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Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies
(M D P I AG, 2019-10-31)
[Abstract] Optical Coherence Tomography Angiography (OCTA) constitutes a new non-invasive ophthalmic image modality that allows the precise visualization of the micro-retinal vascularity that is commonly used to analyze ...
Image-to-image translation with Generative Adversarial Networks via retinal masks for realistic Optical Coherence Tomography imaging of Diabetic Macular Edema disorders
(Elsevier, 2023)
[Abstract]: One of the main issues with deep learning is the need of a significant number of samples. We intend to address this problem in the field of Optical Coherence Tomography (OCT), specifically in the context of ...
Feature Definition and Comprehensive Analysis on the Robust Identification of Intraretinal Cystoid Regions Using Optical Coherence Tomography Images
(Springer, 2022)
[Abstract] 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 ...
End-To-End Multi-Task Learning for Simultaneous Optic Disc and Cup Segmentation and Glaucoma Classification in Eye Fundus Images
(Elsevier, 2022)
[Abstract] The automated analysis of eye fundus images is crucial towards facilitating the screening and early diagnosis of glaucoma. Nowadays, there are two common alternatives for the diagnosis of this disease using deep ...
Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models
(Elsevier, 2023-07)
[Abstract]: COVID-19 is a global threat for the healthcare systems due to the rapid spread of the pathogen that causes it.
In such situation, the clinicians must take important decisions, in an environment where medical ...
Unsupervised contrastive unpaired image generation approach for improving tuberculosis screening using chest X-ray images
(Elsevier, 2022-12)
[Abstract]: Tuberculosis is an infectious disease that mainly affects the lung tissues. Therefore, chest X-ray imaging can be very useful to diagnose and to understand the evolution of the pathology. This image modality ...
Fully automatic segmentation of the choroid in non-EDI OCT images of patients with multiple sclerosis
(Elsevier, 2022)
[Abstract]: Multiple Sclerosis (MS) is a chronic neurological disease, in which immune-mediated mechanisms lead to pathological processes of neurodegeneration. Optical coherence tomography (OCT) has recently begun to be ...
Deep feature analysis in a transfer learning approach for the automatic COVID-19 screening using chest X-ray images
(Elsevier B.V., 2023)
[Abstract]: COVID-19 is a challenging disease that was declared as global pandemic in March 2020. As the main impact of this disease is located in the pulmonary regions, chest X-ray devices are very useful to understand ...
Explainable learning to analyze the outcome of COVID-19 patients using clinical data
(Elsevier B.V., 2023)
[Abstract]: Patients at high risk of contracting COVID-19 require specialized monitoring throughout their illness to ensure optimal treatment at each stage. To support this monitoring, Computer-Aided Diagnosis (CAD) methods ...
Impact of the Region of Analysis on the Performance of the Automatic Epiretinal Membrane Segmentation in OCT Images
(Springer, 2023-02-10)
[Absctract]: The Epiretinal Membrane (ERM) is an ocular pathology that can cause permanent visual loss if left untreated for long. Despite its transparency, it is possible to visualise the ERM in Optical Coherence Tomography ...