Principal component analysis of dynamic fluorescence diffuse optical tomography images.
Challenges remain in resolving drug distributions within small animals utilizing fluorescence diffuse optical tomography (FDOT). In this paper, we present a new method for detecting and visualizing organs with different kinetics utilizing principal component analysis (PCA). Indocynaine green (ICG) metabolic processes are simulated and imaged using FDOT. When applied to the time series of generated FDOT images, PCA provides a set of the principal components (PCs) which can represent spatial patterns associated with different kinetic behavior. Simulation and experiment studies are both performed to validate the performance of the proposed algorithm. The results suggest that we are able to extract and illustrate changes in ICG kinetic behavior between the heart and the lungs.
Liu
Xin
X
Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China.
Wang
Daifa
D
Liu
Fei
F
Bai
Jing
J
D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods*; D025341:Principal Component Analysis; D041622:Tomography, Optical / Q000379:methods*