Every year Inria@SiliconValley launches a call for Post-Doc Fellowships.
After a tough competition, we are please to congratulate Nina Miolane and Ziran Zhang who have been selected.
“Geometric Hierarchical Model of the Brain Anatomy”
Computational Medicine is a dynamic field experiencing an exponential growth. As an example, the cloud computing market for medical images is estimated at $400 millions for 2018 in the United States. This represents a 27% increase in ten years. Likewise, ”Medtech” – a term refering to technology for health care – is now a ”buzzword”: its web-based researches have increased by 20% since 2010. The transfer of medical imaging technology to industry and to the hospital is at the heart of this societal revolution.
The computational tools are especially important when it comes to neuroimaging. Brain images are produced every day in hospitals and show large anatomical variability. On the brain’s surface, for example, the distribution of folding patterns varies significantly from a healthy subject to another. Because of this complexity, the brain images are difficult to analyze. The clinician often extracts only visual qualitative information or quantitative information restricted to one dimension, for example a distance on a slice. Medicine needs computational tools that model the whole brain anatomy with its variability. This is required for a better understanding of the healthy and pathological brain variability. Associated to neuroimaging studies, it will improve our knowledge of diseases like Alzheimer or Parkinson for applications in hospitals. The postdoc research focuses on modeling the brain anatomical variability with a geometric hierarchical model.