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    1. A Step-Index Silicate Nonlinear Fiber With All Normal Flattened Dispersion for Coherent Supercontinuum

      A Step-Index Silicate Nonlinear Fiber With All Normal Flattened Dispersion for Coherent Supercontinuum

      A step-index silicate fiber with all normal flat dispersion was fabricated. Coherent supercontinuum (SC) spectrum spanning 1200 to 2000 nm was generated in a 5 cm silicate fiber pumped at 1560 nm. The numerical simulation result agreed with the experiment result. Also, highly coherent SC spectrum spanning from 1100 to 2100 nm with flatness <7 dB generated in the fiber with 57 kW pumping power according to simulation. The step-index silicate fiber is not only easy to prepare but also a promising candidate to achieve all-fiber structure for coherent SC.

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    2. Deep Neural Network Regression for Automated Retinal Layer Segmentation in Optical Coherence Tomography Images

      Deep Neural Network Regression for Automated Retinal Layer Segmentation in Optical Coherence Tomography Images

      Segmenting the retinal layers in optical coherence tomography (OCT) images helps to quantify the layer information in early diagnosis of retinal diseases, which are the main cause of permanent blindness. Thus, the segmentation process plays a critical role in preventing vision impairment. However, because there is a lack of practical automated techniques, expert ophthalmologists still have to manually segment the retinal layers. In this study, we propose an automated segmentation method for OCT images based on a feature-learning regression network without human bias. The proposed deep neural network regression takes the intensity, gradient, and adaptive normalized intensity score (ANIS) of ...

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      Mentions: Korea University
    3. RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge

      RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge

      Retinal swelling due to the accumulation of fluid is associated with the most vision-threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of care in assessing the presence and quantity of retinal fluid and image-guided treatment management. Deep learning methods have made their impact across medical imaging, and many retinal OCT analysis methods have been proposed. However, it is currently not clear how successful they are in interpreting the retinal fluid on OCT, which is due to the lack of standardized benchmarks. To address this, we organized a challenge RETOUCH in conjunction with MICCAI 2017, with eight teams ...

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    4. Automatic Lumen Segmentation in Intravascular Optical Coherence Tomography Using Morphological Features

      Automatic Lumen Segmentation in Intravascular Optical Coherence Tomography Using Morphological Features

      Lumen segmentation in intravascular optical coherence tomography (IVOCT) images is a fundamental work for more advanced plaque analysis, stent recognition, fractional flow reserve (FFR) assessment, and so on. However, the catheter, guide-wire, inadequate blood clearance, and other factors will impact on the accuracy of lumen segmentation. We present a simple and effective method for automatic lumen segmentation method in IVOCT based on morphological features. We use image enhancement, median filtering, image binarization, and morphological closing operation to reduce speckle noise, minimize the effect of blood artifacts and fill in small holes inside vascular walls. We extract the orientation and area-size ...

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    5. Automated Deformation-Based Analysis of 3D Optical Coherence Tomography in Diabetic Retinopathy

      Automated Deformation-Based Analysis of 3D Optical Coherence Tomography in Diabetic Retinopathy

      Diabetic retinopathy (DR) is a significant microvascular complication of diabetes mellitus and a leading cause of vision impairment in working age adults. Optical coherence tomography (OCT) is a routinely used clinical tool to observe retinal structural and thickness alterations in DR. Pathological changes that alter the normal anatomy of the retina, such as intraretinal edema, pose great challenges for conventional layer-based analysis of OCT images. We present an alternative approach for the automated analysis of OCT volumes in DR research based on nonlinear registration. In our work, we first obtain an anatomically consistent volume of interest (VOI) in different OCT ...

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    6. Automatic Classification of Retinal Optical Coherence Tomography Images With Layer Guided Convolutional Neural Network

      Automatic Classification of Retinal Optical Coherence Tomography Images With Layer Guided Convolutional Neural Network

      Optical coherence tomography (OCT) enables instant and direct imaging of morphological retinal tissue and has become an essential imaging modality for ophthalmology diagnosis. As one of the important morphological retinal characteristics, the structural information of retinal layers provides meaningful diagnostic information and is closely related to several retinal diseases. In this letter, we propose a novel layer guided convolutional neural network (LGCNN) to identify normal retina and three common types of macular pathologies, namely, diabetic macular edema, drusen, and choroidal neovascularization. Specifically, an efficient segmentation network is first employed to generate the retinal layer segmentation maps, which can delineate two ...

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    7. Segmentation of Retinal Cysts From Optical Coherence Tomography Volumes Via Selective Enhancement

      Segmentation of Retinal Cysts From Optical Coherence Tomography Volumes Via Selective Enhancement

      Automated and accurate segmentation of cystoid structures in optical coherence tomography (OCT) is of interest in the early detection of retinal diseases. It is, however, a challenging task. We propose a novel method for localizing cysts in 3-D OCT volumes. The proposed work is biologically inspired and based on selective enhancement of the cysts, by inducing motion to a given OCT slice. A convolutional neural network is designed to learn a mapping function that combines the result of multiple such motions to produce a probability map for cyst locations in a given slice. The final segmentation of cysts is obtained ...

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    8. An averaged intensity difference detection algorithm for identification of human gingival sulcus in optical coherence tomography images

      An averaged intensity difference detection algorithm for identification of human gingival sulcus in optical coherence tomography images

      In the past decade, there has been an increase in the development of sensitive, highresolution, non-invasive diagnostic methods for periodontic diseases. Optical coherence tomography (OCT) has attracted considerable attention in clinical settings. In this study, a reliable, robust algorithm for the detection of gingival sulcus in 2D OCT cross-sectional images is proposed. Previously, the measurement of gingival sulcus in OCT images has been performed by manual identification using two-dimensional (2D) cross-sectional images. The automated detection of gingival sulcus continuity in 2D OCT images may help medical practitioners to assess important features of gingival tissues. The Sobel and canny operators have ...

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    9. Decreasing the Size of a Spectral Domain Optical Coherence Tomography System With Cascaded ...

      Decreasing the Size of a Spectral Domain Optical Coherence Tomography System With Cascaded ...

      This paper describes a proof-of-concept of a miniaturized spectral-domain optical coherence tomography system, based on photonic integrated circuit (PIC) technology. The integrated optics 512-channel spectrometer consists of cascaded arrayed waveguide gratings (AWG) with the output waveguides directly attached to a CCD detector. The spectrometer has a center wavelength of 850 nm and a spectral sampling interval of 0.22 nm. The PIC has a footprint of 2.0 × 2.7 cm 2 . The wavelength response of the cascaded AWG spectrometer is calibrated with a tunable laser. Free space OCT measurements are done with a mirror as sample. The signal-to-noise ratio ...

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    10. Geometric Validation of Continuous, Finely Sampled 3-D Reconstructions From aOCT and CT in Upper Airway Models

      Geometric Validation of Continuous, Finely Sampled 3-D Reconstructions From aOCT and CT in Upper Airway Models

      Identification and treatment of obstructive airway disorders (OADs) are greatly aided by imaging of the geometry of the airway lumen. Anatomical optical coherence tomography (aOCT) is a promising high-speed and minimally invasive endoscopic imaging modality for providing micrometer-resolution scans of the upper airway. Resistance to airflow in OADs is directly caused by the reduction in luminal cross-sectional area (CSA). It is hypothesized that aOCT can produce airway CSA measurements as accurate as that from computed tomography (CT). Scans of machine hollowed cylindrical tubes were used to develop methods for segmentation and measurement of airway lumen in CT and aOCT. Simulated ...

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    11. A FBG-OCT Catheter to reconstruct vascular shape in intravascular optical coherence tomography

      A FBG-OCT Catheter to reconstruct vascular shape in intravascular optical coherence tomography

      We propose a novel Fiber Bragg Grating (FBG)-Optical Coherence Tomography (OCT) catheter to reconstruct vascular shape by intravascular OCT imaging of the actual curvature as well as the bending direction of the vascular in real-time. Compared with the traditional OCT catheter, the FBG-OCT catheter uses the FBG encapsulated with half-sectioned stainless-steel tube as a flexural sensitive component. With the 360-degree rotation of the catheter, the encapsulated FBG will produce maximum tension and maximum compression at the bend of the blood vessel, and then get the solution of the curvature and direction of the bending catheter as well as the ...

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      Mentions: Tiegen Liu
    12. Establishment of an Automated Algorithm Utilizing Optical Coherence Tomography and Micro-Computed Tomography Imaging to Reconstruct the 3-D Deformed Stent Geometry

      Establishment of an Automated Algorithm Utilizing Optical Coherence Tomography and Micro-Computed Tomography Imaging to Reconstruct the 3-D Deformed Stent Geometry

      Percutaneous coronary intervention (PCI) is the prevalent treatment for coronary artery disease, with hundreds of thousands of stents implanted annually. Computational studies have demonstrated the role of biomechanics in the failure of vascular stents, but clinical studies is this area are limited by a lack of understanding of the deployed stent geometry, which is required to accurately model and predict the stent-induced in vivo biomechanical environment. Herein, we present an automated method to reconstruct the 3-D deployed stent configuration through the fusion of optical coherence tomography (OCT) and micro-computed tomography ( μ CT) imaging data. In an experimental setup, OCT and μ CT ...

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    13. Cardiac muscle energetics: Improved normalisation of heat using optical coherence tomography

      Cardiac muscle energetics: Improved normalisation of heat using optical coherence tomography

      Heat liberated from isolated cardiac muscle has been used to inform us of thermo-mechanical processes that occur during a contraction. However, for comparisons between different samples to be useful, the heat output needs to be normalized to volume. We have implemented an optical coherence tomograph (OCT), together with a flow-through calorimeter, to accurately determine both muscle volume and heat in the same measurement chamber. The heat rate for multiple stimulation frequencies were recorded and normalized to the volume captured by the OCT. There was a ~15 % difference in the volume estimated by the OCT compared to the standard 1D approximation ...

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    14. Attention to Lesion: Lesion-Aware Convolutional Neural Network for Retinal Optical Coherence Tomography Image Classification

      Attention to Lesion: Lesion-Aware Convolutional Neural Network for Retinal Optical Coherence Tomography Image Classification

      Automatic and accurate classification of retinal optical coherence tomography (OCT) images is essential to assist ophthalmologist in the diagnosis and grading of macular diseases. Clinically, ophthalmologists usually diagnose macular diseases according to the structures of macular lesions, whose morphologies, size, and numbers are important criteria. In this paper, we propose a novel lesion-aware convolutional neural network (LACNN) method for retinal OCT image classification, in which retinal lesions within OCT images are utilized to guide the CNN to achieve more accurate classification. The LACNN simulates the ophthalmologists’ diagnosis that focuses on local lesion-related regions when analyzing the OCT image. Specifically, we ...

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    15. Optical coherence tomography with gapped spectrum

      Optical coherence tomography with gapped spectrum

      The axial resolution of optical coherence tomography (OCT) is determined by the spectral shape and bandwidth of the detected light, which are limited by the gaps in the wavelength range of illumination, transmission, and detection. In this work, we demonstrate that the axial resolution deteriorated by gaps in OCT spectra can be restored by adopting the gapped amplitude and phase estimation (GAPES) method. GAPES estimates the missing parts between separated spectral bands and obtains the axial profile of tissue with reduced sidelobe artifacts compared to the gapped spectra and significantly improved axial resolution over the individual bands. This technique may ...

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    16. Monitoring acute stroke progression: multi-parametric OCT imaging of cortical perfusion, flow, and tissue scattering in a mouse model of permanent focal ischemia

      Monitoring acute stroke progression: multi-parametric OCT imaging of cortical perfusion, flow, and tissue scattering in a mouse model of permanent focal ischemia

      Cerebral ischemic stroke causes injury to brain tissue characterized by a complex cascade of neuronal and vascular events. Imaging during early stages of its development allows prediction of tissue infarction and penumbra, so that optimal intervention can be determined in order to salvage brain function impairment. Therefore, there is a critical need for novel imaging techniques that can characterize brain injury in the earliest phases of ischemic stroke. This study examined optical coherence tomography (OCT) for imaging acute injury in experimental ischemic stroke in vivo. Based on endogenous optical scattering signals provided by OCT imaging, we have developed a single ...

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    17. Establishment of an Automated Algorithm Utilizing Optical Coherence Tomography and Micro-Computed Tomography Imaging to Reconstruct the 3D Deformed Stent Geometry

      Establishment of an Automated Algorithm Utilizing Optical Coherence Tomography and Micro-Computed Tomography Imaging to Reconstruct the 3D Deformed Stent Geometry

      Percutaneous coronary intervention (PCI) is the prevalent treatment for coronary artery disease, with hundreds of thousands of stents implanted annually. Computational studies have demonstrated the role of biomechanics in the failure of vascular stents, but clinical studies is this area are limited by a lack of understanding of the deployed stent geometry, which is required to accurately model and predict the stent induced in vivo biomechanical environment. Herein, we present an automated method to reconstruct the 3D deployed stent configuration through the fusion of optical coherence tomography (OCT) and micro-computed tomography (μCT) imaging data. In an experimental setup, OCT and ...

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    18. Nondestructive Measurement of Conformal Coating Thickness on Printed Circuit Board with Ultra-high Resolution Optical Coherence Tomography

      Nondestructive Measurement of Conformal Coating Thickness on Printed Circuit Board with Ultra-high Resolution Optical Coherence Tomography

      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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    19. Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks

      Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks

      Coronary heart disease is a common cause of death despite being preventable. To treat the underlying plaque deposits in the arterial walls, intravascular optical coherence tomography can be used by experts to detect and characterize the lesions. In clinical routine, hundreds of images are acquired for each patient, which require automatic plaque detection for fast and accurate decision support. So far, automatic approaches rely on classic machine learning methods and deep learning solutions have rarely been studied. Given the success of deep learning methods with other imaging modalities, a thorough understanding of deep learning-based plaque detection for future clinical decision ...

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    20. Semi-Supervised Automatic Segmentation of Layer and Fluid Region in Retinal Optical Coherence Tomography Images Using Adversarial Learning

      Semi-Supervised Automatic Segmentation of Layer and Fluid Region in Retinal Optical Coherence Tomography Images Using Adversarial Learning

      Optical coherence tomography (OCT) is a primary imaging technique for ophthalmic diagnosis due to its advantages in high resolution and non-invasiveness. Diabetes is a chronic disease, which could cause retinal layer deformation and fluid accumulation. It might increase the risk of blindness, and thus, it is important to monitor the morphology change of the retinal layer and fluid accumulation for diabetes patients. Due to the existence of deformation and fluid accumulation, the retinal layer and fluid region segmentation in the OCT image is a challenging task. Machine learning-based segmentation methods have been proposed, but they depend on a significant number ...

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    21. Integrating Handcrafted and Deep Features for Optical Coherence Tomography Based Retinal Disease Classification

      Integrating Handcrafted and Deep Features for Optical Coherence Tomography Based Retinal Disease Classification

      Deep Neural Networks (DNNs) have been widely applied to automatic analysis of medical images for disease diagnosis, and to help human experts by efficiently processing immense amounts of images. While handcrafted feature has been used for eye disease detection or classification since the 1990s, DNN was recently adopted in this area and showed very promising performance. Since handcrafted and deep feature can extract complementary information, we propose in this paper three different integration frameworks to combine handcrafted and deep feature for optical coherence tomography (OCT) image based eye disease classification. In addition, to integrate the handcrafted feature at Input and ...

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    22. Ultrafast Wavenumber Linear-step-swept source Based on Synchronous Lightwave Synthesized Frequency Sweeper

      Ultrafast Wavenumber Linear-step-swept source Based on Synchronous Lightwave Synthesized Frequency Sweeper

      An ultrafast wavenumber linear-step-swept source based on a synchronous lightwave synthesized frequency sweeper (SLSFS) is demonstrated. A multi-wavelength source is used as a seed source. In SLSFS, the swept range of different wavelength components is precisely controlled by a stable programmable radio frequency (RF) signal applied on a dual-parallel Mach-Zehnder modulator (DP-MZM) instead of a conventional wavelength filter. The identical frequency shifting step of all the wavelength components promises high linear sweeping in frequency domain. The key significance of this technique is that the swept rate and the swept range increases as the number of the seed wavelengths increases. Experimentally ...

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    23. Polarization-Sensitive Optical Coherence Tomography for Brain Tumor Characterization

      Polarization-Sensitive Optical Coherence Tomography for Brain Tumor Characterization

      Complete removal of brain tumor is of the most interest to a surgeon because the resection area directly relates to recurrence rate. Although there are many biomedical imaging modalities applied to locate the positions of tumors, they lack the spatial resolution to precisely delineate the boundary between brain tumor and normal brain tissues and are also inconvenient to be used intraoperatively. This study aims to examine the feasibility of the label-free, polarization-sensitive optical coherence tomography (PS-OCT) for distinguishing brain tumors from normal brain tissues. Ex vivo samples were obtained from two patients with grade II and II-III glioma; healthy porcine ...

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    24. Non-ionized, High-resolution Measurement of Internal and Marginal Discrepancies of Dental Prosthesis Using Optical Coherence Tomography

      Non-ionized, High-resolution Measurement of Internal and Marginal Discrepancies of Dental Prosthesis Using Optical Coherence Tomography

      An internal and marginal fit between prosthesis and abutment are important factors of the durability of dental prosthesis. In this study we have proposed the use of swept-source optical coherence tomography (SS-OCT) as a novel application for non-ionized and high-resolution measurements of internal and marginal discrepancies at anatomically critical four points, such as occlusal, angle, axial, and margin during prosthesis attachment. A tooth model was fabricated by 3D printing technique and the dental prosthesis was designed using dental CAD software. The cross-sectional images along with intensity peak profile analysis of the sample were acquired using OCT system for measurements of ...

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