204 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Universitat de BarcelonaES3 papers
- University College LondonGB3 papers
- Hospital de Sant PauES2 papers
- Institució Catalana de Recerca i Estudis AvançatsES2 papers
- King's College LondonGB2 papers
- Universitat Pompeu FabraES2 papers
- Amsterdam NeuroscienceNL1 paper
- Amsterdam Public HealthNL1 paper
- Amsterdam University Medical CentersNL1 paper
- Centre d'Esclerosi Múltiple de CatalunyaES1 paper
- Centre Eugène MarquisFR1 paper
- Centre Tecnologic de Telecomunicacions de CatalunyaES1 paper
8 papers
Adaptive Plane Reformatting for 4D Flow MRI using Deep Reinforcement Learning
Javier Bisbal, Julio Sotelo, Maria I Valdés +7
Background and Objective: Plane reformatting for four-dimensional phase contrast MRI (4D flow MRI) is time-consuming and prone to inter-observer variability, which limits fast card…
Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results
Meritxell Riera-Marin, Sikha O K, Julia Rodriguez-Comas +29
Deep learning (DL) has become the dominant approach for medical image segmentation, yet ensuring the reliability and clinical applicability of these models requires addressing key…
Expanding the deep-learning model to diagnosis LVNC: Limitations and trade-offs
Gregorio Bernabé, Pilar González-Férez, José M. García +2
Hyper-trabeculation or non-compaction in the left ventricle of the myocardium (LVNC) is a recently classified form of cardiomyopathy. Several methods have been proposed to quantify…
Progressive Subsampling for Oversampled Data - Application to Quantitative MRI
Stefano B. Blumberg, Hongxiang Lin, Francesco Grussu +3
We present PROSUB: PROgressive SUBsampling, a deep learning based, automated methodology that subsamples an oversampled data set (e.g. multi-channeled 3D images) with minimal loss…
Domain generalization in deep learning for contrast-enhanced imaging
Carla Sendra-Balcells, Víctor M. Campello, Carlos Martín-Isla +5
The domain generalization problem has been widely investigated in deep learning for non-contrast imaging over the last years, but it received limited attention for contrast-enhance…
Detection, growth quantification and malignancy prediction of pulmonary nodules using deep convolutional networks in follow-up CT scans
Xavier Rafael-Palou, Anton Aubanell, Mario Ceresa +3
We address the problem of supporting radiologists in the longitudinal management of lung cancer. Therefore, we proposed a deep learning pipeline, composed of four stages that compl…
Using smartphones and wearable devices to monitor behavioural changes during COVID-19
Shaoxiong Sun, Amos Folarin, Yatharth Ranjan +23
We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiti…
Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach
Sergi Valverde, Mariano Cabezas, Eloy Roura +7
In this paper, we present a novel automated method for White Matter (WM) lesion segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a cascade of two 3D…