BioMedIA Talk: Matthan Caan (Academic Medical Centre & Spinoza Centre for Neuroimaging, Amsterdam)
2017-02-22 12:00 - 13:00 UTC
Quantifying MRI: from reconstruction to application in neuroimaging
Abstract: To understand the origin and development of neurological disorders, Magnetic Resonance Imaging (MRI) has proven to provide valuable quantitative measures. In this overview presentation, I will touch upon several topics. Volumetric measures obtained via segmentation find their application in prenatal famine exposure, HIV and ischemic stroke. We developed a scattering transform that has no learnable parameters for computing convolutional neural networks in small patient studies. Diffusion MRI is a sensitive method for detecting microstructural changes. We assessed the reproducibility of different models in a multi-site context using a complex diffusion phantom. T1, T2* and Quantitative Susceptibility Mapping (QSM) allow for mapping myelin and iron content at high resolution at 7T. We present a single MRI sequence for obtaining these measures in a time efficient manner. Further acceleration may be achieved by compressed sensing and potentially deep learning.

BioMedIA Talk: Loic Le Folgoc (Microsoft Research)
2017-08-29 12:00 - 13:00
Title: Learning structure in complex data: machine learning for medical image segmentation, registration and shape analysis

BioMedIA Talk: Polina Golland (MIT CSAIL)
2017-09-28 11:00 - 12:00
Title: MRI of placenta: from pixels to function
