DN-GAN: Denoising generative adversarial networks for speckle noise reduction in optical coherence tomography images
Optical coherence tomography (OCT) is an efficient noninvasive bioimaging technique that
can measure retinal tissue. Considering the changes in the acquisition environment during …
can measure retinal tissue. Considering the changes in the acquisition environment during …
Synthetic OCT data in challenging conditions: three-dimensional OCT and presence of abnormalities
H Danesh, K Maghooli, A Dehghani… - Medical & Biological …, 2022 - Springer
Nowadays, retinal optical coherence tomography (OCT) plays an important role in
ophthalmology and automatic analysis of the OCT is of real importance: image denoising …
ophthalmology and automatic analysis of the OCT is of real importance: image denoising …
Motion artefact correction in retinal optical coherence tomography using local symmetry
A Montuoro, J Wu, S Waldstein, B Gerendas… - … Image Computing and …, 2014 - Springer
Patient movements during the acquisition of SD-OCT scans create substantial motion
artefacts in the volumetric data that hinder registration and 3D analysis and can be mistaken …
artefacts in the volumetric data that hinder registration and 3D analysis and can be mistaken …
3-D adaptive nonlinear complex-diffusion despeckling filter
P Rodrigues, R Bernardes - IEEE Transactions on Medical …, 2012 - ieeexplore.ieee.org
This work aims to improve the process of speckle noise reduction while preserving edges
and other relevant features through filter expansion from 2-D to 3-D. Despeckling is very …
and other relevant features through filter expansion from 2-D to 3-D. Despeckling is very …
Automatic production of synthetic labelled OCT images using an active shape model
H Danesh, K Maghooli, A Dehghani… - IET Image …, 2020 - Wiley Online Library
Limited labelled data is a challenge in the field of medical imaging and the need for a large
number of them is paramount for the training of machine learning algorithms, as well as …
number of them is paramount for the training of machine learning algorithms, as well as …
Bandlets on oriented graphs: Application to medical image enhancement
In this paper, we introduce a new image modeling method by getting benefit from both
sparsity and multiscale characteristics of transform-domain modeling, along with the …
sparsity and multiscale characteristics of transform-domain modeling, along with the …
Deep learning based retinal OCT image denoising using generative adversarial network
Optical Coherence Tomography (OCT) is the mostly used imaging modality for detecting
retinal diseases. But, the presence of multiplicative granular type speckle noise in the OCT …
retinal diseases. But, the presence of multiplicative granular type speckle noise in the OCT …
Improve synthetic retinal OCT images with present of pathologies and textural information
ES Varnousfaderani, WD Vogl, J Wu… - Medical Imaging …, 2016 - spiedigitallibrary.org
The lack of noise free Optical Coherence Tomography (OCT) images makes it challenging to
quantitatively evaluate performance of image processing methods such as denoising …
quantitatively evaluate performance of image processing methods such as denoising …
[HTML][HTML] Synthetic OCT Data Generation to Enhance the Performance of Diagnostic Models for Neurodegenerative Diseases
Purpose: Optical coherence tomography (OCT) has recently emerged as a source for
powerful biomarkers in neurodegenerative diseases such as multiple sclerosis (MS) and …
powerful biomarkers in neurodegenerative diseases such as multiple sclerosis (MS) and …
Intensity inhomogeneity correction of SD-OCT data using macular flatspace
Images of the retina acquired using optical coherence tomography (OCT) often suffer from
intensity inhomogeneity problems that degrade both the quality of the images and the …
intensity inhomogeneity problems that degrade both the quality of the images and the …