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SUMMARY:Accelerating localisation microscopy - Susan Cox\, Department of B
 iology\, King's College London
DTSTART:20131025T130000Z
DTEND:20131025T140000Z
UID:TALK47955@talks.cam.ac.uk
CONTACT:Alessio Zaccone
DESCRIPTION:Localisation microscopy is a powerful tool for imaging structu
 res at a\nlengthscale of tens of nm\, but its utility for live cell imagin
 g is limited\nby the time it takes to acquire the data needed for a super-
 resolution\nimage. The acquisition time can be cut by more than two orders
  of magnitude\nby using advanced algorithms which can analyse dense data\,
  trading off\nacquisition and processing time. We have developed two metho
 ds which allow\ndifferent tradeoffs to be made.\nModelling the entire loca
 lisation microscopy dataset using a Hidden Markov\nModel allows localisati
 on information to be extracted from extremely dense\ndatasets. This Bayesi
 an analysis of blinking and bleaching (3B) is able to\nimage dynamic proce
 sses in live cells at a timescale of a few seconds\,\nthough it is very co
 mputationally intensive\, requiring at least several\nhours of analysis.\n
 \nAnalysis speed can be improved over 3B by a factor of ten by instead\nmo
 delling the data using an alternative statistical approach\, which\nautoma
 tically determines the number\, position\, and brightness of\nfluorescing 
 molecules within a particular image region. This method treats\nthe backgr
 ound noise as a parameter to be found\, avoiding the background\nremoval s
 tep in 3B or the need to hand set thresholds in more conventional\nanalysi
 s techniques.\n\nOur methods are demonstrated on various live cell systems
 \, including\ncardiac myocytes and podosomes\, showing a resolution of ten
 s of nm with\nacquisition times down to a second. We also compare our meth
 ods to other\nhigh density algorithms and discuss the artefacts which can 
 occur during\nreconstruction of the super-resolution image.
LOCATION:Small Lecture Theatre\, Cavendish Laboratory
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