1. 1-24 of 333 1 2 3 4 ... 12 13 14 »
    1. Visualising ganglion cell layer based on image entropy optimisation for adaptive contrast enhancement

      Visualising ganglion cell layer based on image entropy optimisation for adaptive contrast enhancement

      Optical coherence tomography cannot easily be used for visual identification of the ganglion cell layer (GCL) for diagnosing retinal diseases owing to the extremely low image contrast between adjacent layers. To solve this problem, the authors used a limit-clipping optimisation method along with the image entropy to enhance the image contrast of targeted layers. As a result, the GCL was successfully extracted using an intelligent tracking system without impacting the segmentation of other retinal layers and image morphology. The segmentation results were evaluated through comparisons with manual segmentation results provided by clinical experts. The results of this study should help ...

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    2. Optical Biopsy of Melanoma and Basal Cell Carcinoma Progression by Noncontact Photoacoustic and Optical Coherence Tomography: In vivo Multi-parametric Characterizing Tumor Microenvironment

      Optical Biopsy of Melanoma and Basal Cell Carcinoma Progression by Noncontact Photoacoustic and Optical Coherence Tomography: In vivo Multi-parametric Characterizing Tumor Microenvironment

      Measuring the structural and functional status of tumor microenvironment for malignant melanoma (MM) and basal cell carcinoma (BCC) is of profound significance in understanding dermatological condition for biopsy. However, conventional optical imaging techniques are limited to visualize superficial skin features and parameter information is deficient to depict pathophysiology correlations of skin diseases. Here, we demonstrate a preclinical device, all-optically integrated photoacoustic and optical coherence tomography (AOPA/OCT), that, for the first time, can simultaneously provide label-free biomarkers of vascular patterns, temporal and spatial heterogeneity of blood flow, and tissue micro-structure changes during tumor growth with pathophysiological correlations in mice models ...

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    3. Catheter-Based Polarization Sensitive Optical Coherence Tomography Using Similar Mueller Matrix Method

      Catheter-Based Polarization Sensitive Optical Coherence Tomography Using Similar Mueller Matrix Method

      Objective : Research of catheter-based polarization sensitive optical coherence tomography (PS-OCT) is a challenging field. In this paper, we present a new polarization determination method, similar Mueller matrix (SMM) method, for a catheter-based PS-OCT system using a standard clinical catheter probe with an outer diameter of 0.9 mm. Methods : The SMM method can remove the diattenuation and depolarization compositions by polar decomposition. By constructing the similarity between the measured Mueller matrices and sample matrices, the phase retardance of the sample can be determined from the trace of the measured matrices. Results : In the experiments, we find that images processed by ...

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    4. Machine-Learning Classification of Port Wine Stain With Quantitative Features of Optical Coherence Tomography Image

      Machine-Learning Classification of Port Wine Stain With Quantitative Features of Optical Coherence Tomography Image

      Port wine stain (PWS) is the benign congenital capillary malformation of skin, occurring in 0.3% to 0.5% of the population. In this paper, we build two automated support vector machine (SVM) based classifiers by extracting quantitative features from normal and PWS tissue images recorded by optical coherence tomography (OCT). We use both full feature set and simplified feature set for training. Accuracy of 92.7%, sensitivity of 92.3% and specificity of 93.8% were obtained for classifier with full feature set. Accuracy of 92.7%, sensitivity of 94.9% and specificity of 87.5% were obtained for ...

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    5. Optical Coherence Tomography Guided Robotic Needle Insertion for Deep Anterior Lamellar Keratoplasty

      Optical Coherence Tomography Guided Robotic Needle Insertion for Deep Anterior Lamellar Keratoplasty

      Objective: Deep anterior lamellar keratoplasty (DALK) significantly reduces the post-transplantation morbidity in patients eligible for partial-thickness cornea grafts. The popular "big bubble" technique for DALK is so challenging, however, that a significant fraction of corneal pneumodissection attempts fail for surgeons without extensive DALK-specific experience, even with previous-generation cross-sectional optical coherence tomography (OCT) guidance. We seek to develop robotic, volumetric OCT-guided technology capable of facilitating or automating the difficult needle insertion step in DALK. Methods: Our system provides for real-time volumetric corneal imaging, segmentation, and tracking of the needle insertion to display feedback for surgeons and to generate needle insertion plans ...

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    6. Simultaneous morphological and flow imaging enabled by megahertz intravascular Doppler optical coherence tomography

      Simultaneous morphological and flow imaging enabled by megahertz intravascular Doppler optical coherence tomography

      We demonstrate three-dimensional intravascular flow imaging compatible with routine clinical image acquisition workflow by means of megahertz (MHz) intravascular Doppler Optical Coherence Tomography (OCT). The OCT system relies on a 1.1 mm diameter motorized imaging catheter and a 1.5 MHz Fourier Domain Mode Locked (FDML) laser. Using a post processing method to compensate the drift of the FDML laser output, we can resolve the Doppler phase shift between two adjoining OCT A-line datasets. By interpretation of the velocity field as measured around the zero phase shift, the flow direction at specific angles can be qualitatively estimated. Imaging experiments ...

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    7. Segmentation Guided Registration for 3D Spectral-Domain Optical Coherence Tomography Images

      Segmentation Guided Registration for 3D Spectral-Domain Optical Coherence Tomography Images

      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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    8. Packaged Negative Axicon Optical Fiber Probe and Bessel Beam Interferometry for Refractive Index Measurement of Hazardous Liquid Sample

      Packaged Negative Axicon Optical Fiber Probe and Bessel Beam Interferometry for Refractive Index Measurement of Hazardous Liquid Sample

      In this work, we demonstrate the packaging of an optical fiber negative axicon probe generating Bessel beam and its application in the measurement of refractive index (RI) of hazardous liquids. The negative axicon probe is placed inside cascaded capillary tube capped with a glass coverslip of RI ~1.52 and thickness ~0.15 mm. The packaged probe, connected to a broadband source through an optical circulator, is dipped in different hazardous liquid samples. The reflected light from the air-glass as well as the glass-liquid interface couples to the negative axicon probe and interferes with the reference beam generated at the ...

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    9. Multi-level Dual-attention Based CNN for Macular Optical Coherence Tomography Classification

      Multi-level Dual-attention Based CNN for Macular Optical Coherence Tomography Classification

      In this letter, we propose a multi-level dual-attention model to classify two common macular diseases, age-related macular degeneration (AMD) and diabetic macular edema (DME) from normal macular eye conditions using optical coherence tomography (OCT) imaging technique. Our approach unifies the dual-attention mechanism at multi-levels of the pre-trained deep convolutional neural network (CNN). It provides a focused learning mechanism by taking into account both multi-level features based attention focusing on the salient coarser features and self-attention mechanism attending higher entropy regions of the finer features. Our proposed method enables the network to automatically focus on the relevant parts of the input ...

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    10. Intraoperative Speckle Variance Optical Coherence Tomography for Tissue Temperature Monitoring During Cutaneous Laser Therapy

      Intraoperative Speckle Variance Optical Coherence Tomography for Tissue Temperature Monitoring During Cutaneous Laser Therapy

      Background: Tissue temperature monitoring during cutaneous laser therapy can lead to safer and more effective treatments. In this study, we investigate the use of speckle variance optical coherence tomography (svOCT) to monitor real-time temperature changes in the excised human skin tissue sample during laser irradiation. Methods: To accomplish this, we combined the pulse laser system with a reference-based svOCT system. To calibrate the svOCT, the ex-vivo human skin samples from three individuals with tissues collected from the arm, face, and back were heated with 1-degree increments. Additionally, linear regression was used to extract and evaluate the linear relationship between the ...

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    11. Highlighting Directional Reflectance Properties of Retinal Substructures From D-OCT Images

      Highlighting Directional Reflectance Properties of Retinal Substructures From D-OCT Images

      Optical coherence tomography (OCT), which is routinely used in ophthalmology, enables transverse optical imaging of the retina and, hence, the identification of the different neuronal layers. Directional OCT (D-OCT) extends this technology by acquiring sets of images at different incidence angles of the light beam. In this way, reflectance properties of photoreceptor substructures are highlighted, enabling physicians to study their orientation, which is potentially an interesting biomarker for retinal diseases. Nevertheless, commercial OCT devices equipped to automate D-OCT acquisition do not yet exist, meaning that physicians manually deviate the light beam to acquire a set of D-OCT images sequentially. Therefore ...

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    12. 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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    13. 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
    14. 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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    15. 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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    16. 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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    17. 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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    18. 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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    19. 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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    20. 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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    21. 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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    22. 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
    23. 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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    24. 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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