All Articles from Xinjian Chen -Optical Coherence Tomography News

Articles from Xinjian Chen

1-24 of 34 1 2 »
1. Axial and horizontal registration guided speckle suppression in single-line HD mode for retinal optical coherence tomography images
  
  Explore ScienceDirect Jan 29 2021 Ophthalmology
  
  We propose an image registration method to suppress the speckle noise in retinal optical coherence tomography(OCT) adapted to single-line HD mode hardware implementation. In single-line HD mode, multiple cross-section images at the same straight scan line are obtained repeatedly and rapidly for averaging the speckle noise. Not like static objects, cross-section retinal images are often blurred by direct averaging due to unintentional eye/head motions in axial and horizontal directions. An image registration method which combines regularized dynamic programming algorithm with hill-climbing algorithm is demonstrated to correct axial and lateral motion shifts efficiently. The unaligned images are discarded automatically ...
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  Mentions: Soochow University
2. Semi-Supervised Capsule cGAN for Speckle Noise Reduction in Retinal OCT Images
  
  Explore IEEE Xplore Jan 7 2021 Ophthalmology
  
  Speckle noise is the main cause of poor optical coherence tomography (OCT) image quality. Convolutional neural networks (CNNs) have shown remarkable performances for speckle noise reduction. However, speckle noise denoising still meets great challenges because the deep learning-based methods need a large amount of labeled data whose acquisition is time-consuming or expensive. Besides, many CNNs-based methods design complex structure based networks with lots of parameters to improve the denoising performance, which consume hardware resources severely and are prone to overfitting. To solve these problems, we propose a novel semi-supervised learning based method for speckle noise denoising in retinal OCT images ...
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  Mentions: Soochow University
3. Quantitative Analysis of Macular Retina Using Light Reflection Indices Derived from SD-OCT for Pituitary Adenoma
  
  Explore Hindawi Publishing Corporation Nov 20 2020 Ophthalmology
  
  Purpose: To quantitatively investigate the macular retinal light reflection characteristic using optical property indices derived from spectral-domain optical coherence tomography (SD-OCT) scans with depth attenuation compensation for pituitary adenoma. Methods: This study included 38 patients (mean age 44.66 ± 13.77 years old) with diagnosis of pituitary adenoma and 43 age-matched controls. All SD-OCT scans were light attenuation compensated by a depth-resolved model. Attenuation coefficient, the corrected intensity, and the retinal layer thickness were deduced for macular retinal nerve fiber layer (RNFL) and ganglion cell layer combined with inner plexiform layer (GCIPL), as well as comparing between patients and controls ...
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  Mentions: Soochow University
4. Low Tensor Train- and Low Multilinear Rank Approximationsfor De-speckling and Compression of 3D Optical Coherence Tomography Images
  
  Explore arxiv.org Sep 2 2020
  
  This paper proposes low tensor-train (TT) rank and low multilinear (ML) rank approximations for de-speckling and compression of 3D optical coherence tomography (OCT) images for a given compression ratio (CR). To this end, we derive the alternating direction method of multipliers based algorithms for the related problems constrained with the low TT- and low ML rank. Rank constraints are implemented through the Schatten-p (Sp) norm, p e {0, 1/2, 2/3, 1}, of unfolded matrices. We provide the proofs of global convergence towards a stationary point for both algorithms. Rank adjusted 3D OCT image tensors are finally approximated through ...
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
5. Segmentation Guided Registration for 3D Spectral-Domain Optical Coherence Tomography Images
  
  Explore IEEE Xplore Nov 5 2019 Ophthalmology
  
  Medical image registration can be used for combining information from multiple imaging modalities, monitoring changes in size, shape or image intensity over time intervals. However, the development of such technique can be challenging for 3D spectral-domain optical coherence tomography (SD-OCT) imaging, because SD-OCT image is inherently noisy and its high resolution leads to high complexity of non-rigid registration. In this paper, a new segmentation guided approach is reported for registration of retinal OCT data. The proposed method models the 3D registration as a two-stage registration including x-y direction registration and z direction registration. In x-y direction registration, the vessel maps ...
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  Mentions: Soochow University
6. DeSpecNet: a CNN-based method for speckle reduction in retinal optical coherence tomography images
  
  Explore IOPscience Jul 30 2019
  
  Speckle is a major quality degrading factor in optical coherence tomography (OCT) images. In this work we propose a new deep learning network for speckle reduction in retinal OCT images, termed DeSpecNet. Unlike traditional algorithms, the model can learn from training data instead of manually selecting parameters such as noise level. The proposed deep convolutional neural network (CNN) applies strategies including residual learning, shortcut connection, batch normalization and leaky rectified linear units to achieve good despeckling performance. Application of the proposed method to the OCT images shows great improvement in both visual quality and quantitative indices. The proposed method provides ...
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  Mentions: Soochow University
7. Retinal Optical Coherence Tomography Image Analysis (Textbook)
  
  Explore Home - Springer Jul 11 2019 Ophthalmology , Textbooks
  
  This book introduces the latest optical coherence tomography (OCT) imaging and computerized automatic image analysis techniques, and their applications in the diagnosis and treatment of retinal diseases. Discussing the basic principles and the clinical applications of OCT imaging, OCT image preprocessing, as well as the automatic detection and quantitative analysis of retinal anatomy and pathology, it includes a wealth of clinical OCT images, and state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging.
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
8. Effect Of Optic Disk—Fovea Distance On Measurements Of Individual Macular Intraretinal Layers In Normal Subjects
  
  Explore LWW Online Apr 24 2019 Ophthalmology
  
  Purpose: To investigate the effect of optic disk—fovea distance (DFD) on measurements of macular intraretinal layers using spectral domain optical coherence tomography in normal subjects. Methods: One hundred and eighty-two eyes from 182 normal subjects were imaged using spectral domain optical coherence tomography. The average thicknesses of eight macular intraretinal layers were measured using an automatic segmentation algorithm. Partial correlation test and multiple regression analysis were used to determine the effect of DFD on thicknesses of intraretinal layers. Results: Disk—fovea distance correlated negatively with the overall average thickness in all the intraretinal layers (r ≤ −0.17, all P ...
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
9. Nondestructive Measurement of Conformal Coating Thickness on Printed Circuit Board with Ultra-high Resolution Optical Coherence Tomography
  
  Explore IEEE Xplore Feb 5 2019 NDE/NDT
  
  Conformal coating (CC) is widely used to protect printed circuit board (PCB) from corrosion, mould growth and electrical failures. To ensure an effective protection, the thickness of the conformal coating layer needs to be well controlled. However, to date, the coating thickness is usually measured in a destructive way under microscopes. In this study, we proposed to use optical coherence tomography (OCT) to measure the CC thickness nondestructively. Specifically, to obtain a good accuracy in thickness measurement, we constructed a spectral domain OCT (SD-OCT) with ultra-high axial resolution to image the CC layer in three dimensions, and developed an image ...
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  Mentions: Nanyang Technological University University of Iowa Linbo Liu
10. Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN
  
  Explore OSA | OSA Publishing Oct 6 2018
  
  Speckle noise in optical coherence tomography (OCT) impairs both the visual quality and the performance of automatic analysis. Edge preservation is an important issue for speckle reduction. In this paper, we propose an end-to-end framework for simultaneous speckle reduction and contrast enhancement for retinal OCT images based on the conditional generative adversarial network (cGAN). The edge loss function is added to the final objective so that the model is sensitive to the edge-related details. We also propose a novel method for obtaining clean images for training from outputs of commercial OCT scanners. The results show that the overall denoising performance ...
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11. Shared-hole graph search with adaptive constraints for 3D optic nerve head optical coherence tomography image segmentation
  
  Explore OSA | OSA Publishing Feb 6 2018 Ophthalmology
  
  Optic nerve head (ONH) is a crucial region for glaucoma detection and tracking based on spectral domain optical coherence tomography (SD-OCT) images. In this region, the existence of a “hole” structure makes retinal layer segmentation and analysis very challenging. To improve retinal layer segmentation, we propose a 3D method for ONH centered SD-OCT image segmentation, which is based on a modified graph search algorithm with a shared-hole and locally adaptive constraints. With the proposed method, both the optic disc boundary and nine retinal surfaces can be accurately segmented in SD-OCT images. An overall mean unsigned border positioning error of 7 ...
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
12. Automated segmentation of choroidal neovascularization in optical coherence tomography images using multi-scale convolutional neural networks with structure prior
  
  Explore Home - Springer Feb 1 2018 Ophthalmology
  
  Automated segmentation of choroidal neovascularization (CNV) in optical coherence tomography (OCT) images plays an important role for the treatment of CNV disease. This paper proposes multi-scale convolutional neural networks with structure prior to segment CNV from OCT data. The proposed framework consists of two stages. In the first stage, the structure prior learning method based on sparse representation-based classification and the local potential function is developed to capture the global spatial structure and local similarity structure prior. The obtained prior can be used to improve the distinctiveness between CNV and background patches. In the second stage, multi-scale CNN model with ...
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  Mentions: Xiaoming Xiang Soochow University Haoyu Chen
13. Automated framework for intraretinal cystoid macular edema segmentation in three-dimensional optical coherence tomography images with macular hole
  
  Explore SPIE | Journal Jul 22 2017 Ophthalmology
  
  Cystoid macular edema (CME) and macular hole (MH) are the leading causes for visual loss in retinal diseases. The volume of the CMEs can be an accurate predictor for visual prognosis. This paper presents an automatic method to segment the CMEs from the abnormal retina with coexistence of MH in three-dimensional-optical coherence tomography images. The proposed framework consists of preprocessing and CMEs segmentation. The preprocessing part includes denoising, intraretinal layers segmentation and flattening, and MH and vessel silhouettes exclusion. In the CMEs segmentation, a three-step strategy is applied. First, an AdaBoost classifier trained with 57 features is employed to generate ...
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
14. Quantitative analysis of retinal layers on three-dimensional spectral-domain optical coherence tomography for pituitary adenoma
  
  Explore Journals | PLOS Jun 19 2017 Ophthalmology
  
  Purpose To quantitatively investigate the characteristics of eyes with pituitary adenoma presented by three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) using three common indices, including thickness, optical intensity ratio, and optical intensity attenuation coefficient (OIAC). Methods The SD-OCT database of 38 patients with pituitary adenoma and 39 normal controls were included in the study. Quadrantal and average measurements of thickness, optical intensity ratio, and OIAC were calculated for macular retinal nerve fiber layer (mRNFL), ganglion cell layer (GCL) combined with inner plexiform layer (IPL) (GCIPL) and/or the collective ganglion cell complex (GCC). The parameters of patients and controls were ...
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  Mentions: Topcon Medical Systems
15. Retinal SD-OCT image-based pituitary tumor screening
  
  Explore Conference Proceedings Mar 7 2017 Ophthalmology
  
  In most cases, the pituitary tumor compresses optic chiasma and causes optic nerves atrophy, which will reflect in retina. In this paper, an Adaboost classification based method is first proposed to screen pituitary tumor from retinal spectral- domain optical coherence tomography (SD-OCT) image. The method includes four parts: pre-processing, feature extraction and selection, training and testing. First, in the pre-processing step, the retinal OCT image is segmented into 10 layers and the first 5 layers are extracted as our volume of interest (VOI). Second, 19 textural and spatial features are extracted from the VOI. Principal component analysis (PCA) is utilized ...
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  Mentions: Soochow University
16. Nonrigid registration of 3D longitudinal optical coherence tomography volumes with choroidal neovascularization
  
  Explore Conference Proceedings Mar 3 2017 Ophthalmology
  
  In this paper, we propose a 3D registration method for retinal optical coherence tomography (OCT) volumes. The proposed method consists of five main steps: First, a projection image of the 3D OCT scan is created. Second, the vessel enhancement filter is applied on the projection image to detect vessel shadow. Third, landmark points are extracted based on both vessel positions and layer information. Fourth, the coherent point drift method is used to align retinal OCT volumes. Finally, a nonrigid B-spline-based registration method is applied to find the optimal transform to match the data. We applied this registration method on 15 ...
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  Mentions: Soochow University Haoyu Chen
17. Graph search: active appearance model based automated segmentation of retinal layers for optic nerve head centered OCT images
  
  Explore Conference Proceedings Mar 1 2017 Ophthalmology
  
  In this paper, a novel approach combining the active appearance model (AAM) and graph search is proposed to segment retinal layers for optic nerve head(ONH) centered optical coherence tomography(OCT) images. The method includes two parts: preprocessing and layer segmentation. During the preprocessing phase, images is first filtered for denoising, then the B-scans are flattened. During layer segmentation, the AAM is first used to obtain the coarse segmentation results. Then a multi-resolution GS–AAM algorithm is applied to further refine the results, in which AAM is efficiently integrated into the graph search segmentation process. The proposed method was tested ...
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  Mentions: Soochow University Haoyu Chen
18. Depth-encoded dual beam phase-resolved Doppler OCT for Doppler-angle-independent flow velocity measurement
  
  Explore Conference Proceedings Mar 1 2017
  
  Phase-resolved Doppler optical coherence tomography (PR-D-OCT) is a functional OCT imaging technique that can provide high-speed and high-resolution depth-resolved measurement on flow in biological materials. However, a common problem with conventional PR-D-OCT is that this technique often measures the flow motion projected onto the OCT beam path. In other words, it needs the projection angle to extract the absolute velocity from PR-D-OCT measurement. In this paper, we proposed a novel dual-beam PR-D-OCT method to measure absolute flow velocity without separate measurement on the projection angle. Two parallel light beams are created in sample arm and focused into the sample at ...
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  Mentions: Soochow University Jianhua Mo
19. Dual-beam angular compounding for speckle reduction in optical coherence tomography
  
  Explore Conference Proceedings Feb 23 2017
  
  Optical coherence tomography (OCT), as a low-coherence interferometric imaging technique, inevitably suffers from speckle noise, which can reduce image quality and signal-to-noise (SNR). In this paper, we present a dual-beam angular compounding method to reduce speckle noise and improve SNR of OCT image. Two separated parallel light beams are created on the sample arm using a 1x2 optical fiber coupler and are focused into samples at different angles. The epi-detection scheme creates three different light path combinations of these two light beams above. The three combinations produce three images in single B-scan, which are completely separated in depth. The three ...
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  Mentions: Soochow University Jianhua Mo
20. Enhanced low-rank + sparsity decomposition for speckle reduction in optical coherence tomography
  
  Explore SPIE | Journal Jul 22 2016
  
  Speckle artifacts can strongly hamper quantitative analysis of optical coherence tomography (OCT), which is necessary to provide assessment of ocular disorders associated with vision loss. Here, we introduce a method for speckle reduction, which leverages from low-rank + sparsity decomposition (LRpSD) of the logarithm of intensity OCT images. In particular, we combine nonconvex regularization-based low-rank approximation of an original OCT image with a sparsity term that incorporates the speckle. State-of-the-art methods for LRpSD require a priori knowledge of a rank and approximate it with nuclear norm, which is not an accurate rank indicator. As opposed to that, the proposed method provides ...
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  Mentions: Soochow University
21. A framework for classification and segmentation of branch retinal artery occlusion in SD-OCT
  
  Explore Conference Proceedings Apr 1 2016 Ophthalmology
  
  Branch retinal artery occlusion (BRAO) is an ocular emergency which could lead to blindness. Quantitative analysis of BRAO region in the retina is very needed to assessment of the severity of retinal ischemia. In this paper, a fully automatic framework was proposed to classify and segment BRAO based on 3D spectral-domain optical coherence tomography (SD-OCT) images. To the best of our knowledge, this is the first automatic 3D BRAO segmentation framework. First, a support vector machine (SVM) based classifier is designed to differentiate BRAO into acute phase and chronic phase, and the two types are segmented separately. To segment BRAO ...
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  Mentions: Haoyu Chen
22. Depths-encoded angular compounding for speckle reduction in optical coherence tomography
  
  Explore Conference Proceedings Mar 15 2016
  
  Optical coherence tomography (OCT) is one of the successful inventions in medical imaging as a clinic routine in the past decades. This imaging technique is based on low coherence interferometer and consequently suffers from speckle noise inherently, which can degrade image quality and obscure micro-structures. Therefore, effective speckle reduction techniques have been always desired and researched since optical coherence tomography was invented. In this study, we proposed an angular compounding method to reduce speckle noise of OCT image. Two different angular light paths are created on the sample arm using two beam splitters. The epi-detection scheme creates three different combinations ...
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  Mentions: Soochow University Jianhua Mo
23. Profile and Determinants of Retinal Optical Intensity in Normal Eyes with Spectral Domain Optical ...
  
  Explore Journals | PLOS Feb 10 2016 Ophthalmology
  
  Purpose To investigate the profile and determinants of retinal optical intensity in normal subjects using 3D spectral domain optical coherence tomography (SD OCT). Methods A total of 231 eyes from 231 healthy subjects ranging in age from 18 to 80 years were included and underwent a 3D OCT scan. Forty-four eyes were randomly chosen to be scanned by two operators for reproducibility analysis. Distribution of optical intensity of each layer and regions specified by the Early Treatment of Diabetic Retinopathy Study (ETDRS) were investigated by analyzing the OCT raw data with our automatic graph-based algorithm. Univariate and multivariate analyses were ...
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  Mentions: Topcon Medical Systems The Chinese University of Hong Kong University of Hong Kong
24. Automated segmentation of serous pigment epithelium detachment in SD-OCT images
  
  Explore Conference Proceedings Mar 28 2015 Ophthalmology
  
  Pigment epithelium detachment (PED) is an important clinical manifestation of multiple chorio-retinal disease processes, which can cause the loss of central vision. A 3-D method is proposed to automatically segment serous PED in SD-OCT images. The proposed method consists of five steps: first, a curvature anisotropic diffusion filter is applied to remove speckle noise. Second, the graph search method is applied for abnormal retinal layer segmentation associated with retinal pigment epithelium (RPE) deformation. During this process, Bruch’s membrane, which doesn’t show in the SD-OCT images, is estimated with the convex hull algorithm. Third, the foreground and background seeds ...
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  Mentions: Soochow University Haoyu Chen
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