Quantitative Photoacoustic Imaging of Chlorophyll Using a GPU-Accelerated Finite Element Method

Abstract

Chlorophyll in leaves is tightly associated with physiological status of plants. Chemical extraction or hyperspectral estimation is the conventional method to estimate the concentration of Chlorophyll in leaves. However, chemical extraction is invasive and time consuming, and hyperspectral method is extremely sensitive to background light. In this paper, we develop a quantitative photoacoustic imaging technique based on a finite-element-based reconstruction algorithm accelerated by a multicore GPU card to image morphological features and derive distribution of Chlorophyll A in rice leaves. The results suggest that this new method holds great potential in various studies of plant physiology.