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Intraretinal Fluid Pattern Characterization in Optical Coherence Tomography Images
(MDPI AG, 2020-04-03)
[Abstract] 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 ...
Fully Automatic Retinal Vascular Tortuosity Assessment Integrating Domain-Related Information
(MDPI AG, 2020-08-21)
[Abstract]
The fundus of the eye is the only part of the human body that allows a direct non-invasive observation of the circulatory system. Retinal vascular tortuosity presents a valuable potential for diagnostic and ...
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 ...
COVID-19 Lung Radiography Segmentation by Means of Multiphase Transfer Learning
(MDPI, 2021)
[Abstract] COVID-19 is characterized by its impact on the respiratory system and, during the global outbreak of 2020, specific protocols had to be designed to contain its spread within hospitals. This required the use of ...
Portable Chest X-ray Synthetic Image Generation for the COVID-19 Screening
(MDPI, 2021)
[Abstract] The global pandemic of COVID-19 raises the importance of having fast and reliable methods to perform an early detection and to visualize the evolution of the disease in every patient, which can be assessed with ...