Drusen, the hallmark lesions of age related macular degeneration (AMD), are biochemically heterogeneous and the identification of their biochemical distribution is key to understanding AMD. Yet the challenges are to develop imaging technology and analysis tools which respect the physical generation of the hyperspectral signal in the presence of noise and multiple mixed sources while maximally exploiting the full data dimensionality to uncover clinically relevant spectral signatures.
7 patient eyes with drusen were imaged with the snapshot hyperspectral camera previously described (doi:10.1117/1.2434950). Regions of interest (ROI’s) of drusen were identified in each image. Multiple images were acquired of one eye. We performed statistical intra-subject analysis to investigate the reproducibility of non-negative matrix factorization (NMF) in AMD patients with different types of drusen. Given a data matrix D and a positive integer r the NMF problem is to compute a decomposition with r being the low-rank factor, W the basis vectors, and H the linear encoding representing the mixing coefficients.
Figure 1 shows central slices of 5 different ROIs for patient P=c. In each ROI a drusen sensitivity spectrum was recovered with a response peak between 550 and 600nm. This spectrum had low variability across different ROIs within a patient (mean-standard error (σ) = 0.01) and between patients (σ=0.041).
Snapshot hyperspectral images analyzed with NMF, which imposes physically realistic positivity constraints on the mixing process, recovered spectral profiles that reliably identified drusen. The recovered spectra were consistently similar for drusen in different areas of the macula from the same eye and also in different eyes. Our results suggest that hyperspectral imaging can detect biochemically meaningful components of drusen.