• Olivier Salvado
  • CSIRO

Curriculum Vitae

Education

MBA Australian Graduate School of Management, University of New South Wales, Sydney , Australia
PhD Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
MSEE ESIEE Paris, France

Professional Experience

CSIRO - Group leader Biomedical Informatics (2012- )
CSIRO - Team leader Medical Imaging (2007-2012)
University hospitals of Cleveland, Instructor of Radiology (2006-2007)

Research Interests

Medical Imaging, Machine Learning, Biomedical Engineering, Deep Learning, Clinical studies, Genomics, Biostatistics
Innovation, research management

Honors & Awards

Publications

Abstract

Machine Learning applied to medical imaging for quantitative phenotyping of neurodegeneration and brain disorders

New medical imaging technologies are offering increasingly detailed information about the structure, function, and composition of the brain. Specifically, Magnetic Resonance Imaging (MRI) and Positron Emission tomography (PET) are now used routinely in clinical reasearch studies with accelerating translation to clinical practice as their value becomes evident for neurodegeneration and the assesment of co-morbidities’ associated with ageing. However, 3D scans from MRI and PET are rich in information but are tedious to visually qualify. Advances in machine learning techniques are making great progress into quantifying clinically relevant information and presenting the results in a clinically relevant way. This includes reporting normative measures that take into account demographics and other personal and clinical variables. This talk will present some new techniques to quantify Amyloid, Tau, and glucose metabolism from PET as well as morphometry, white matter lesions, perfusion, microbleeds and connectivity from MRI. A delivery model using a cloud computing platofrom will be presented allowing researchers and clinicians to evaluate imaging biomarker reports and provide a test bed for commercialisaiton effort.