1. 1-6 of 6
    1. BG-CNN: A Boundary Guided Convolutional Neural Network for Corneal Layer Segmentation from Optical Coherence Tomography

      BG-CNN: A Boundary Guided Convolutional Neural Network for Corneal Layer Segmentation from Optical Coherence Tomography

      Precise segmentation of corneal layers depicted on optical coherence tomography (OCT) images plays an important role in detecting corneal diseases, such as keratoconus and dry eye. In this study, we present a boundary guided convolutional neural network (BG-CNN) to extract different corneal layers. The developed network uses three convolutional blocks to construct two network modules derived from the classical U-Net network. This network was trained based on a dataset consisting of 1712 OCT images. The segmentation results demonstrated the developed network achieved an average dice similarity coefficient (DSC) of 0.9599 and an interFiguresection over union (IOU) of 0.9253 ...

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    2. Detection of Artificial Tooth Cracks based on Optical Coherence Tomography

      Detection of Artificial Tooth Cracks based on Optical Coherence Tomography

      Due to the hidden symptoms of the tooth cracks, the existing imaging technologies have problems of insufficient resolution and inaccurate detection. In this paper, a swept-source OCT system is designed, which is suitable for the full crown scanning of different kinds of teeth. And the artificial tooth-cracked model is prepared by the temperature difference method, the tooth cracks tomographic images of incisors, premolars and molars under different preparation conditions were obtained by the swept-source OCT. The experimental results show that the swept-source OCT system can image different grades of tooth cracks and monitor the progress of cracks. At the same ...

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    3. Three-dimensional Reconstruction of Optical Coherence Tomography Images of Esophagus

      Three-dimensional Reconstruction of Optical Coherence Tomography Images of Esophagus

      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 reconstruct three-dimensional image of OCT cross-section images of guinea pig esophagus. Preprocessing including image segmentation, coordinate transformation, angle correction is used to achieve a better result in three-dimensional reconstruction. The ...

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    4. Automatic vessel detection by means of brightness profile characterization in OCT images

      Automatic vessel detection by means of brightness profile characterization in OCT images

      Optical Coherence Tomography (OCT) is a well-established medical imaging technique that allows the analysis of the eye fundus characteristics in real time. These images enable the experts to make a clinical evaluation of the retinal vasculature, whose morphology provides relevant information for diseases like diabetes, hypertension or arteriosclerosis. In this paper, we present a novel proposal for the automatic vasculature identification in retinal OCT images. To achieve this, we analyse the intensity profiles between representative retinal layers, previously segmented. Then, two statistical models are generated using representative samples of vessel and non-vessel profiles. The analysis of both statistical models let ...

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    5. 3D Digital Microscopy for Characterizing Punchworks on Medieval Panel Paintings

      3D Digital Microscopy for Characterizing Punchworks on Medieval Panel Paintings

      This article is devoted to a novel application of the micro-3D modeling based on shape from focus. A 3D portable digital microscope prototype has been used for the first time in order to analyze gold punchwork on medieval panel paintings. In general, the 3D domain provides a more flexible and complete characterization of these decorative elements than traditional photographic documentation. Low-magnification 3D digital microscopy is well suited for analyzing morphologies, depths, and profiles of different punch marks. Here, we used these parameters for interpreting the punching process and recognizing sliding and bouncing effects. The 3D reconstruction of the surface engraved ...

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    6. A performance and energy comparison of convolution on GPUs, FPGAs, and multicore processors

      A performance and energy comparison of convolution on GPUs, FPGAs, and multicore processors

      Recent architectural trends have focused on increased parallelism via multicore processors and increased heterogeneity via accelerator devices (e.g., graphics-processing units, field-programmable gate arrays). Although these architectures have significant performance and energy potential, application designers face many device-specific challenges when choosing an appropriate accelerator or when customizing an algorithm for an accelerator. To help address this problem, in this article we thoroughly evaluate convolution, one of the most common operations in digital-signal processing, on multicores, graphics-processing units, and field-programmable gate arrays. Whereas many previous application studies evaluate a specific usage of an application, this article assists designers with design space ...

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    1-6 of 6
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