Adaptive artifact removal for selective multistatic microwave breast imaging signals. (April 2017)

• Record Type: Journal Article
• Authors: Elahi, M.A.; Glavin, M.; Jones, E.; O'Halloran, M.
• Is Part Of: Biomedical signal processing and control. Volume 34(2017)
• Page Start: 93
• Page End: 100
• Publication Date: 2017-04
• Subjects: Microwave imaging -- Ultra wideband radar -- Breast cancer -- Multistatic artifact removal -- Skin subtraction -- Skin-artifact removal; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.01.006
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract : Graphical abstract: Abstract : Highlights: A novel multistatic artifact removal algorithm for confocal microwave imaging of the breast is proposed. The proposed algorithm allows the inclusion of multistatic signals in the imaging in addition to the monostatic signals. The combined monostatic and multistatic imaging approach improves the imaging quality compared to monostatic-only imaging approach. Abstract: Microwave imaging is one of the most promising alternative breast imaging modalities. Early-stage artifact removal is an important signal processing component of a microwave breast imaging system. In this paper, a monostatic artifact removal algorithm is extended to remove the early-stage artifact from multistatic radar signals. The multistatic radar signals exhibit greater variation in the early-stage artifact due to varying propagation paths between transmitting and receiving antennas. This variation makes it more challenging to estimate and remove the artifact compared to the monostatic signals. This paper proposes an entropy-based adaptive method to group signals with similar artifacts and then remove the artifact from each group separately using a hybrid artifact removal algorithm. The efficacy of the proposed algorithm has been demonstrated by imaging anatomically and dielectrically realistic 3D numerical breast phantoms.