1. Articles from Marcos Ortega

    1-17 of 17
    1. Joint Diabetic Macular Edema Segmentation and Characterization in OCT Images

      Joint Diabetic Macular Edema Segmentation and Characterization in OCT Images

      The automatic identification and segmentation of edemas associated with diabetic macular edema (DME) constitutes a crucial ophthalmological issue as they provide useful information for the evaluation of the disease severity. According to clinical knowledge, the DME disorder can be categorized into three main pathological types: serous retinal detachment (SRD), cystoid macular edema (CME), and diffuse retinal thickening (DRT). The implementation of computational systems for their automatic extraction and characterization may help the clinicians in their daily clinical practice, adjusting the diagnosis and therapies and consequently the life quality of the patients. In this context, this paper proposes a fully automatic ...

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    2. Intraretinal fluid map generation in optical coherence tomography images (book chapter)

      Intraretinal fluid map generation in optical coherence tomography images (book chapter)

      The retina represents one of the most studied parts of the human body, thanks to its easy access for any ophthalmological study. It represents the main neurosensory part of the eye and, by its study, pathologies not only from the visual system but also from different body systems (like the neural system or vascular system) can be detected. Among the principal medical imaging modalities that are used to study the eye fundus and the retinal histological structures, the optical coherence tomography (OCT) has proven to be one of the most reliable techniques. It is widely used for the detection of ...

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    3. Intuitive and Coherent Intraretinal Cystoid Map Representation in Optical Coherence Tomography Images

      Intuitive and Coherent Intraretinal Cystoid Map Representation in Optical Coherence Tomography Images

      Fluid accumulations in between the retinal layers represent one of the main causes of blindness in developed countries. Currently, these fluid accumulations are detected by means of a manual inspection of Optical Coherence Tomography images, prone to subjective and non-quantifiable diagnostics. For this reason, numerous works aimed for an automated methodology. Nonetheless, these systems mostly focus on obtaining a defined segmentation, which is not always possible. For this reason, we present in this work a fully automatic methodology based in a fuzzy and confidence-based visualization of a regional analysis, allowing the clinicians to study the fluid accumulations independently of their ...

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    4. Intraretinal Fluid Pattern Characterization in Optical Coherence Tomography Images

      Intraretinal Fluid Pattern Characterization in Optical Coherence Tomography Images

      Optical Coherence Tomography (OCT) has become a relevant image modality in the ophthalmological clinical practice, as it offers a detailed representation of the eye fundus. This medical imaging modality is currently one of the main means of identification and characterization of intraretinal cystoid regions, a crucial task in the diagnosis of exudative macular disease or macular edema, among the main causes of blindness in developed countries. This work presents an exhaustive analysis of intensity and texture-based descriptors for its identification and classification, using a complete set of 510 texture features, three state-of-the-art feature selection strategies, and seven representative classifier strategies ...

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    5. Automatic Identification and Intuitive Map Representation of the Epiretinal Membrane Presence in 3D OCT Volumes

      Automatic Identification and Intuitive Map Representation of the Epiretinal Membrane Presence in 3D OCT Volumes

      Optical Coherence Tomography (OCT) is a medical image modality providing high-resolution cross-sectional visualizations of the retinal tissues without any invasive procedure, commonly used in the analysis of retinal diseases such as diabetic retinopathy or retinal detachment. Early identification of the epiretinal membrane (ERM) facilitates ERM surgical removal operations. Moreover, presence of the ERM is linked to other retinal pathologies, such as macular edemas, being among the main causes of vision loss. In this work, we propose an automatic method for the characterization and visualization of the ERM’s presence using 3D OCT volumes. A set of 452 features is refined ...

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    6. A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography

      A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography

      The assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure ...

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    7. Automatic Identification of Diabetic Macular Edema Using a Transfer Learning-Based Approach

      Automatic Identification of Diabetic Macular Edema Using a Transfer Learning-Based Approach

      This paper presents a complete system for the automatic identification of pathological Diabetic Macular Edema (DME) cases using Optical Coherence Tomography (OCT) images as source of information. To do so, the system extracts a set of deep features using a transfer learning-based approach from different fully-connected layers and different pre-trained Convolutional Neural Network (CNN) models. Next, the most relevant subset of deep features is identified using representative feature selection methods. Finally, a machine learning strategy is applied to train and test the potential of the identified deep features in the pathological classification process. Satisfactory results were obtained, demonstrating the suitability ...

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    8. Intraretinal fluid identification via enhanced maps using optical coherence tomography images

      Intraretinal fluid identification via enhanced maps using optical coherence tomography images

      Nowadays, among the main causes of blindness in developed countries are age-related macular degeneration (AMD) and the diabetic macular edema (DME). Both diseases present, as a common symptom, the appearance of cystoid fluid regions inside the retinal layers. Optical coherence tomography (OCT) image modality was one of the main medical imaging techniques for the early diagnosis and monitoring of AMD and DME via this intraretinal fluid detection and characterization. We present a novel methodology to identify these fluid accumulations by means of generating binary maps (offering a direct representation of these areas) and heat maps (containing the region confidence). To ...

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    9. Automatic Identification of Macular Edema in Optical Coherence Tomography Images

      Automatic Identification of Macular Edema in Optical Coherence Tomography Images

      This paper proposes a novel system for the simultaneous identification and characterization of the three types of Macular Edema (ME) in Optical Coherence Tomography (OCT). These MEs are clinically defined, by the reference classification of the field, as: Serous Retinal Detachment (SRD), Diffuse Retinal Thickening (DRT) and Cystoid Macular Edema (CME). Our system uses multilevel image thresholding approaches to identify the SRD and CME cases and a learning approach for the DRT identification. The system provided promising results with F-Measures of 83.35% and 81.95% for the DRT and CME detections, respectively. It was also efficient in detecting all ...

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    10. Optical Coherence Tomography Denoising by Means of a Fourier Butterworth Filter-Based Approach

      Optical Coherence Tomography Denoising by Means of a Fourier Butterworth Filter-Based Approach

      Optical Coherence Tomography (OCT) is affected by ubiquitous speckle noise that difficult the visualization and analysis of the retinal structures. Any denoising strategy should be able to remove efficiently the noise as well as preserves clinical information contained in the images. This information is crucial to analyses the retinal layer tissue that allows the posterior analysis and recognition of relevant diseases as macular edema or diabetic retinopathy. To address this issue, a method based on the Fourier Butterworth filter combined with a contrast enhancement and a histogram regularization was developed in order to reduce the speckle noise in OCT retinal ...

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    11. Feature Definition and Selection for Epiretinal Membrane Characterization in Optical Coherence Tomography Images

      Feature Definition and Selection for Epiretinal Membrane Characterization in Optical Coherence Tomography Images

      Optical Coherence Tomography (OCT) is a common imaging technique for the detection and analysis of optical diseases, since it is a non invasive method that generates in vivo a cross-sectional visualization of the retinal tissues. These characteristics contributed to the use of OCT imaging in the analysis of pathologies as, for instance, vitreomacular traction, age-related macular degeneration or hypertension. Among its applications, OCT imaging can be used in the detection of any present epiretinal membrane section in the retina, a critical issue to prevent further complications caused by this pathology. This work analyzed the main characteristics of the epiretinal membrane ...

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    12. 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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    13. Feature definition, analysis and selection for cystoid region characterization in Optical Coherence Tomography

      Feature definition, analysis and selection for cystoid region characterization in Optical Coherence Tomography

      Optical Coherence Tomography (OCT) is, nowadays, a clinical standard imaging technique in opthalmology as it provides more information than other classical modalities as can be, for instance, retinographies. OCT scans show a 3D representation of the real layout of the eye fundus in a non-invasive way, letting clinicians inspect deeply the retinal layers in a cross-sectional visualization. For that reason, OCT scans are commonly used in the study of the retinal morphology and the identification of pathological structures. Among them, an appropriate identification and analysis of any present intraretinal cystoid region is crucial to perform an adequate diagnosis of the ...

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    14. Automatic Identification of Intraretinal Cystoid Regions in Optical Coherence Tomography

      Automatic Identification of Intraretinal Cystoid Regions in Optical Coherence Tomography

      Optical Coherence Tomography (OCT) is, nowadays, one of the most referred ophthalmological imaging techniques. OCT imaging offers a window to the eye fundus in a non-invasive way, permitting the inspection of the retinal layers in a cross sectional visualization. For that reason, OCT images are frequently used in the analysis of relevant diseases such as hypertension or diabetes. Among other pathological structures, a correct identification of cystoid regions is a crucial task to achieve an adequate clinical analysis and characterization, as in the case of the analysis of the exudative macular disease. This paper proposes a new methodology for the ...

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    15. Automatic Detection of Epiretinal Membrane in OCT Images by Means of Local Luminosity Patterns

      Automatic Detection of Epiretinal Membrane in OCT Images by Means of Local Luminosity Patterns

      This work presents a novel approach for automatic detection of the epiretinal membrane in Optical Coherence Tomography (OCT) images. A tool able to detect this pathology is very valued since it can prevent further ocular damage by doing an early detection. This approach is based in the location of the inner limiting membrane (ILM) layers of the retina. Then, the detected locations are classified using a local-feature based vector in order to determine presence of the membrane. Different tests are run and compared to establish the appropriateness of the approach as well as its practical validity.

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    16. Automatic Vessel Shade-Robust Segmentation of Retinal Layers in OCT Images

      Automatic Vessel Shade-Robust Segmentation of Retinal Layers in OCT Images

      Optical Coherence Tomography (OCT) is a promising imaging technique used by ophthalmologists to diagnose diseases. Since retinal morphology can be identified on these images, several image processing-based methods are emerging with the purpose of extracting their information. The first step to tackle any automatic method to extract pathological features from these images is delimiting retinal layers automatically. This is the aim of this paper, which presents an active contour-based method to segment layer boundaries in the retina. Results obtained by this method present high accuracy and robustness, even when some of these layers are low defined or vessel shades are ...

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    1-17 of 17
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    Automatic Vessel Shade-Robust Segmentation of Retinal Layers in OCT Images Automatic Detection of Epiretinal Membrane in OCT Images by Means of Local Luminosity Patterns Automatic Detection of Blood Vessels in Retinal OCT Images (Book Chapter) Automatic Identification of Intraretinal Cystoid Regions in Optical Coherence Tomography Feature definition, analysis and selection for cystoid region characterization in Optical Coherence Tomography Automatic vessel detection by means of brightness profile characterization in OCT images Feature Definition and Selection for Epiretinal Membrane Characterization in Optical Coherence Tomography Images Optical Coherence Tomography Denoising by Means of a Fourier Butterworth Filter-Based Approach Automatic Identification of Macular Edema in Optical Coherence Tomography Images Intraretinal fluid identification via enhanced maps using optical coherence tomography images A case report of a coronary myocardial bridge with impaired full-cycle ratio during dobutamine challenge Diagnosis of chronic stage of hypertensive retinopathy based on spectral domain optical coherence tomography