Novel microwave apparatus for breast lesions detection: Preliminary clinical results

Journal article

Sani, L., Ghavami, N., Vispa, A., Paoli, M., Raspa, G., Ghavami, M., Sacchetti, F., Vannini, E., Ercolani, S., Saracini, A., Duranti, M. and Tiberi, G. (2019). Novel microwave apparatus for breast lesions detection: Preliminary clinical results. Biomedical Signal Processing and Control. 52, pp. 257-263. https://doi.org/10.1016/j.bspc.2019.04.025
AuthorsSani, L., Ghavami, N., Vispa, A., Paoli, M., Raspa, G., Ghavami, M., Sacchetti, F., Vannini, E., Ercolani, S., Saracini, A., Duranti, M. and Tiberi, G.
Abstract

This paper presents preliminary results of an innovative microwave imaging apparatus for breast lesions detection. Specially, a Huygens Principle based method is employed to process the microwave signals and to build the respective microwave images. The apparatus has been first tested on phantoms. Next, its performance has been verified through clinical examinations on 22 healthy breasts and on 29 breast having lesions, using as gold standard the output of the radiologist study review obtained using conventional techniques. Specifically, we introduce a metric, which is the ratio between maximum and average of the image intensity (MAX/AVG). We found that MAX/AVG of microwave images can be used for classifying breasts containing lesions. In addition, using MAX/AVG as classification parameter, receiver operating characteristic curves have been empirically determined. Furthermore, for one randomly selected breast having lesion, we have demonstrated that the localisation of the inclusion acquired through microwave imaging is compatible with mammography images.

KeywordsMicrowave imaging; Breast cancer detection; Huygens principle
Year2019
JournalBiomedical Signal Processing and Control
Journal citation52, pp. 257-263
PublisherElsevier
Digital Object Identifier (DOI)https://doi.org/10.1016/j.bspc.2019.04.025
Web address (URL)http://www.scopus.com/inward/record.url?eid=2-s2.0-85065238935&partnerID=MN8TOARS
Publication dates
Print09 May 2019
2019
Publication process dates
Deposited11 May 2019
Accepted18 Apr 2019
Accepted author manuscript
License
File Access Level
Open
ISBN17468108 17468094
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Human Behaviour Model Combining Multiple Sensors
Liao, Z, Buchanan, K, Ghavami, N, Vastardis, N, Adjrad, M, Koch, C, Ghavami, M, Anderson, B, Yang, K, Russo, R and Dudley, S (2015). Human Behaviour Model Combining Multiple Sensors. Conference of the eceee 2015 Summer Study on energy efficiency. Presqu’île de Giens Toulon/Hyères, France 01 - 06 Jun 2015 London South Bank University.
A new approach for event detection using k-means clustering and neural networks.
Oladimeji, MO, Turkey, M, Ghavami, M and Dudley, S (2015). A new approach for event detection using k-means clustering and neural networks. 2015 International Joint Conference on Neural Networks (IJCNN). Killarney Institute of Electrical and Electronics Engineers (IEEE). pp. 1 - 5 https://doi.org/10.1109/IJCNN.2015.7280752
Occupancy based household energy disaggregation using ultra wideband radar and electrical signature profiles
Brown, R., Ghavami, N., Siddiqui, H., Adjrad, M., Ghavami, M. and Dudley-Mcevoy, S. (2017). Occupancy based household energy disaggregation using ultra wideband radar and electrical signature profiles. Energy and Buildings. 141, pp. 134-141. https://doi.org/10.1016/j.enbuild.2017.02.004
Equity Risk Premiums and Risk Free Rates in Modelling and Prediction of Financial Markets
Ghavami, M and Shams Dilmaghani, R (2017). Equity Risk Premiums and Risk Free Rates in Modelling and Prediction of Financial Markets. International Conference on Mathematical Finance, Statistics and Economics. Vienna, Austria 21 - 22 Jun 2017
A Spatially Processed 3D Wideband Adaptive Conical Array System
Ghavami, M (2017). A Spatially Processed 3D Wideband Adaptive Conical Array System. IEEE International Conference on Ubiquitous Wireless Broadband ICUWB’2017. Salamanca, Spain 12 - 15 Sep 2017 Institute of Electrical and Electronics Engineers (IEEE).
UWB Localization Employing Supervised Learning Method
Rana, S., Dey, M., Siddiqui, H., Tiberi, G., Ghavami, M. and Dudley, S (2017). UWB Localization Employing Supervised Learning Method. IEEE International Conference on Ubiquitous Wireless Broadband 2017. Salamanca, Spain 12 - 15 Sep 2017 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICUWB.2017.8250971
UWB power propagation for bio-medical implanted devices
Ghafari, M, Brennan, P and Ghavami, M (2015). UWB power propagation for bio-medical implanted devices. 17th International Conference on E-health Networking, Application & Services (HealthCom). Boston, MA, USA 14 - 17 Oct 2015 London South Bank University. pp. 483 - 487 https://doi.org/10.1109/HealthCom.2015.7454551
Huygens Principle based UWB Microwave Imaging Method for Skin Cancer Detection
Ghavami, N, Tiberi, G, Ghavami, M, Dudley, S and Lane, ME (2016). Huygens Principle based UWB Microwave Imaging Method for Skin Cancer Detection. 10th IEEE/IET International Symposium on Communication Systems, Networks and Digital Signal Processing. Prague, Czech Republic 20 - 22 Jul 2016 Institute of Electrical and Electronics Engineers (IEEE).
Improving time–frequency domain sleep EEG classification via singular spectrum analysis
Mahvash Mohammadi, S., Kouchaki, S., Ghavami, M. and Sanei, S. (2016). Improving time–frequency domain sleep EEG classification via singular spectrum analysis. Journal of Neuroscience Methods. 273, pp. 96-106. https://doi.org/10.1016/j.jneumeth.2016.08.008
A semantic-enhanced trajectory visual analytics for digital forensic
Liao, Z.-F., Li, Y., Peng, Y., Zhao, Y., Zhou, F.-F., Liao, Z.-N., Dudley, S. and Ghavami, M. (2015). A semantic-enhanced trajectory visual analytics for digital forensic. Journal of Visualization. 18 (2), pp. 173 - 184. https://doi.org/10.1007/s12650-015-0276-z
Classification of awake, REM, and NREM from EEG via singular spectrum analysis
Mohammadi, SM, Enshaeifar, S, Ghavami, M and Sanei, S (2015). Classification of awake, REM, and NREM from EEG via singular spectrum analysis. International Conference of the IEEE Engineering in Medicine and Biology Society. Milan, Italy 25 - 29 Aug 2015 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EMBC.2015.7319460
Automatic trust calculation for service-oriented systems
Ye, B., Nekovee, M., Pervez, A. and Ghavami, M. (2014). Automatic trust calculation for service-oriented systems. IET Software. 8 (3), pp. 134 - 142. https://doi.org/10.1049/iet-sen.2013.0056
Ultra-wideband-based multilateration technique for indoor localisation
Onalaja, O., Adjrad, M. and Ghavami, M. (2014). Ultra-wideband-based multilateration technique for indoor localisation. IET COMMUNICATIONS. 8 (10), pp. 1800 - 1809. https://doi.org/10.1049/iet-com.2013.0815
Study of human being detection in an indoor environment using ultra wideband radar
Hassan Khausru, MA and Ghavami, M (2014). Study of human being detection in an indoor environment using ultra wideband radar. IEEE International Conference on Ultra-Wideband 2014. Paris, France Institute of Electrical and Electronics Engineers (IEEE). pp. 113 - 118 https://doi.org/10.1109/ICUWB.2014.6958961
Signal Detection Performance of Overlapped FFT Scheme with Additional Frames Consisting of Non-continuous Samples in Indoor Environment
Uchida, S., Sato, A., Inamori, M., Sanada, Y. and Ghavami, M. (2014). Signal Detection Performance of Overlapped FFT Scheme with Additional Frames Consisting of Non-continuous Samples in Indoor Environment. Wireless Personal Communications. 79 (2), pp. 987 - 1002. https://doi.org/10.1007/s11277-014-1899-4
A user-centric system architecture for residential energy consumption reduction
Vastardis, N, Adjrad, M, Buchanan, K, Liao, Z, Koch, C, Russo, R, Yang, K, Ghavami, M, Anderson, B and Dudley, S (2014). A user-centric system architecture for residential energy consumption reduction. IEEE Online Conference on Green Communications. Online 12 - 14 Nov 2014 Institute of Electrical and Electronics Engineers (IEEE). pp. 1-7 https://doi.org/10.1109/OnlineGreenCom.2014.7114423