A novel algorithm for multiplicative speckle noise reduction in ex vivo human brain OCT images

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 pena...

Full description

Saved in:
Bibliographic Details
Published in:NeuroImage (Orlando, Fla.) Fla.), 2022-08, Vol.257, p.119304-119304, Article 119304
Main Authors: Varadarajan, Divya, Magnain, Caroline, Fogarty, Morgan, Boas, David A., Fischl, Bruce, Wang, Hui
Format: Article
Language:English
Subjects:
Algorithms
Artifact correction
Brain
Brain - diagnostic imaging
Gamma distribution
Human brain
Humans
Majorize minimize
Methods
Multiplicative noise
Noise reduction
Optical coherence tomography
Optical properties
Phantoms, Imaging
Signal-To-Noise Ratio
Speckle
Tissue imaging
Tomography, Optical Coherence - methods
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2022.119304