Unveiling precision: a data-driven approach to enhance photoacoustic imaging with sparse data
Author : Mengyuan Huang, Wu Liu, Guocheng Sun, Chaojing Shi, Xi Liu, Kaitai Han, Shitou Liu, Zijun Wang, Zhennian Xie, and Qianjin Guo Journa Name: BIOMEDICAL OPTICS EXPRESS Country : USA Volume: 15 issue: 1 Year: 2024 Views : 419This study presents the Fourier Decay Perception Generative Adversarial Network (FDP-GAN), an innovative approach dedicated to alleviating limitations in photoacoustic imaging stemming from restricted sensor availability and biological tissue heterogeneity. By integrating diverse photoacoustic data, FDP-GAN notably enhances image fidelity and reduces artifacts, particularly in scenarios of low sampling. Its demonstrated effectiveness highlights its potential for substantial contributions to clinical applications, marking a significant stride in addressing pertinent challenges within the realm of photoacoustic acquisition techniques.
Related Indexing Platform
Indexed
bibpurl
Journal Website
GS
Search on Google Scholar
Google Scholar
Search this title on Scholar
SS
Search on Semantic Scholar
Semantic Scholar
Search this title