Second-harmonic generation (SHG) is uniquely capable of imaging collagen non-invasively with high-resolution, making it ideal to evaluate tissue organization in health and disease. For this, quantitative data analysis is essential. Different approaches have been proposed to quantify tissue organization from SHG images. Nevertheless, these methods have never been objectively evaluated or compared. In this study, we performed a comprehensive analysis on the performance of different metrics in computer-generated SHG images with increasing levels of disorganization to evaluate the advantages and limitations of each approach.
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