IEEE TRANSACTIONS ONCOMPUTATIONAL IMAGING, VOL. 6, 2020 167
Microwave Breast Imaging Using a Dry Setup
João M. Felício , Member, IEEE, José M. Bioucas-Dias , Fellow, IEEE, Jorge R. Costa , Senior Member, IEEE,
and Carlos A. Fernandes , Senior Member, IEEE
Abstract—This article demonstrates for the first time, both
numerically and experimentally, the feasibility of radar-based
microwave imaging of anthropomorphic heterogeneously dense
breasts in prone position, requiring no immersion liquid. The dry,
contactless approach greatly simplifies the setup, favors patient
comfort, and further avoids lengthy sanitation procedures after
each exam. We use a radar-type technique with the antennas
distributed in cylindrical configuration around the breast phan-
tom. The reflectivity map is reconstructed using a wave-migration
algorithm in the frequency domain. This article presents new
developed strategies to cope with the challenges of a dry setup,
namely increased skin artifact due to the concomitant absence
of matching liquid and nonuniform breast shape. We propose an
iterative and adaptive algorithm based on singular value decom-
position that effectively removes the skin backscattering under
the abovementioned conditions. It is compatible with automatic
processing, and computationally fast. One of its inputs is the breast
three-dimensional surface information, and its distance to the
antennas, all obtained automatically from a proposed low-cost
procedure based on a webcam. The imaging method is reasonably
resilient to the presence of fibroglandular tissues, and to uncer-
tainties of tissue permittivity. Another tackled challenge is the
miniaturization of the antenna in air, which is achieved with an
optimized balanced antipodal Vivaldi of the same size as coun-
terparts used in dense immersion liquids. Finally, all the building
blocks are combined to demonstrate experimentally the overall dry
system performance, with very good detection of the tumor at three
different positions in the breast, even in low-contrast scenarios.
Index Terms—Artifact removal, balanced antipodal Vivaldi
antenna (BAVA), breast surface estimation, broadband antenna,
dry imaging setup, heterogeneous breast imaging, inverse prob-
lem, medical microwave imaging (MWI), phantom, singular value
decomposition (SVD), skin backscattering, cascade transmission
line, wave-migration.
Manuscript received April 6, 2019; revised June 24, 2019; accepted July 6,
2019. Date of publication July 26, 2019; date of current version January 13,
2020. This work was supported in part by Fundação para a Ciência e Tecnologia
under Project PTDC/EEI-TEL/30323/2017 and Grant SFRH/BD/115671/2016,
in part by Instituto de Telecomunicações, and Universidade de Lisboa, in part
by the FCT/MEC through national funds, and in part by the FEDER—PT2020
partnership agreement under Project UID/EEA/50008/2019. This work has been
developed in the framework of COST Action TD1301 (MiMed). The associate
editor coordinating the review of this manuscript and approving it for publication
was Dr. Francesco Soldovieri. (Corresponding author: João M. Felício.)
J. M. Felício and J. R. Costa are with Instituto de Telecomunicações,
Instituto Superior Técnico, Universidade de Lisboa, Lisbon 1049-001,
Portugal, and also with Departamento de Ciências e Tecnologias de Informação,
Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon 1649-026, Portugal
(e-mail: joao.felicio@lx.it.pt; jorge.costa@iscte-iul.pt).
J. M. Bioucas-Dias and C. A. Fernandes are with Instituto de Telecomuni-
cações, Instituto Superior Técnico, Universidade de Lisboa, Lisbon 1049-001,
Portugal (e-mail: bioucas@lx.it.pt; carlos.fernandes@lx.it.pt).
Digital Object Identifier 10.1109/TCI.2019.2931079
I. INTRODUCTION
O
VER the last two decades, Microwave Imaging (MWI) has
been investigated as an alternative imaging modality for
breast cancer screening. De facto techniques, such as mammog-
raphy (X-rays) and Magnetic Resonance Imaging (MRI), have
well known limitations [1], which contributed to the emergence
of new technologies.
Active MWI systems illuminate the breast with electromag-
netic (EM) energy usually comprised in the frequency spectrum
between 1 GHz and 10 GHz. The microwave energy is radiated
by antennas distributed around the breast. Given the permittivity
contrast of different tissues, the EM waves are scattered and
picked up by the same or separate antennas [1]. In the specific
case of breast cancer detection, MWI benefits from high contrast
between healthy and malignant tissues [1].
It is common to categorize MWI methods as quantitative or
qualitative. The first type aims at spatially mapping the dielectric
properties of media in the frequency-domain, for instance by
means of the distorted Born’s or Rytov’s linear approximation
[2], [3]. Quantitative methods involve time-consuming iterative
calculations to find the solutions of ill-posed inverse problem,
which depends greatly on the accuracy of the forward model and
on good initializations [2], [4]. In contrast, qualitative imaging
aims at reconstructing the reflectivity of a given volume [5] and
is compatible with real-time examinations. In the present work
we focus on qualitative techniques based on radar-approach.
Due to the restricted bandwidth and relatively large wave-
lengths, the attainable resolution of microwaves is of a few cen-
timeters in free-space, which contrasts with the fine resolution
of X-rays. Nevertheless, unlike mammography, microwaves do
not pose any health risk and are compatible with contactless
imaging setup. Moreover, medical MWI is intended as a primary
screening examination method and not as the ultimate and
single-validation examination. In case of such detection, patients
would be forwarded to other exams, such as MRI or ultra-
sound. We highlight that this is already standard procedure with
mammography. The attainable resolution using microwaves is
addressed in more detail ahead in this article.
Given the high permittivity contrast between skin and air,
the received signals are dominated by this early-time reflec-
tion [6]. This artifact is easily hundreds of times larger in
magnitude than the tumor response, which can potentially mask
the tumor, thus precluding its detection. Consequently, before
addressing the image reconstruction, it is necessary to eliminate
(or at least significantly reduce) the early-time response from
the skin. This processing step is known as artifact removal.
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