full
search.png

Search

close.png

Cancel

arrow
Volume 28, Issue 2
Quantitative Photoacoustic Imaging of Chlorophyll Using a GPU-Accelerated Finite Element Method

Weizhi Qi, Lei Yao, Yunchao Jiang, Na Huang, Heng Guo, Jian Rong, Hui Feng, Wanneng Yang & Lei Xi

DOI: 10.4208/cicp.OA-2017-0248

Commun. Comput. Phys., 28 (2020), pp. 679-690.

Published online: 2020-06

Preview Purchase PDF 2477 40025

Cited by

google scholar semantic scholar
Export citation
  • 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.

  • Keywords

  • AMS Subject Headings

65N30, 65Y05

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{CiCP-28-679, author = {Qi , WeizhiYao , LeiJiang , YunchaoHuang , NaGuo , HengRong , JianFeng , HuiYang , Wanneng and Xi , Lei}, title = {Quantitative Photoacoustic Imaging of Chlorophyll Using a GPU-Accelerated Finite Element Method}, journal = {Communications in Computational Physics}, year = {2020}, volume = {28}, number = {2}, pages = {679--690}, 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.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2017-0248}, url = {http://global-sci.org/intro/article_detail/cicp/16949.html} }
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 -

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.

Qi , WeizhiYao , LeiJiang , YunchaoHuang , NaGuo , HengRong , JianFeng , HuiYang , Wanneng and Xi , Lei. (2020). Quantitative Photoacoustic Imaging of Chlorophyll Using a GPU-Accelerated Finite Element Method. Communications in Computational Physics. 28 (2). 679-690. doi:10.4208/cicp.OA-2017-0248
Copy to clipboard
BibteX RIS TXT
The citation has been copied to your clipboard