Radiology Data Quantification

Radiological images provide a non invasive way to study different diseases. Providing automatic tools for the quantification of radiology markers or characteristics can help on different clinically relevant endoinds such as screening, diagnosis or even prognosis assisting radiologists during their clinical practice. Within this research axis we have proposed a number of deep learning models for the detection and quantification of lung pneumonias from CT scans.

Related Publications

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia
AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia

MedIA 2021
Semantic Segmentation of Pathological Lung Tissue with Dilated Fully Convolutional Networks
Semantic Segmentation of Pathological Lung Tissue with Dilated Fully Convolutional Networks

IEEE-JBHI 2018
Lung pattern classification for interstitial lung diseases using a deep convolutional neural network
Lung pattern classification for interstitial lung diseases using a deep convolutional neural network

IEEE-TMI 2016