Toward ground-truth optical coherence tomography via three-dimensional unsupervised deep learning processing and data
Optical coherence tomography (OCT) can perform non-invasive high-resolution three-
dimensional (3D) imaging and has been widely used in biomedical fields, while it is …
dimensional (3D) imaging and has been widely used in biomedical fields, while it is …
Self-supervised blind2unblind deep learning scheme for oct speckle reductions
As a low-coherence interferometry-based imaging modality, optical coherence tomography
(OCT) inevitably suffers from the influence of speckles originating from multiply scattered …
(OCT) inevitably suffers from the influence of speckles originating from multiply scattered …
State-of-the-Art of Deep Learning in Multidisciplinary Optical Coherence Tomography Applications
Optical Coherence Tomography (OCT) emerged as a technology for the detection of retinal
disease. Owing to its excellent performance and ability to provide in-vivo high-resolution …
disease. Owing to its excellent performance and ability to provide in-vivo high-resolution …
Self-supervised Self2Self denoising strategy for OCT speckle reduction with a single noisy image
C Ge, X Yu, M Yuan, Z Fan, J Chen… - Biomedical Optics …, 2024 - opg.optica.org
Optical coherence tomography (OCT) inevitably suffers from the influence of speckles
originating from multiple scattered photons owing to its low-coherence interferometry …
originating from multiple scattered photons owing to its low-coherence interferometry …
[PDF][PDF] GPU-accelerated OCT imaging: Real-time data processing and artifact suppression for enhanced monitoring of 3D bioprinted tissues and vascular-like …
S Yang, J Zhou, H Guo, L Wang, M Xu - Journal of Innovative …, 2024 - researching.cn
Optical coherence tomography (OCT) is a noninvasive, high-resolution, high-sensitivity and
threedimensional (3D) imaging modality, which is widely used for clinical diagnosis and …
threedimensional (3D) imaging modality, which is widely used for clinical diagnosis and …
Unsupervised OCT image despeckling with ground-truth-and repeated-scanning-free features
R Wu, S Huang, J Zhong, F Zheng, M Li, X Ge… - Optics …, 2024 - opg.optica.org
Optical coherence tomography (OCT) can resolve biological three-dimensional tissue
structures, but it is inevitably plagued by speckle noise that degrades image quality and …
structures, but it is inevitably plagued by speckle noise that degrades image quality and …
Dual blind-spot network for self-supervised denoising in OCT images
The blind-spot network and its variants have shown promising results in the field of self-
supervised denoising tasks. These methods aim at concealing noisy image pixels and …
supervised denoising tasks. These methods aim at concealing noisy image pixels and …
NL-CoWNet: A Deep Convolutional Encoder-Decoder Architecture for OCT Speckle Elimination using Non-Local and Subband Modulated DT-CWT blocks
OCT (Optical Coherence Tomography), a noninvasive diagnostic technology for identifying
and treating various ocular diseases, encounters a loss of image quality due to the …
and treating various ocular diseases, encounters a loss of image quality due to the …
A Machine-Agnostic Approach to Denoising OCT Images of the Retina
Optical Coherence Tomography (OCT) is a widely used imaging modality in ophthalmology
for management of various ocular diseases. However, the presence of speckle noise …
for management of various ocular diseases. However, the presence of speckle noise …
[PDF][PDF] Is denoising necessary for ultrasound image segmentation deep learning: review and benchmark
F Liu, L Chen, P Qin, S Xu, Z Dong, X Zhao, X Wan… - Authorea …, 2023 - techrxiv.org
Ultrasound image segmentation deep learning still has performance bottleneck due to an
inherent speckle noise having complex non-Gaussian statistics in the images. Denoised …
inherent speckle noise having complex non-Gaussian statistics in the images. Denoised …