Breast cancer is a major health concern worldwide, and early detection is crucial for effective treatment. Traditional imaging methods, such as mammography, have limitations, especially for women with dense breast tissue. Photoacoustic imaging, which combines light and sound to create detailed images of breast tissue, offers a promising alternative. However, recent research has highlighted a significant challenge: skin tone bias.
A team of researchers from Johns Hopkins University recently investigated how skin tone affects the visibility of breast cancer targets in photoacoustic imaging.
As reported in Biophotonics Discovery, the study focused on three image reconstruction methods: fast Fourier transform (FFT)-based reconstruction, delay-and-sum (DAS) beamforming, and short-lag spatial coherence (SLSC) beamforming. The study used simulations with different wavelengths (757800, and 1,064 nm), target sizes (0.5 to 3 mm), and skin tones (ranging from very light to dark).
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