My research is focused on Machine Learning and Deep Learning for Medical Image Analysis. I develop AI algorithms that help clinicians detect diseases faster and more accurately from medical images such as CT, MRI, and X-Ray.

Research Interests

  • Deep Learning for Medical Image Segmentation
  • Uncertainty Estimation in Deep Learning
  • Domain Adaptation and Transfer Learning
  • Federated Learning for Medical Imaging
  • Generative Models for Data Augmentation

Projects

EuCanImage

Horizon 2020 funded European project for building a cancer imaging platform.

Read more →

EVOLUTION

Predictive models for multiple sclerosis using brain magnetic resonance imaging biomarkers.

Read more →

wASSABI

Automatic brain Structures Segmentation As potential imaging BIomarkers.

Read more →

biomarkEM.cat

Development of novel techniques for the improvement in the medical image processing and analysis field.

Read more →

NICOLE

New technologies applied to clinical practice for obtaining biomarkers of atrophy and lesions in MRI of patients with multiple sclerosis.

Read more →