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DTSTAMP:20250804T095554Z
DESCRIPTION:Model-based imaging and image-based modelling\n\nDaniel Alexand
 er\, University College London\n	Tuesday March 23\, 12-1pm\n	Zoom Link: http
 s:/mcgill.zoom.us/j/91589192037\n\nAbstract: My talk will cover three curr
 ent research topics. 1. Microstructure imaging\, which uses mathematical o
 r computational modelling and machine learning to estimate and map microst
 ructural features of tissue from MRI\; see (Alexander NMR Biomed 2019) for
  a review. Examples from my group’s work include NODDI (Zhang et al Neuroi
 mage 2012) for brain imaging and VERDICT (Panagiotaki et al Cancer Researc
 h 2014) for cancer imaging. I will describe moves towards a new paradigm c
 ombining multi-contrast measurements through sophisticated computational m
 odels exploiting machine learning. 2. Data-driven disease progression mode
 ls (e.g. Fonteijn et al Neuroimage 2012\; Young et al Brain 2014\; Lorenzi
  et al Neuroimage 2017)\, which aim to piece together longitudinal picture
 s of disease from cross-sectional or short-term longitudinal data sets and
  thus gain new disease understanding\, stratification systems\, and predic
 tive power. The Subtype and Stage Inference (SuStaIn - Young et al Nature 
 Comms 2018) algorithm extends the idea to identify disease subgroups defin
 ed by distinct longitudinal trajectories of change. Most recently we are e
 xploiting these models to make inferences about underlying spreading mecha
 nisms in neurodegeneration (Garbarino et al eLife 2019). 3. Image Quality 
 Transfer (Alexander et al Neuroimage 2017\; Tanno et al Neuroimage 2020)\,
  which uses machine learning to estimate a high quality image\, e.g. that 
 we would have acquired from a one-off super-powered scanner\, from a lower
  quality image\, e.g. acquired on a standard hospital scanner.\n
DTSTART:20210323T160000Z
DTEND:20210323T170000Z
LOCATION:CA\, QC
SUMMARY:QLS Seminar Series - Daniel Alexander
URL:/qls/channels/event/qls-seminar-series-daniel-alex
 ander-329243
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