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Microwave Medical Imaging

Raquel Conceição (raquelcruzconceicao@gmail.com)

Institute of Biophysics and Biomedical Engineering (IBEB),

Faculty of Sciences, University of Lisbon, Portugal

Fundação para a Ciência e a Tecnologia

7th FP, Marie Curie Intra-European Fellowship, REA grant 301269

EPSRC: EP/J007293/1

Medical Microwave Imaging Radar

Advantages:- non-invasive- non-ionising (MW)- low-power- potentially low-cost- comfortable – no compression, quick

- differences in dielectric properties between the constituent tissues of the healthy and cancer masses at MW frequencies in shallow parts of the body

Medical Microwave Imaging Radar

First studies date back from late 1990s:- Hagness et al (1998), Two Dimensional FDTD Analysis of aPulsed Microwave Confocal System for Breast CancerDetection: Fixed-Focus and Antenna-Array Sensors- Fear et al (1999), Microwave System for Breast TumorDetection

Applications include:- Breast cancer detection- Stroke detection- Bladder volume control- Lung edema- Bone analysis…

-> How does Medical Microwave ImagingRadar work?

(examples given for breast MWI)

• Antennas at different locations surrounding the breast

Artefact Removal algorithms (remove the skin response):

Differential Rotation

Average Subtraction

Adaptive Filtering

Subtract the rotated measurements from original stored waveforms – Klemm et al

Subtract the average of all the stored waveforms from each of the original backscattered signals – Li et al

The artefact in each channel is estimated as a filtered combination of the signal in all other channels – Bond et al

Artefact Removal algorithms (remove the skin response):

Other algorithms include:

Wiener Filter Root Least Squares Filter

Entropy-based Time Windowing Hybrid Artefact Removal

Frequency Domain Skin-Artefact Removal

Neighbourhood based Skin Subtraction

Independent Component Analysis Artefact Removal Algorithm

Beamformer algorithms – Data independent beamformers:

Delay and Sum Time shift and sum the backscattered signals Hagness et al.

Beamformer algorithms – Data independent beamformers:

Delay Multiply and Sum

Delay and Sum

Channel Ranked Delay and Sum

Additional pairing multiplication procedure after time shifting

Time shift and sum the backscattered signals

Gives extra weighting to signals with shorter propagation distances

Hagness et al.

Lim et al.

O’Halloran et al.

Beamformer algorithms – Data independent beamformers:

Microwave Space-Time (MIST) Beamformer

Coherence Weighted Beamformers

Compensation for frequencydependentpropagation effects to better spatially focus the backscattered signals – Bond et al

Extension of DAS beamformer by introducing an additional weighting factor called the “Quality Factor” (QF) – Klemm et al

Beamformer algorithms – Adaptive beamforming:

Minimum Variance Capon beamformer – Haykin et al

Multistatic Adaptive Microwave Imaging – Xie et al

Transmitter-Grouping Robust Capon beamformer – Byrne et al

Wideband Time-Domain Adaptive Beamforming – Byrne et al

Beamformer algorithms – Path Dielectric Estimation Techniques

Multiple Signal Classification Time-Of-Flight – Sarafianou et al

Transmission Coefficient Method – Bourqui et al

Optimisation Based Propagation Technique – Guo et al

• Creation of an energy profile of the breast

• High-energy regions may indicate the presence of tumours

-> How to simulate radar MicrowaveImaging?

(examples given for breast MWI)

Electromagnetic propagationin the breast is simulatedwith Finite-Difference Time-Domain (FDTD) modelling.

Breast models have a typical resolution of 0.5 mm.

Different tissues are present, such as: normal (adipose andfibroglandular) tissue, skin and tumour tissue.

Tissues are mapped into a 3D FDTD grid – a Debye formulation isused to attribute the appropriate dielectric properties to each tissue:

ε∞ permittivity of the free spaceΔε relative permittivityτ relaxation time constantσs conductivity

University of Bristol

University of Bristol/ Micrima

https://www.youtube.com/watch?v=i1OoRmPntVs

-> Example of radar Microwave Imagingprototypes

University of Bristol – array of

antennas

Multistatic-based prototype

Monostatic-based prototype

University of Calgary –single scanning antenna

Imaging: Confocal Microwave ImagingConsultant’s report Microwave Image

University of Calgary

Imaging: Confocal Microwave ImagingConsultant’s report Microwave Image

University of Calgary

To sum up:

• Presentation of monostatic and multistatic radar microwave imaging systems

• Break-down of radar Microwave Imaging: i) UWB pulse, ii) skin-artefact removal, iii) beamforming

• Simulation and patient results

• Small scale studies indicate significant dielectric contrast between healthy and cancer tissue

This work has been developed in the framework of COST Action TD1301, MiMed. The goal of this COST Action is to accelerate the technological, clinical and commercialisationprogress in the area of medical Microwave Imaging andtherapeutical techniques.

Action website: http://cost-action-td1301.org

We are a network of over 200 researchers from:25 COST countries (AT, BE, BG, CH, CY, CZ, DE, DK, EL, ES, FR, HR, IE, IL, IT,

MT, NL, NO, PT, RO, RS, SE, SO, TR, UK), 1 NNC (RU) and 3 IPC countries (CA, CN, US)

This work has been developed in the framework of COST Action TD1301, MiMed. The goal of this COST Action is to accelerate the technological, clinical and commercialisationprogress in the area of medical Microwave Imaging andtherapeutical techniques.

Questions?

Thank you!