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BEGIN:VEVENT
DTSTAMP:20260628T195542Z
DTSTART;VALUE=DATE-TIME:20080501T160000
DTEND;VALUE=DATE-TIME:20080501T170000
SUMMARY:SIP Seminar: Hans Knutsson
TZID:Europe/London
UID:20080501-094d43f01961145f01197bba718a08f1@warwick.ac.uk
CREATED:20080423T144026Z
DESCRIPTION:"The Morphon: A Robust Tool for Image Fusion and Segmentation
 " Hans Knutsson\, Linköpings Universitet\, Sweden Even though the histor
 y of image segmentation goes back to the very beginning of image process
 ing it is still a topic of major concern. Naive thresholding based appro
 aches are basically abandoned and the need to incorporate strong prior i
 nformation is hardly disputed. A-priori information in terms of allowabl
 e deformation of initial shapes has been frequently used in segmentation
  of 2D images and for tracking of deformable objects in video. Existing 
 deformable models are however sensitive to the initial conditions of the
  computation and often get trapped in local minima. In such cases intera
 ctive measures are paramount to attain successful results. For most user
 s interaction with the deformable model is complicated and non-intuitive
  and there is typically no means for user interaction during the process
 . The talk targets segmentation and\, to some extent\, fusion of medical
  data volumes. The approach is rather general and encompasses much of th
 e deformable model ideas that have evolved. Looking to achieve robustnes
 s as well as flexibility the approach aims for easy interactive incorpor
 ation of domain specific knowledge. The idea is to use a type of 'paint 
 on priors' interface to specify a Morphon model for a specific situation
 . This model volume describes the pertinent general characteristics\, su
 ch as shape\, object elasticity\, visual appearance etc\, of the object.
  These priors determine how the neighborhood will be perceived and how t
 his percept translates into a suggested new location. The model volume c
 an be seen as an elastic (N-dimensional) canvas which is deformed/morphe
 d to align with the data at hand\, hence the method name - The Morphon. 
 Initial tests in several different cases show promising results. Example
 s will be given of heart wall segmentation in ultrasound sequences and e
 xtraction of brain nerve fibre tracks. The latter involves a novel appro
 ach where the displacement field is computed through the inverse gradien
 t of a a rotational field holding the local difference in model and data
  orientation.
LOCATION:CS 1.01
CATEGORIES:
LAST-MODIFIED:20080423T144026Z
ORGANIZER;CN=Sara Kalvala:
END:VEVENT
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