Merge branch 'main' of https://git-bioimage.coe.drexel.edu/opensource/rsf

manuscript/RSF.tex

@@ -93,6 +93,12 @@ tl;dr RKHS make subsequent optimization learning easier to implement and more li
 [Ronald?] -- ~ 4 paragraphs summarize impact of retinal OCT (Glaucoma, occulomics, etc.),  background on VFMD, background on metadata, imaging physics. 
 Key recent deep learning papers [Schuman et al.]. Other learning approaches [NNMF et al.].
 
+-------
+
+Optical coherence tomography (OCT) is a non-invasive diagnostic imaging tool which employs principles of optical interferometry to obtain cross-sectional images from biological tissue \cite[]{huang1991}.
+
+-------
+
 Key observation -- inherent anisotropy of imaging implements Frangi-like plate filter along the high resolution axis.
 
 \subsection{Kolmogorov complexity and the normalized information distance (NID)}

manuscript/rsf.bib

@@ -250,3 +250,14 @@
    year = {2016},
    type = {Journal Article}
 }
+
+@article{huang1991,
+  title={Optical coherence tomography},
+  author={Huang, David and Swanson, Eric A and Lin, Charles P and Schuman, Joel S and Stinson, William G and Chang, Warren and Hee, Michael R and Flotte, Thomas and Gregory, Kent and Puliafito, Carmen A},
+  journal={Science},
+  volume={254},
+  number={5035},
+  pages={1178--1181},
+  year={1991},
+  doi={10.1126/science.1957169}
+}