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SUMMARY:Biological Image Analysis Made Easy - Fred Hamprecht (Heidelberg)
DTSTART:20120521T100000Z
DTEND:20120521T110000Z
UID:TALK33475@talks.cam.ac.uk
CONTACT:Florian Markowetz
DESCRIPTION:Biology has become a data-driven science. Much of the raw data
  now comes in the form of images\, creating a need for easy-to-use tools f
 or automated quantitative analysis.\n\nIn this talk\, I will describe and 
 demo our current best attempt at realizing such a tool: ilastik (http://il
 astik.org) is a convenient tool for image\nclassification and segmentation
  which requires no experience in image processing.\n\nThe interactive trai
 ning of a powerful classifier allows to distinguish an arbitrary number of
  classes (such as different tissue\, different organelles\,\netc) provided
  that these are distinguishable by local appearance. The program provides 
 real-time feedback of the current classifier predictions and thus\nallows 
 for targeted training and overall reduced labeling time. Once the classifi
 er has been trained on a representative subset of the data\, it can be\nus
 ed to automatically process a very large number of images. ilastik works o
 n gray value\, color or spectral images with up to three spatial dimension
 s.\n\nI will demo selected applications from high-throughput screening\, t
 he neurosciences and mass spectrometric imaging\, and be around to experim
 ent with\nimages supplied by the audience.\n\nilastik is open source and a
 vailable from http://ilastik.org
LOCATION:Cancer Research UK Cambridge Research Institute\, Lecture Theatre
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