Name: Roxane Licandro
Affiliation:
1.) Medical University of Vienna
Department of Biomedical Imaging and Image-guided Therapy
Computational Imaging Research Lab (CIR)
2.) Massachusetts General Hospital/ Harvard Medical School
Athinoula A. Martinos Center for Biomedical Imaging
Laboratory for Computational Neuroimaging
Primary research interest: Medical Image Analysis, Spatio Temporal Modelling, Statistical Pattern Analysis
Title of the lecture: Machine Learning for Medical Imaging – Spatio Temporal Analysis of the Developing Brain
Keywords: fetal and infant brain atlas, deep learning for prediction, functional image reconstruction, brain shape analysis, graph-based analysis
Summary: This talk gives a brief introduction to machine learning concepts for medical image-segmentation, -reconstruction, -registration and –prediction and we will discuss the challenges that deep learning approaches face in the medical field. The second part of the talk focuses on machine learning approaches that are used to analyze the developing brain of fetuses, infants and children. An overview will be given how functional and structural development of the brain can be assessed using graph-based analysis, how brain shape changes can be encoded in a spatio temporal model and how we can reconstruct motion corrupted fetal brain images .