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The Application of an Iterative Structure to the Delay-and-Sum and the Delay-Multiply-and-Sum Beamformers in Breast Microwave Imaging

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Specialty Radiology
Date 2020 Jun 21
PMID 32560309
Citations 8
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Abstract

Breast microwave imaging (BMI) is a potential breast cancer screening method. This manuscript presents a novel iterative delay-and-sum (DAS) based reconstruction algorithm for BMI. This iterative-DAS (itDAS) algorithm uses a forward radar model to iteratively update an image estimate. A variation of the itDAS reconstruction algorithm that uses the delay-multiply-and-sum (DMAS) beamformer was also implemented (the itDMAS algorithm). Both algorithms were used to reconstruct images from experimental scans of an array of 3D-printed MRI-based breast phantoms performed with a clinical BMI system. The signal-to-clutter ratio (SCR) and signal-to-mean ratio (SMR) were used to compare the performance of the itDAS and itDMAS methods to the DAS and DMAS beamformers. While no significant difference between the itDAS and itDMAS methods was observed in most images, the itDAS algorithm produced reconstructions that had significantly higher SMR than the non-iterative methods, increasing contrast by as much as 19 dB over DAS and 13 dB over DMAS. The itDAS algorithm also increased the SCR of reconstructions by up to 5 dB over DAS and 4 dB over DMAS, indicating that both high-intensity and background clutter are reduced in images reconstructed by the itDAS algorithm.

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References
1.
Porter E, Bahrami H, Santorelli A, Gosselin B, Rusch L, Popovic M . A Wearable Microwave Antenna Array for Time-Domain Breast Tumor Screening. IEEE Trans Med Imaging. 2016; 35(6):1501-9. DOI: 10.1109/TMI.2016.2518489. View

2.
Gotzsche P, Jorgensen K . Screening for breast cancer with mammography. Cochrane Database Syst Rev. 2013; (6):CD001877. PMC: 6464778. DOI: 10.1002/14651858.CD001877.pub5. View

3.
Hagness S, Taflove A, Bridges J . Two-dimensional FDTD analysis of a pulsed microwave confocal system for breast cancer detection: fixed-focus and antenna-array sensors. IEEE Trans Biomed Eng. 1998; 45(12):1470-9. DOI: 10.1109/10.730440. View

4.
Preece A, Craddock I, Shere M, Jones L, Winton H . MARIA M4: clinical evaluation of a prototype ultrawideband radar scanner for breast cancer detection. J Med Imaging (Bellingham). 2016; 3(3):033502. PMC: 4951628. DOI: 10.1117/1.JMI.3.3.033502. View

5.
Elahi M, OLoughlin D, Lavoie B, Glavin M, Jones E, Fear E . Evaluation of Image Reconstruction Algorithms for Confocal Microwave Imaging: Application to Patient Data. Sensors (Basel). 2018; 18(6). PMC: 6022049. DOI: 10.3390/s18061678. View