Difference between revisions of "2011 Winter Project Week:SegEye"

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*We segmented the eye ball.
 
*We segmented the eye ball.
 
*Experiments:
 
*Experiments:
VMTK Modules in Slicer for optic nerve segmentation.
+
#VMTK Modules in Slicer for optic nerve segmentation.
The particle filtering based approach for nerve segmentation.
+
#The particle filtering based approach for nerve segmentation.
Ellipse constrained segmentation of optic lens.
+
#Ellipse constrained segmentation of optic lens.
*Received a number of suggestions for future experiments:
+
 
#Incorporate constraints on Hounsfield units for segmentation of CT imagery.
+
*There remain a number of future experiments:
#Use atlas for more robust localization of eye ball.
+
#Incorporate constraints on Hounsfield units for segmentation of CT imagery.
#Add prior anatomical knowledge for optic nerve segmentation (surrounding bone easily visible).
+
#Use atlas for more robust localization of eye ball.
 +
#Add prior anatomical knowledge for optic nerve segmentation (surrounding bone easily visible).
  
  

Latest revision as of 23:47, 13 January 2011

Home < 2011 Winter Project Week:SegEye


Segmentation of the eye ball.
Axial view of the eye ball segmentation.


Key Investigators

  • Georgia Tech: Ivan Kolesov and Allen Tannenbaum
  • MGH: Gregory Sharp

Objective

  • We are interested in segmenting the eye ball, lens, optic nerve, and the optic chiasm.
  • Anatomical structures are highly sensitive to radiation.
  • We are creating a framework to perform these segmentations, which is likely to require a different approach for each structures due to the proximity of multiple structures to each other.

Approach

  • The eye ball is considered to be the pivotal organ since its segmentation will localize the region of interest when looking for other structures.
  • We will reduce the dimensionality of this problem by performing model based segmentation for each structure.
  • Once the eye is segmented, we use this knowledge to locate the lens/ initialize optic nerve segmentation.
  • We would like to leverage the information provided by a CT scan with additional data from an MRI -- we have to consider this registration problem.



Progress

  • We segmented the eye ball.
  • Experiments:
  1. VMTK Modules in Slicer for optic nerve segmentation.
  2. The particle filtering based approach for nerve segmentation.
  3. Ellipse constrained segmentation of optic lens.
  • There remain a number of future experiments:
  1. Incorporate constraints on Hounsfield units for segmentation of CT imagery.
  2. Use atlas for more robust localization of eye ball.
  3. Add prior anatomical knowledge for optic nerve segmentation (surrounding bone easily visible).