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1. Mentioned In 34 Articles
2. 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 ...
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  Mentions: Soochow University
3. Three-dimensional Reconstruction of Optical Coherence Tomography Images of Esophagus
  
  Explore ACM Digital Library Oct 1 2019
  
  The combination of optical coherence tomography (OCT) and endoscope can take images of the body tissues for clinical diagnosis. OCT images are difficult to photograph with regular imaging devices, such as the esophagus and gastrointestinal tract. Three-dimensional reconstruction of the two-dimensional sequence images can help the doctor understand the clinical situation of the body tissue, therefore improve the accuracy of diagnosis. In this paper, Ray Casting method is used to ...
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4. 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 ...
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5. 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 ...
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
6. A New Approach for the Segmentation of Three Distinct Retinal Capillary Plexuses Using Optical Coherence Tomography Angiography
  
  Explore TVST Journal Jul 6 2019 Ophthalmology
  
  Purpose : To segment three distinct retinal capillary plexuses by using optical coherence tomography angiography (OCTA). Methods : This prospective study included 30 eyes of 15 healthy subjects. En face OCTA images generated by the AngioPlex platform were manually segmented by the progressive matching method to the superficial, middle, and deep capillary plexuses (SCP, MCP, and DCP, respectively). The estimated position of each plexus relative to the reference line was calculated. Vascular ...
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7. 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 diskfovea 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 ...
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
8. A RESNET-BASED UNIVERSAL METHOD FOR SPECKLE REDUCTION IN OPTICAL COHERENCE TOMOGRAPHY IMAGES
  
  Explore arxiv.org Mar 31 2019
  
  In this work we propose a ResNet-based universal method for speckle reduction in optical coherence tomography (OCT) images. The proposed model contains 3 main modules: Convolution-BN-ReLU, Branch and Residual module. Unlike traditional algorithms, the model can learn from training data instead of selecting parameters manually such as noise level. Application of this proposed method to the OCT images shows a more than 22 dB signal-to-noise ratio improvement in speckle noise ...
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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 ...
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  Mentions: Nanyang Technological University University of Iowa Linbo Liu
10. Imaging cellular structures of atherosclerotic coronary arteries using circumferentially scanning micro-optical coherence tomography fiber probe ex vivo
  
  Explore IEEE Xplore Nov 6 2018 Cardiology
  
  Development and progression of coronary atherosclerotic lesions is mediated by a number of cellular components, which are not readily visualized using the current clinical investigation tools. Visualizing these cellular components in situ and in vivo may allow early detection of the vulnerable plaques, with implications for coronary artery disease (CAD) therapy and for the prevention of acute myocardial infarction (AMI). In this study, we have developed a fiber-optic micro-optical coherence ...
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  Mentions: Nanyang Technological University Linbo Liu Soochow University
11. 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 ...
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12. Relationship between filtering bleb vascularization and surgical outcomes after trabeculectomy: an optical coherence tomography angiography study
  
  Explore Home - Springer Sep 19 2018 Ophthalmology
  
  Purpose To explore the relationship between the bleb vasculature and surgical outcome after trabeculectomy (TRAB) using optical coherence tomography angiography (OCT-A). Methods A prospective study was conducted, which included 26 eyes of 26 primary glaucoma patients in the final analysis. Thereinto, six patients underwent TRAB combined 5-FU and 12 patients received subconjunctival 5-FU injection postoperation. The bleb vessel was evaluated using OCT-A 1 week, 2 weeks, 1 month, 3 months ...
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13. Surrogate-assisted Retinal OCT Image Classification Based on Convolutional Neural Networks
  
  Explore IEEE Xplore Jul 12 2018 Ophthalmology
  
  Optical Coherence Tomography (OCT) is becoming one of the most important modalities for the noninvasive assessment of retinal eye diseases. As the number of acquired OCT volumes increases, automating the OCT image analysis is becoming increasingly relevant. In this paper, we propose a surrogate-assisted classification method to classify retinal OCT images automatically based on convolutional neural networks (CNNs). Image denoising is first performed to reduce the noise. Thresholding and morphological ...
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14. Extending axial focus of optical coherence tomography using parallel multiple aperture synthesis
  
  Explore OSA | OSA Publishing Apr 26 2018
  
  Compromising the inherent trade-off between transverse resolution and depth of focus (DOF) remains a long-standing issue in optical coherence tomography (OCT). In this work, we report a novel techniqueparallel multiple aperture synthesis (pMAS) to simultaneously generate multiple optical apertures in an OCT sample arm by employing a two-surface coated mirror. In the proposed pMAS, the DOF is extended by a factor of 16.49 without sacrificing the transverse resolution for ...
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  Mentions: Nanyang Technological University Linbo Liu Soochow University
15. 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 ...
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  Mentions: The Chinese University of Hong Kong Soochow University Haoyu Chen
16. 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 ...
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  Mentions: Xiaoming Xiang Soochow University Haoyu Chen
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