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Unveiling precision: a data-driven approach to enhance photoacoustic imaging with sparse data.


ABSTRACT: This 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.

SUBMITTER: Huang M 

PROVIDER: S-EPMC10783920 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Unveiling precision: a data-driven approach to enhance photoacoustic imaging with sparse data.

Huang Mengyuan M   Liu Wu W   Sun Guocheng G   Shi Chaojing C   Liu Xi X   Han Kaitai K   Liu Shitou S   Wang Zijun Z   Xie Zhennian Z   Guo Qianjin Q  

Biomedical optics express 20231204 1


This 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 clin  ...[more]

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