My research career started in Barcelona working on quantification and image noise characterization in Electrical Impedance Tomography. I learned during this period that ill-posedness in image acquisition and formation cannot be overcome latter on with imaginative image analysis methods ("garbish in, garbish out") and that as an image analysis expert you cannot overlook or ignore the physics image formation. 

After two years of research in EIT I moved to 3D image processing of angiographic and cardiac images. I learned in Utrecht a lot about multiscale image analysis, image registration, deformable models and statistical shape modelling. One of the key lessons I learned is that image analysis is inherently application-specific and, hence, the aim of developing generic tools in image analysis is, in my experience, an impossible mission. However, if one focuses on specific clinical questions, the emerging challenges for image analysis become focused and inspire principled algorithmic contributions that are even more challenging and  attractive that the quest for one-fit-all solutions.

I then moved to Zargoza and subsequently back to Barcelona. During all these years, I got excited for the research and translation potential at the intersection of medical imaging, image computing and computational physiology. One that can contribute to healthcare by endowing with a predictive angle to medical imaging, that could leverage experience and techniques from medical image computing, and that could help to personalise computational physiology models. I was inspired by the vision behind the IUPS Physiome Project and later on became a key contributor to the Virtual Physiological Human initiative in Europe, which had its seminal meeting in Barcelona back in 2005. The work in this area is truly exciting, interdisciplinary, full of scientific challenges and transformational impact for healthcare.

I moved in 2011 to the UK an was based till 2018 in Sheffield, were I was particularly interested in applications of computational imaging and computational physiology for developing image-based computational models of the cardiovascular, neurological and musculoskeletal systems and their interactions with medical devices and other forms of treatments. In particular, I was then interested in minimally invasive interventional planning and guidance. My interest in imaging broaden to wider physiological sensing as pervasive sensing techniques promise to introduce further elements to personalised physiological modelling as those connected to lifestyle, biorhythms and environmental factors.

I am currently at the University of Leeds with joint appointments at the School of Computing and the School of Medicine. My goal in the next 10 years is to bring the previous experience to the clinic through even more translational research than before and with an eye on commercialisation and industrial take up, which go hand in hand with achieving clinical impact. Not surprisingly, this may simultaneously require more and focused basic research. My current joint affiliation in Computing and Medicine and the broader MedTech context in Leeds give me an ideal context to deliver. See, for instance: Medical Technologies and Translate programs.

Here a list of topics in which I have been involved in the last years:

  • Noise propagation in EIT reconstruction algorithm
  • Pattern recognition based on statistical classifiers and neural networks
  • Geometric modelling of anatomical structures
  • Multi-scale image analysis
  • Model-based image segmentation
  • Statistical shape modelling
  • Image registration based on information theory
  • Non-rigid diffeomorphic registration
  • Image-based tissue elastography
  • Image-based computational fluid dynamics
  • Image-based cardiac electro mechanics
  • Image-based bone biomechanics

For a full list of the projects in which I am or was involved have a look at