Phantom experiments using soft-prior regularization EIT for breast cancer imaging
Abstract
A soft-prior regularization (SR) electrical impedance tomography (EIT) technique for breast cancer imaging is described, which shows an ability to accurately reconstruct tumor/inclusion conductivity values within a dense breast model investigated using a cylindrical and a breast-shaped tank. The SR-EIT method relies on knowing the spatial location of a suspicious lesion initially detected from a second imaging modality. Standard approaches (using Laplace smoothing and total variation regularization) without prior structural information are unable to accurately reconstruct or detect the tumors. The soft-prior approach represents a very significant improvement to these standard approaches, and has the potential to improve conventional imaging techniques, such as automated whole breast ultrasound (AWB-US), by providing electrical property information of suspicious lesions to improve AWB-US's ability to discriminate benign from cancerous lesions. Specifically, the best soft-regularization technique found average absolute tumor/inclusion errors of 0.015 S m(-1) for the cylindrical test and 0.055 S m(-1) and 0.080 S m(-1) for the breast-shaped tank for 1.8 cm and 2.5 cm inclusions, respectively. The standard approaches were statistic...Continue Reading
References
The negative predictive value of electrical impedance scanning in BI-RADS category IV breast lesions
Optical breast shape capture and finite-element mesh generation for electrical impedance tomography.
FPGA-based voltage and current dual drive system for high frame rate electrical impedance tomography
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