Ultrasound-enhanced Unet model for quantitative photoacoustic tomography of ovarian lesions.

ABSTRACT: Quantitative photoacoustic tomography (QPAT) is a valuable tool in characterizing ovarian lesions for accurate diagnosis. However, accurately reconstructing a lesion's optical absorption distributions from photoacoustic signals measured with multiple wavelengths is challenging because it involves an ill-posed inverse problem with three unknowns: the Grüneisen parameter (Γ) , the absorption distribution, and the optical fluence (ϕ) . Here, we propose a novel ultrasound-enhanced Unet model (US-Unet) that reconstructs optical absorption distribution from PAT data. A pre-trained ResNet-18 extracts the US features typically identified as morphologies of suspicious ovarian lesions, and a Unet is implemented to reconstruct optical absorption coefficient maps, using the initial pressure and US fea

SUBMITTER: Zou Y 

PROVIDER: S-EPMC9619170 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature