AI-assisted adaptive spectral unmixing algorithm from micro to macro resolution photoacoustic imaging

Valeria Grasso; Regine Willumeit-Römer; Jithin Jose

doi:10.1117/12.3003182

13 March 2024 AI-assisted adaptive spectral unmixing algorithm from micro to macro resolution photoacoustic imaging

Valeria Grasso, Regine Willumeit-Römer, Jithin Jose

Proceedings Volume PC12842, Photons Plus Ultrasound: Imaging and Sensing 2024; PC128420V (2024) https://doi.org/10.1117/12.3003182
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

The limited frequency bandwidth of the ultrasound transducer used as receivers in photoacoustic imaging (PAI) has a significant impact on the resolution and depth of the reconstructed image. Therefore, for clinical applications, PAI may require the use of a low or high-frequency transducer depending on the application. Here we propose an adaptive spectral PAI algorithm based on prior information of multiple linear array ultrasound transducers ranging from 1-50 MHz, to retrieve tissue molecular components from micro to macro scale. The method includes multiple modules to coherently unmix molecular components at multi-scale. Results on numerical simulations and human imaging demonstrate that the adaptive method can effectively merge multiple-scale molecular imaging and substantially improve PAI quality.

Conference Presentation

Citation Download Citation

Valeria Grasso, Regine Willumeit-Römer, and Jithin Jose "AI-assisted adaptive spectral unmixing algorithm from micro to macro resolution photoacoustic imaging", Proc. SPIE PC12842, Photons Plus Ultrasound: Imaging and Sensing 2024, PC128420V (13 March 2024); https://doi.org/10.1117/12.3003182

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