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Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?
(BMC, 2022)
[Abstract] Background
The health crisis resulting from the global COVID-19 pandemic highlighted more than ever the need for rapid, reliable and safe methods of diagnosis and monitoring of respiratory diseases. To study ...
Automatic Identification and Representation of the Cornea–Contact Lens Relationship Using AS-OCT Images
(MDPI AG, 2019-11-21)
[Abstract] The clinical study of the cornea–contact lens relationship is widely used in the process of adaptation of the scleral contact lens (SCL) to the ocular morphology of patients. In that sense, the measurement of ...
Automatic Identification and Intuitive Map Representation of the Epiretinal Membrane Presence in 3D OCT Volumes
(MDPI AG, 2019-11-29)
[Abstract] 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 ...
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 ...
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 ...
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 ...
Automatic Segmentation of Retinal Layers in Multiple Neurodegenerative Disorder Scenarios
(IEEE, 2023-11)
[Absctract]: Retinal Optical Coherence Tomography (OCT) allows the non-invasive direct observation of the central nervous system, enabling the measurement and extraction of biomarkers from neural tissue that can be helpful ...
Robust multi-view approaches for retinal layer segmentation in glaucoma patients via transfer learning
(AME Publishing, 2023-05-01)
[Absctract]: Background: Glaucoma is the leading global cause of irreversible blindness. Glaucoma patients experience a progressive deterioration of the retinal nervous tissues that begins with a loss of peripheral vision. ...