Hélène Lajous - CIBM | Center for Biomedical Imaging Hélène Lajous - CIBM | Center for Biomedical Imaging

Helene

Hélène Lajous

Research Staff Scientist
SP CHUV-UNIL Computational Neuroanatomy & Fetal Imaging Section

Hélène is a post-doctoral researcher in the CHUV-UNIL Signal Processing Section of the CIBM. She graduated as a biomedical engineer from the National Polytechnic Institute of Grenoble (INPG, France) in 2013. She specialized in quantitative MR imaging (Clinatec, France) and approached the challenges of genetic imaging with a deep interest in neurosciences (NeuroSpin, France). In 2014, Hélène got involved in the Erasmus Mundus Joint Doctorate in Nanomedicine and Pharmaceutical Innovation (EMJD NanoFar) between the Research Center in Oncology and Immunology Nantes Angers (France) and the Center for Education and Research on Macromolecules (Belgium). During her PhD, she developed a multimodal macromolecular nanoplatform dedicated to the local treatment of glioblastoma. While evolving in a highly interdisciplinary context, she demonstrated a great adaptability and acquired a strong hands-on experience at the crossroads of medical imaging, pharmaceutical sciences, tumor biology and preclinical models. From 2015 to 2017, Hélène also taught various subjects related to her research at the Department for Biological Engineering of the University Institute of Technology of Angers (France). She graduated as a PhD in biomedical technologies in 2018. Passionate about the tremendous advancements achieved in MR imaging, Hélène envisions medical research as a collaborative and translational work that aims at addressing the true needs of physicians while considering the patients’ welfare. Since 2019, she has been working on quantitative MR imaging of the developing fetal brain for computer-assisted diagnosis in the Medical Image Analysis Laboratory (MIAL) headed by Dr. Meritxell Bach Cuadra.

KEYWORDS: Medical imaging, magnetic resonance imaging (MRI), fetal imaging, quantitative MRI (qMRI), contrast agents, neurosciences, computational neuroimaging