Dr Jose Bernal Moyano
Jose was a PhD student on the Precision Medicine programme, based at the Centre for Clinical Brain Sciences of The University of Edinburgh. Jose graduated with merits as BSc in Computer Engineering from the Universidad del Valle in 2014 (best Computer Engineer graduate in 2014; meritorious final career project). A year after, he was awarded an Erasmus Mundus Joint Master Degree Programme scholarship to complete his MSc studies in Computer Vision and Robotics from the Heriot-Watt University (HWU), Universitat de Girona and Université de Bourgogne (UoB). He completed the programme with merits in 2017 (best master thesis 2017; graduation with distinction from HWU; mention très bien from UoB).
Jose has worked previously on artificial intelligence for tissue segmentation and atrophy quantification in brain magnetic resonance imaging at the Universitat de Girona. His PhD project investigated whether image and signal processing tools can compensate for MR imaging artefacts without dispensing with clinically relevant information. His primary goal is to develop a framework for assessing the pertinence of established and novel MRI artefact reduction methods on synthetic and real data to the study of small vessel disease. Up until now, he has co-authored 45 publications in peer-reviewed scientific journals/book chapters and presented his work in national and international conferences. While working at The University of Edinburgh SVD Research, he was also a successful author of datasets.
Upon successfully defending his PhD thesis, Dr Bernal has now moved onto a new role as a Postdoctoral position at the DZNE Magdeburg (Germany), investigating the role of lifestyle factors on MR-based biomarkers of brain health function.
Key publications
Bernal et al (2021) "A four-dimensional computational model of dynamic contrast-enhanced magnetic resonance imaging measurement of subtle blood-brain barrier leakage." NeuroImage (2021): 117786.
Publication link: pubmed.ncbi.nlm.nih.gov/33497771/
Bernal et al (2020) "A Framework for Jointly Assessing and Reducing Imaging Artefacts Automatically Using Texture Analysis and Total Variation Optimisation for Improving Perivascular Spaces Quantification in Brain Magnetic Resonance Imaging." Annual Conference on Medical Image Understanding and Analysis. Springer, Cham.
Publication link: https://link.springer.com/chapter/10.1007/978-3-030-52791-4_14
Datasets
Systematic review of signal post-processing methods in blood-brain barrier dysfunction assessments via dynamic-contrast enhanced magnetic resonance imaging [publicly available dataset].
Link: Dataset in Datashare
Related links
Jose Bernal Moyano profile at The University of Edinburgh website
