Abstract
Optical coherence tomography (OCT) images are corrupted by multiplicative generalized gamma distributed speckle noise that significantly degrades the contrast to noise ratio (CNR) of microstructural compartments in biological applications. This work proposes a novel algorithm to optimize the negative log likelihood of the spatial distribution of speckle. Specifically, the proposed method formulates a penalized negative log likelihood (P-NLL) cost function and proposes a majorize-minimize-based optimization method that removes speckle from OCT images. The optimization reduces to solving an iterative gradient descent problem. We demonstrate the usefulness of the proposed method by removing speckle in OCT images of uniform phantoms with varying scattering coefficients and human brain tissue.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵# In addition, B. Fischl has a financial interest in CorticoMetrics, a company whose medical pursuits focus on brain imaging and measurement technologies. B. Fischl’s interests were reviewed and are managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflict of interest policies.
Support for this research was provided in part by the BRAIN Initiative Cell Census Network grant U01MH117023, the National Institute for Biomedical Imaging and Bioengineering (P41EB015896, 1R01EB023281, R01EB006758, R21EB018907, R01EB019956, R00EB023993, U01EB026996), the National Institute on Aging (1R56AG064027, 1R01AG064027, 5R01AG008122, R01AG016495), the National Institute of Mental Health, the National Institute of Diabetes and Digestive and Kidney Diseases (1-R21-DK-108277-01), the National Institute for Neurological Disorders and Stroke (R01NS0525851, R21NS072652, R01NS070963, R01NS083534, 5U01NS086625, 5U24NS10059103, R01NS105820), and was made possible by the resources provided by Shared Instrumentation Grants 1S10RR023401, 1S10RR019307, and 1S10RR023043. Additional support was provided by the NIH Blueprint for Neuroscience Research (5U01-MH093765), part of the multi-institutional Human Connectome Project.