Title
A novel algorithm for multiplicative speckle noise reduction in ex vivo human brain OCT images
Abstract
Optical coherence tomography (OCT) images of ex vivo human brain tissue are corrupted by multiplicative speckle noise that degrades the contrast to noise ratio (CNR) of microstructural compartments. This work proposes a novel algorithm to reduce noise corruption in OCT images that minimizes the penalized negative log likelihood of gamma distributed speckle noise. The proposed method is formulated as a majorize-minimize problem that reduces to solving an iterative regularized least squares optimization. We demonstrate the usefulness of the proposed method by removing speckle in simulated data, phantom data and real OCT images of human brain tissue. We compare the proposed method with state of the art filtering and non-local means based denoising methods. We demonstrate that our approach removes speckle accurately, improves CNR between different tissue types and better preserves small features and edges in human brain tissue.
Year
DOI
Venue
2022
10.1016/j.neuroimage.2022.119304
NeuroImage
Keywords
DocType
Volume
Speckle,Optical coherence tomography,Multiplicative noise,Artifact correction,Majorize minimize,Gamma distribution,Human brain,Tissue imaging
Journal
257
ISSN
Citations 
PageRank 
1053-8119
0
0.34
References 
Authors
4
6
Name
Order
Citations
PageRank
Divya Varadarajan100.34
Caroline Magnain200.34
Morgan Fogarty300.34
David A. Boas466372.57
Fischl Bruce54131219.39
Hui Wang629185.17