Many different methods exist for the rendering and visualisation of 2D and 3D medical data (e.g. MRI), but few harness the possibilities of modern information workflows. The cloud rise, connected devices, immersive/augmented/web interfaces revolutionise the workplace, allowing increasing remote collaborative working and disappearance of individual storage. In the healthcare sector there is an increasing number of visualization and image processing platforms starting to move from desktop to web. Nevertheless, most advances are still in their infancy and translation to a the clinical environment far away. The recent affordable virtual/augmented reality systems, and software tools to easily develop interfaces, pave the way for multi-user immersive applications besides those by large labs. Within healthcare, educational, patient-family-doctor communication, intervention planning and follow-up/rehabilitation are ideal scenarios for them. 

The main goal of this project will be to research and develop immersive and web-based systems with clinician-friendly interfaces for a multi-user joint exploration of complex datasets related to several clinical applications, including multi-modal images, 3D anatomies and in silico simulations, for educational, patient-doctor communication and interventional planning purposes. As web-based graphics and visual analytics are relatively new fields, the research is both interesting and challenging. This project is strongly interdisciplinary, joining technical and biomedical expertise. The PhD candidate will be part of two research groups at UPF, the Interactive Technologies (GTI, led by Pr. J. Blat) and PhySense (led by Dr. O. Camara), with large experience on web-based computer graphics and clinical translation of computational tools, respectively. Research will be performed in collaboration with clinical and scientific partners (A. Gómez, King’s College London; I. Valverde, Hospital Virgen del Rocío; X. Freixa, Clínic de Barcelona).

JOB DESCRIPTION

The PhD candidate will work on different methodological aspects of the visualization and processing of large medical data, be tailored to several clinical applications. A first initial task will consist on adapting the web-based computer graphics tools available from the GTI research group to processing biomedical data. The primary question will concern how to visualize medical images and render meshes in a web context, with particular emphasis on: how to best display the different standard views in medical images; how to show different kinds of attributes depending on the data given; the level of interactivity of the user with the images and meshes. Secondly, several components will be explored to integrate some processing and visualization tools with a cloud storage platform and develop a web-based solution for the selection of medical data. Next, different virtual/augmented reality systems will be considered to develop immersive interfaces. Three possible applications will be targeted including educational, patient-doctor communication and treatment planning. As for the first one, a visualization interface will be developed with different degrees of complexity, from bachelor to medical school students. A similar interface will be required for patient-doctor communication, where augmented reality will firstly be studied so that face-to-face contact is not lost. Treatment planning interfaces will be the most advanced ones, including visualization of multimodal clinical data by several healthcare professionals at the same time.

UPF was established in 1990 as a public university with strong dedication to excellence in research and teaching. It is the 1st Spanish university in the world Top 200 (THE2020), the 11th (ranked 5th in Europe and 1st in Spain) under 50 years (THE18). It also ranked 5th in Europe and 1st in Spain (U-Multirank 2018) in teaching and research performance (U-Ranking, BBVA Foundation & Ivie, 2018), quality output (excellence rate), normalized impact and percentage of collaborative papers with foreign institutions. UPF is full member of the Big Data Value Association (BDVA). DTIC has since its creation emphasized scientific excellence and internationalisation as core aspects of its activities. It has an important track record of active participation in EU projects (a total of 66 FP7 projects and 10 other projects in non-FP7 program such as CIP, Ambient Assisted Living and the Lifelong Learning Program, and, up to now 44 H2020 projects). It is the Spanish university department with the largest number of ERC grants (9 FP7 and 9 H2020) and is part of the FET Flagship initiative “The Human Brain Project”. DTIC has been awarded the “María de Maeztu” excellence by the Spanish government for the quality and relevance of its pioneering scientific research.

BCN MedTech is the Barcelona Centre for New Medical Technologies at UPF. It focusses on biomedical integrative research, including mathematical and computational models, algorithms and systems for computer-aided diagnosis and treatment, and the translation thereof into relevant clinical problems and industrial products. It has a team of 60 full time researchers working on medical image and signal processing, computational simulation, computer-assisted surgery and biomedical electronics. Within BCN MedTech, the BMMB lab combines mechanistic and stochastic theoretical modelling with computational methods in biology and physics, to rationally explore the complex multiscale interactions between tissue multiphysics and biological processes, and to understand the bottom-up regulation of the functional biomechanics of organs in health and disease. The specific targets are cartilaginous (rheumatic disorders), bone (osteoporosis), arterial (atherosclerosis) and lung (emphysema) tissues. The project will combine this expertise with computational anatomy and manifold learning techniques for patient stratification, from the BCN MedTech medical image analysis and machine learning areas.