -based reconstruction algorithm for multi -monostatic radar in imaging system,” in Proc. IEEE Int. Symp Antennas and Propag. USNC/URSI National Radio Sci. Meeting, Jul. 2017, pp. 405–406

    2017

  92. [105]

    THz absorption in fabric and its impact on body scanning for security application,

    R. Knipper, A. Brahm, E. Heinz, T. May, G. Notni, H.-G. Meyer, A. Tunnermann, and J. Popp, “THz absorption in fabric and its impact on body scanning for security application,” IEEE Trans. THz Sci. Technol., vol. 5, no. 6, pp. 999–1004, Nov. 2015

    2015

Pith tools

Reviewed August 14, 2026 · model on record in the stance chip above.