1. Articles from Valery Naranjo

    1-3 of 3

    1. Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging

      Explore MDPI Open Access Journals Platform Ophthalmology
      Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging

      Glaucoma is a neurodegenerative disease process that leads to progressive damage of the optic nerve to produce visual impairment and blindness. Spectral-domain OCT technology enables peripapillary circular scans of the retina and the measurement of the thickness of the retinal nerve fiber layer (RNFL) for the assessment of the disease status or progression in glaucoma patients. This paper describes a new approach to segment and measure the retinal nerve fiber layer in peripapillary OCT images. The proposed method consists of two stages. In the first one, morphological operators robustly detect the coarse location of the layer boundaries, despite the speckle ...

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    2. Glaucoma Detection from Raw SD-OCT Volumes: A Novel Approach Focused on Spatial Dependencies

      Explore ScienceDirect Ophthalmology
      Glaucoma Detection from Raw SD-OCT Volumes: A Novel Approach Focused on Spatial Dependencies

      Background and objective: Glaucoma is the leading cause of blindness worldwide. Many studies based on fundus image and optical coherence tomography (OCT) imaging have been developed in the literature to help ophthalmologists through artificial-intelligence techniques. Currently, 3D spectral-domain optical coherence tomography (SD-OCT) samples have become more important since they could enclose promising information for glaucoma detection. To analyse the hidden knowledge of the 3D scans for glaucoma detection, we have proposed, for the first time, a deep-learning methodology based on leveraging the spatial dependencies of the features extracted from the B-scans. Methods: The experiments were performed on a database composed ...

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    3. Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks

      Explore Frontiers Dermatology
      Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks

      Optical coherence tomography (OCT) is a well-established bedside imaging modality that allows analysis of skin structures in a non-invasive way. Automated OCT analysis of skin layers is of great relevance to study dermatological diseases. In this paper, an approach to detect the epidermal layer along with the follicular structures in healthy human OCT images is presented. To the best of the authors' knowledge, the approach presented in this paper is the only epidermis detection algorithm that segments the pilosebaceous unit, which is of importance in the progression of several skin disorders such as folliculitis, acne, lupus erythematosus, and basal cell ...

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    1-3 of 3
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    Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks Glaucoma Detection from Raw SD-OCT Volumes: A Novel Approach Focused on Spatial Dependencies Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging New insights from non-invasive imaging: from prospection of skin photodamages to training with mobile application Short-sighted woman assumes debilitating headaches mean she needs new glasses but discovers she has multiple sclerosis Shedding light on the impact of microplastics on lentil seedling growth Comparison of radial peripapillary capillary density results of individuals with and without Helicobacter pylori infection Ai, Oct Operate in Tandem to Detect Plaque Erosion in the Heart Noninvasive, in vivo, characterization of cutaneous metastases using a novel multimodal RCM-OCT imaging device: A case-series Mimickers of punctate inner retinal toxoplasmosis on optical coherence tomography Measuring collagen injury depth for burn severity determination using polarization sensitive optical coherence tomography Subretinal drusenoid deposits as a biomarker of age-related macular degeneration progression via reduction of the choroidal vascularity index