TY - JOUR
T1 - Fitting-free algorithm for efficient quantification of collagen fiber alignment in SHG imaging applications
AU - Hall, Gunnsteinn
AU - Liang, Wenxuan
AU - Li, Xingde
N1 - Funding Information:
This project was supported in part by the National Institutes of Health under a grant R01CA153023 and the National Science Foundation under a grant CBET-1430040.
Publisher Copyright:
© 2017 Optical Society of America.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - Collagen fiber alignment derived from second harmonic generation (SHG) microscopy images can be important for disease diagnostics. Image processing algorithms are needed to robustly quantify the alignment in images with high sensitivity and reliability. Fourier transform (FT) magnitude, 2D power spectrum, and image autocorrelation have previously been used to extract fiber information from images by assuming a certain mathematical model (e.g. Gaussian distribution of the fiber-related parameters) and fitting. The fitting process is slow and fails to converge when the data is not Gaussian. Herein we present an efficient constant-time deterministic algorithm which characterizes the symmetricity of the FT magnitude image in terms of a single parameter, named the fiber alignment anisotropy R ranging from 0 (randomized fibers) to 1 (perfect alignment). This represents an important improvement of the technology and may bring us one step closer to utilizing the technology for various applications in real time. In addition, we present a digital image phantom-based framework for characterizing and validating the algorithm, as well as assessing the robustness of the algorithm against different perturbations.
AB - Collagen fiber alignment derived from second harmonic generation (SHG) microscopy images can be important for disease diagnostics. Image processing algorithms are needed to robustly quantify the alignment in images with high sensitivity and reliability. Fourier transform (FT) magnitude, 2D power spectrum, and image autocorrelation have previously been used to extract fiber information from images by assuming a certain mathematical model (e.g. Gaussian distribution of the fiber-related parameters) and fitting. The fitting process is slow and fails to converge when the data is not Gaussian. Herein we present an efficient constant-time deterministic algorithm which characterizes the symmetricity of the FT magnitude image in terms of a single parameter, named the fiber alignment anisotropy R ranging from 0 (randomized fibers) to 1 (perfect alignment). This represents an important improvement of the technology and may bring us one step closer to utilizing the technology for various applications in real time. In addition, we present a digital image phantom-based framework for characterizing and validating the algorithm, as well as assessing the robustness of the algorithm against different perturbations.
KW - (100.2960) imaging analysis
KW - (180.4315) nonlinear microscopy
KW - (180.6900) three-dimensional microscopy
UR - http://www.scopus.com/inward/record.url?scp=85030999194&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85030999194&partnerID=8YFLogxK
U2 - 10.1364/BOE.8.004609
DO - 10.1364/BOE.8.004609
M3 - Article
C2 - 29082088
AN - SCOPUS:85030999194
SN - 2156-7085
VL - 8
SP - 4609
EP - 4620
JO - Biomedical Optics Express
JF - Biomedical Optics Express
IS - 10
M1 - #305215
ER -