ArticleJournal of biomedical optics2024
Convolutional neural network-based regression analysis to predict subnuclear chromatin organization from two-dimensional optical scattering signals.
Article in Journal of biomedical optics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Significance: Azimuth-resolved optical scattering signals obtained from cell nuclei are sensitive to changes in their internal refractive index profile. These two-dimensional signals can therefore offer significant insights into chromatin organization. Aim: We aim to determine whether two-dimensional scattering signals can be used in an inverse scheme to extract the spatial correlation length Approach: Since an analytical formulation that links azimuth-resolved signals to Results: The results show agreement between the true and predicted values for both Conclusions: Our results reveal that CNN-based regression can be a powerful approach for exploiting the information content of two-dimensional optical scattering signals and hence monitoring chromatin organization in a quantitative manner.
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