High Frequency Breast Imaging: Experimental Analysis of Tissue Phantoms

Nguyen, Duy Hai; Stindl, Jonathan; Slanina, Teresa; Moll, Jochen; Krozer, Viktor; Zimmer, Gernot

doi:10.1109/ojap.2021.3127653

Cited by 12 publications

(1 citation statement)

References 28 publications

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“…However, it is expensive and not easily accessible, limiting its widespread application in detection [4]. Electromagnetic microwave imaging (EMI) is an emerging and promising technique with numerous advantages for early breast tumor detection, including safety, low cost, non-ionization, and portability [5]. Several teams have reported the feasibility of their systems developed for microwave breast tumor imaging [6].…”

Section: Introductionmentioning

confidence: 99%

Multiplicative Improved Coherence Factor Delay Multiply and Sum Algorithm for Clutter Removal in a Microwave Breast Tumor Imaging System

Guo,

Wang,

Liu

et al. 2024

Applied Sciences

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In the medical field, microwave imaging technology has experienced rapid development due to its non-invasive and non-radioactive nature. The confocal algorithm is a method commonly used for microwave breast cancer imaging, with the key objective of removing clutter in images to achieve high-quality results. However, the current methods are facing challenges in removing clutter. In order to reduce the clutter in images, a multiplicative improved coherence factor delay multiply and sum algorithm based on the maximum interclass differencing method is proposed. The algorithm compares the starting and ending moments of tumor signals in different channels to determine whether the tumor-scattered signals in different channels overlap in time. An improved coherence coefficient is obtained by summing the non-overlapping signals and multiplying the time window. The multiplicative improved coherence factor, which is obtained by multiplying the coherence coefficients of the improved multi-pair signals, is then multiplied by the focal point intensity obtained using the delay multiply and sum algorithm to reduce clutter in an image. To evaluate the performance of the proposed algorithm, several low-cost uniform and non-uniform models of human breast and tumor tissue with dielectric properties were prepared for testing. The experimental results show that, compared to the existing algorithm, the proposed algorithm can greatly reduce the clutter in images, with a signal-to-clutter ratio of at least 4 dB higher as well as contrast at least six-fold higher.

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Section: Introductionmentioning

confidence: 99%