Search for: All records

Abstract 3D‐bioprinted skin‐mimicking phantoms with skin colors ranging across the Fitzpatrick scale are reported. These tools can help understand the impact of skin phototypes on biomedical optics. Synthetic melanin nanoparticles of different sizes (70–500 nm) and clusters are fabricated to mimic the optical behavior of melanosome. The absorption coefficient and reduced scattering coefficient of the phantoms are comparable to real human skin. Further the melanin content and distribution in the phantoms versus real human skins are validated via photoacoustic (PA) imaging. The PA signal of the phantom can be improved by: 1) increasing melanin size (3–450‐fold), 2) increasing clustering (2–10.5‐fold), and 3) increasing concentration (1.3–8‐fold). Then, multiple biomedical optics tools (e.g., PA, fluorescence imaging, and photothermal therapy) are used to understand the impact of skin tone on these modalities. These well‐defined 3D‐bioprinted phantoms may have value in translating biomedical optics and reducing racial bias. 

Low fluence illumination sources can facilitate clinical transition of photoacoustic imaging because they are rugged, portable, affordable, and safe. However, these sources also decrease image quality due to their low fluence. Here, we propose a denoising method using a multi-level wavelet-convolutional neural network to map low fluence illumination source images to its corresponding high fluence excitation map. Quantitative and qualitative results show a significant potential to remove the background noise and preserve the structures of target. Substantial improvements up to 2.20, 2.25, and 4.3-fold for PSNR, SSIM, and CNR metrics were observed, respectively. We also observed enhanced contrast (up to 1.76-fold) in an in vivo application using our proposed methods. We suggest that this tool can improve the value of such sources in photoacoustic imaging.