14 citations · 14 across the 2 of their papers we have counts for
5 papers
Zero-Shot Pediatric Tuberculosis Detection in Chest X-Rays using Self-Supervised Learning
Daniel Capellán-Martín, Abhijeet Parida, Juan J. Gómez-Valverde +5
Tuberculosis (TB) remains a significant global health challenge, with pediatric cases posing a major concern. The World Health Organization (WHO) advocates for chest X-rays (CXRs)…
DiCoM -- Diverse Concept Modeling towards Enhancing Generalizability in Chest X-Ray Studies
Abhijeet Parida, Daniel Capellan-Martin, Sara Atito +4
Chest X-Ray (CXR) is a widely used clinical imaging modality and has a pivotal role in the diagnosis and prognosis of various lung and heart related conditions. Conventional automa…
A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection
Daniel Capellán-Martín, Juan J. Gómez-Valverde, David Bermejo-Peláez +1
Tuberculosis (TB) is still recognized as one of the leading causes of death worldwide. Recent advances in deep learning (DL) have shown to enhance radiologists' ability to interpre…
Fetal MRI by robust deep generative prior reconstruction and diffeomorphic registration: application to gestational age prediction
Lucilio Cordero-Grande, Juan Enrique Ortuño-Fisac, Alena Uus +4
Magnetic resonance imaging of whole fetal body and placenta is limited by different sources of motion affecting the womb. Usual scanning techniques employ single-shot multi-slice s…
Computer Aided Detection for Pulmonary Embolism Challenge (CAD-PE)
Germán González, Daniel Jimenez-Carretero, Sara Rodríguez-López +17
Rationale: Computer aided detection (CAD) algorithms for Pulmonary Embolism (PE) algorithms have been shown to increase radiologists' sensitivity with a small increase in specifici…