Research Papers: Imaging

Fully automated muscle quality assessment by Gabor filtering of second harmonic generation images

[+] Author Affiliations
Rik Paesen, Sophie Smolders, José Manolo de Hoyos Vega, Marcel Ameloot

Hasselt University, Biomedical Research Institute, Agoralaan Building C, 3590 Diepenbeek, Belgium

Bert O. Eijnde, Dominique Hansen

Hasselt University, Biomedical Research Institute, Agoralaan Building C, 3590 Diepenbeek, Belgium

Hasselt University, REVAL–Rehabilitation Research Center, Agoralaan Building A, 3590 Diepenbeek, Belgium

J. Biomed. Opt. 21(2), 026003 (Feb 05, 2016). doi:10.1117/1.JBO.21.2.026003
History: Received October 4, 2015; Accepted January 15, 2016
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Abstract.  Although structural changes on the sarcomere level of skeletal muscle are known to occur due to various pathologies, rigorous studies of the reduced sarcomere quality remain scarce. This can possibly be explained by the lack of an objective tool for analyzing and comparing sarcomere images across biological conditions. Recent developments in second harmonic generation (SHG) microscopy and increasing insight into the interpretation of sarcomere SHG intensity profiles have made SHG microscopy a valuable tool to study microstructural properties of sarcomeres. Typically, sarcomere integrity is analyzed by fitting a set of manually selected, one-dimensional SHG intensity profiles with a supramolecular SHG model. To circumvent this tedious manual selection step, we developed a fully automated image analysis procedure to map the sarcomere disorder for the entire image at once. The algorithm relies on a single-frequency wavelet-based Gabor approach and includes a newly developed normalization procedure allowing for unambiguous data interpretation. The method was validated by showing the correlation between the sarcomere disorder, quantified by the M-band size obtained from manually selected profiles, and the normalized Gabor value ranging from 0 to 1 for decreasing disorder. Finally, to elucidate the applicability of our newly developed protocol, Gabor analysis was used to study the effect of experimental autoimmune encephalomyelitis on the sarcomere regularity. We believe that the technique developed in this work holds great promise for high-throughput, unbiased, and automated image analysis to study sarcomere integrity by SHG microscopy.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Rik Paesen ; Sophie Smolders ; José Manolo de Hoyos Vega ; Bert O. Eijnde ; Dominique Hansen, et al.
"Fully automated muscle quality assessment by Gabor filtering of second harmonic generation images", J. Biomed. Opt. 21(2), 026003 (Feb 05, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.2.026003


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