107 citations · 163 across the 6 of their papers we have counts for
4 papers · 1 filter
Few-shot learning for COVID-19 Chest X-Ray Classification with Imbalanced Data: An Inter vs. Intra Domain Study
Alejandro Galán-Cuenca, Antonio Javier Gallego, Marcelo Saval-Calvo +1
Medical image datasets are essential for training models used in computer-aided diagnosis, treatment planning, and medical research. However, some challenges are associated with th…
UMLS-ChestNet: A deep convolutional neural network for radiological findings, differential diagnoses and localizations of COVID-19 in chest x-rays
Germán González, Aurelia Bustos, José María Salinas +7
In this work we present a method for the detection of radiological findings, their location and differential diagnoses from chest x-rays. Unlike prior works that focus on the detec…
BIMCV COVID-19+: a large annotated dataset of RX and CT images from COVID-19 patients
Maria de la Iglesia Vayá, Jose Manuel Saborit, Joaquim Angel Montell +10
This paper describes BIMCV COVID-19+, a large dataset from the Valencian Region Medical ImageBank (BIMCV) containing chest X-ray images CXR (CR, DX) and computed tomography (CT) im…
PadChest: A large chest x-ray image dataset with multi-label annotated reports
Aurelia Bustos, Antonio Pertusa, Jose-Maria Salinas +1
We present a labeled large-scale, high resolution chest x-ray dataset for the automated exploration of medical images along with their associated reports. This dataset includes mor…