A Robust and Artifact Resistant Algorithm of Ultrawideband Imaging System for Breast Cancer Detection
- 15 January 2015
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Biomedical Engineering
- Vol. 62 (6), 1514-1525
- https://doi.org/10.1109/tbme.2015.2393256
Abstract
Objective: Ultrawideband radar imaging is regarded as one of the most promising alternatives for breast cancer detection. A range of algorithms reported in literature shows satisfactory tumor detection capabilities. However, most of algorithms suffer significant deterioration or even fail when the early-stage artifact, including incident signals and skin-fat interface reflections, cannot be perfectly removed from received signals. Furthermore, fibro-glandular tissue poses another challenge for tumor detection, due to the small dielectric contrast between glandular and cancerous tissues. Methods: This paper introduces a novel Robust and Artifact Resistant (RAR) algorithm, in which a neighborhood pairwise correlation-based weighting is designed to overcome the adverse effects from both artifact and glandular tissues. In RAR, backscattered signals are time-shifted, summed, and weighted by the maximum combination of the neighboring pairwise correlation coefficients between shifted signals, forming the intensity of each point within an imaging area. Results: The effectiveness was investigated using 3-D anatomically and dielectrically accurate finite-difference-time-domain numerical breast models. The use of neighborhood pairwise correlation provided robustness against artifact and enabled the detection of multiple scatterers. RAR is compared with four well-known algorithms: delay-and-sum, delay-multiply-and-sum, modified-weighted-delay-and-sum, and filtered-delay-and-sum. Conclusion: It has shown that RAR exhibits improved identification capability, robust artifact resistance, and high detectability over its counterparts in most scenarios considered, while maintaining computational efficiency. Simulated tumors in both homogeneous and heterogonous, from mildly to moderately dense breast phantoms, combining an entropy-based artifact removal algorithm, were successfully identified and localized. Significance: These results show the strong potential of RAR for breast cancer screening.Keywords
Funding Information
- China Scholarship Council
- University of Sussex Joint Scholarships
This publication has 43 references indexed in Scilit:
- Feasibility Study of Lesion Classification via Contrast-Agent-Aided UWB Breast ImagingIEEE Transactions on Biomedical Engineering, 2010
- ULTRA WIDEBAND SURFACE WAVE COMMUNICATIONProgress in Electromagnetics Research C, 2009
- Development of Anatomically Realistic Numerical Breast Phantoms With Accurate Dielectric Properties for Modeling Microwave Interactions With the Human BreastIEEE Transactions on Biomedical Engineering, 2008
- A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeriesPhysics in Medicine & Biology, 2007
- Microwave imaging via space-time beamforming for early detection of breast cancerIEEE Transactions on Antennas and Propagation, 2003
- Breast compression in mammography: How much is enough?Australasian Radiology, 2003
- Convolution PML (CPML): An efficient FDTD implementation of the CFS–PML for arbitrary mediaMicrowave and Optical Technology Letters, 2000
- Ten-Year Risk of False Positive Screening Mammograms and Clinical Breast ExaminationsNew England Journal of Medicine, 1998
- Simple treatment of multi-term dispersion in FDTDIEEE Microwave and Guided Wave Letters, 1997
- FDTD calculations of the whole-body averaged SAR in an anatomically realistic voxel model of the human body from 1 MHz to 1 GHzPhysics in Medicine & Biology, 1997