- José Vicente Manjón has been included on the list every year since 2020 in the category that measures scientific impact over the past year.
José Vicente Manjón, head of the Medical Image Analysis Lab (MIA-LAB) at the ITACA Institute of the Universitat Politècnica de València (UPV), has been included, for the seventh consecutive year, in the prestigious Ranking of the World Scientists: World’s Top 2% Scientists, the ranking linked to Stanford University, which identifies researchers with the greatest scientific impact in their respective disciplines.
The list distinguishes between cumulative impact over a researcher’s career and impact based on citations received in the most recent year analysed. Manjón falls into this second category, reflecting the international impact of his scientific publications.
His continued presence in this ranking since 2020 highlights the influence of his contributions to biomedical image processing
His continued presence in this ranking since 2020 highlights the influence of his contributions to biomedical image processing, a field that provides tools for studying the brain and advancing our understanding of neurological diseases.
«This recognition reflects our group’s effort and dedication to advancing biomedical image processing in order to improve our understanding of the development of the human brain and its application in the diagnosis of neurological diseases,» says José Vicente Manjón.
About the MIA-LAB-ITACA group
The MIA-LAB group, part of the ITACA-UPV Institute, specialises in the development of advanced technologies for biomedical image processing, with a particular focus on data obtained through brain magnetic resonance imaging.
«Our aim is to contribute to the progress of the field through innovative tools that enable tasks such as noise removal, super-resolution, data harmonisation, image synthesis, and automatic segmentation and classification,» explains Manjón.
The group combines the design of classical algorithms with the application of state-of-the-art deep learning methods. Furthermore, its research focuses on improving our understanding of conditions such as Alzheimer’s disease, multiple sclerosis and Parkinson’s disease, with the aim of optimising both diagnoses and potential treatments.