Confocal microwave imaging for breast cancer detection: delay-multiply-and-sum image reconstruction algorithm

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Computational Electromagnetics

Background:

• Early breast cancer detection is crucial for effective treatment.
• Microwave imaging offers a non-ionizing alternative for breast cancer diagnosis.
• Existing image reconstruction algorithms have limitations in detecting small tumors.

Purpose of the Study:

• To introduce and evaluate a new image reconstruction algorithm, Delay-Multiply-and-Sum (DMAS), for breast cancer detection.
• To improve the accuracy and resolution of microwave imaging for identifying malignant tumors.
• To demonstrate the capability of DMAS in detecting small tumors.

Main Methods:

• Developed the Delay-Multiply-and-Sum (DMAS) algorithm for microwave imaging.
• Simulated breast phantoms using the finite-difference time-domain (FDTD) method.
• Applied DMAS to backscattered signals from numerical breast phantoms to reconstruct images.
• Compared DMAS performance against the conventional Delay-and-Sum (DAS) algorithm.

Main Results:

• The DMAS algorithm demonstrated improved image reconstruction for breast cancer detection.
• Reconstructed images showed enhanced identification of embedded malignant tumors.
• DMAS successfully detected and localized tumors as small as 2 mm in diameter.
• The algorithm showed superior performance over the Delay-and-Sum algorithm.

Conclusions:

• The proposed DMAS algorithm is effective for breast cancer detection using ultra-wideband confocal microwave imaging.
• DMAS offers improved tumor identification and localization capabilities, particularly for small malignancies.
• This technique shows promise for advancing non-invasive breast cancer diagnostic tools.