TY - JOUR
T1 - Quantitative Photoacoustic Imaging of Chlorophyll Using a GPU-Accelerated Finite Element Method
AU - Qi , Weizhi
AU - Yao , Lei
AU - Jiang , Yunchao
AU - Huang , Na
AU - Guo , Heng
AU - Rong , Jian
AU - Feng , Hui
AU - Yang , Wanneng
AU - Xi , Lei
JO - Communications in Computational Physics
VL - 2
SP - 679
EP - 690
PY - 2020
DA - 2020/06
SN - 28
DO - http://doi.org/10.4208/cicp.OA-2017-0248
UR - https://global-sci.org/intro/article_detail/cicp/16949.html
KW - 
AB - <p style="text-align: justify;">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.</p>