Manuel G. Penedo

A new generative approach for optical coherence tomography data scarcity: unpaired mutual conversion between scanning presets

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In optical coherence tomography (OCT), there is a trade-off between the scanning time and image quality, leading to a scarcity of high quality data. OCT platforms provide different scanning presets, producing visually distinct images, limiting their compatibility. In this work, a fully automatic methodology for the unpaired visual conversion of the two most prevalent scanning presets is proposed. Using contrastive unpaired translation generative adversarial architectures, low quality images acquired with the faster Macular Cube preset can be converted to the visual style of high visibility Seven Lines scans and vice-versa. This modifies the visual appearance of the OCT images generated by each preset while preserving natural tissue structure. The quality of original and synthetic generated images was compared using BRISQUE. The synthetic generated images achieved very similar scores to original images of their target preset. The generative models were validated in automatic and expe...

Choroid segmentation in non-EDI OCT images of multiple sclerosis patients

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Optical coherence tomography (OCT) is a non-invasive diagnostic technique that can image ocular structures. Recently, this imaging technique has been used to diagnose and monitor patients with multiple sclerosis (MS), as several clinical studies have linked the development of MS to various changes in the eye. Among the different structures, one of the relevant biomarkers for MS analysis is the choroid. Systems such as Enhanced Depth Imaging (EDI) provide detailed images of the choroid region. However, OCT images are not routinely captured using this technology unless the study is specifically focused on choroidal analysis. In this work we propose a robust approach, based on convolutional neural networks to segment the choroid in non-EDI OCT images. The results obtained show that the proposed network manages to delimit the inferior contour of the choroid in a similar way to the experts. ( Read Full Article )

Feature definition and comprehensive analysis on the robust identification of intraretinal cystoid regions using optical coherence tomography images

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Currently, optical coherence tomography is one of the most used medical imaging modalities, offering cross-sectional representations of the studied tissues. This image modality is specially relevant for the analysis of the retina, since it is the internal part of the human body that allows an almost direct examination without invasive techniques. One of the most representative cases of use of this medical imaging modality is for the identification and characterization of intraretinal fluid accumulations, critical for the diagnosis of one of the main causes of blindness in developed countries: the Diabetic Macular Edema. The study of these fluid accumulations is particularly interesting, both from the point of view of pattern recognition and from the different branches of health sciences. As these fluid accumulations are intermingled with retinal tissues, they present numerous variants according to their severity, and change their appearance depending on the configuration of the devi...

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

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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 diseases like the diabetic macular edema and the age-related macular degeneration, which cause fluid leakages between the retinal layers. Both these diseases are among the main causes of blindness in developed countries, as these leakages tear the retinal structure and provoke the formation of other pathological bodies. As the symptoms start to be noticeable only when they cause a severe amount...

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

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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 distribution, complications and/or other artifacts that may complicate the identification process. ( Read Full Article )

Intraretinal Fluid Pattern Characterization in Optical Coherence Tomography Images

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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. The methodology validation and the analysis were performed using an image dataset of 83 OCT scans. From these images, 1609 samples were extracted from both cystoid and non-cystoid regions. The different tested configurations provided satisfactory results, reaching a mean cr...

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

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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 the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we ...

Intraretinal fluid identification via enhanced maps using optical coherence tomography images

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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 achieve this, a set of 312 intensity and texture-based features were studied. The most relevant features were selected using the sequential forward selection (SFS) strategy and tested with three archetypal classifiers: LDC, SVM and Parzen window. Finally, the most proficient classifier is used to create the proposed m...

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

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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 us optimize the discrimination of both cathegories that is used, finally, to identify the vessel locations. The proposed method was adjusted and validated using 256 OCT images, including 1274 vascular structures that were labelled by an expert clinician. Satisfactory ...

Automatic Identification of Intraretinal Cystoid Regions in Optical Coherence Tomography

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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 automatic identification of intraretinal cystoid fluid regions in OCT images. Firstly, the method identifies the Inner Limitant Membrane (ILM) and Retinal Pigment Epithelium (RPE) layers that delimit the region of interest where the intraretinal cystoid regions are placed. Inside these limits, the method analyzes windows of a given size an...

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

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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 present. ( Read Full Article )

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