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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 ...
Retinal Microaneurysms Detection Using Adversarial Pre-training With Unlabeled Multimodal Images
(Elsevier, 2022)
[Abstract] The detection of retinal microaneurysms is crucial for the early detection of important diseases such as diabetic retinopathy. However, the detection of these lesions in retinography, the most widely available ...
Fully Automatic Deep Convolutional Approaches for the Analysis of COVID-19 Using Chest X-Ray Images
(Elsevier, 2022)
[Abstract] Covid-19 is a new infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the seriousness of the situation, the World Health Organization declared a global pandemic as ...
Repeatability of choriocapillaris flow voids by optical coherence tomography angiography in central serous chorioretinopathy
(Public Library of Science, 2022-12-16)
[Abstract]: Purpose: To assess the repeatability of flow signal voids (FSV) measurements of the choriocapillaris (CC) and choroid (CH) in central serous chorioretinopathy (CSCR) by Swept-Source optical coherence tomography ...
Multimodal Image Encoding Pre-training for Diabetic Retinopathy Grading
(Elsevier, 2022)
[Abstract] Diabetic retinopathy is an increasingly prevalent eye disorder that can lead to severe vision impairment. The severity grading of the disease using retinal images is key to provide an adequate treatment. However, ...
End-To-End Multi-Task Learning Approaches for the Joint Epiretinal Membrane Segmentation and Screening in OCT Images
(Elsevier, 2022)
[Abstract] Background and objectives The Epiretinal Membrane (ERM) is an ocular disease that can cause visual distortions and irreversible vision loss. Patient sight preservation relies on an early diagnosis and on determining ...
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 ...
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 ...