Difference between revisions of "2017 Winter Project Week/Diffusely abnormal white matter segmentation with 3d U-net"

From NAMIC Wiki
Jump to: navigation, search
Line 16: Line 16:
 
|
 
|
 
<!-- Objective bullet points -->
 
<!-- Objective bullet points -->
* Develop the client side as a Slicer extension.
+
* Develope an automated system that accurately segments diffusely abnormal white matter
* Develop the server side.
 
* Train a diabetic retinopathy classifier and add the model to the DeepInfer model repository.
 
 
|
 
|
 
<!-- Approach and Plan bullet points -->
 
<!-- Approach and Plan bullet points -->
*
+
* We would like to use the 3D unet that is shown to be a great architecture for biomedical image segmentation.
 
|
 
|
 
<!-- Progress and Next steps bullet points (fill out at the end of project week) -->
 
<!-- Progress and Next steps bullet points (fill out at the end of project week) -->
 
*
 
*
 
|}
 
|}

Revision as of 23:33, 6 January 2017

Home < 2017 Winter Project Week < Diffusely abnormal white matter segmentation with 3d U-net

Key Investigators

  • Mohsen Ghafoorian (BWH, Radboud University)
  • Bram Platel (Radboud University)
  • Sandy Wells (BWH)
  • Tina Kapur (BWH)
  • Sandy Wells (BWH)


Project Description

Objective Approach and Plan Progress and Next Steps
  • Develope an automated system that accurately segments diffusely abnormal white matter
  • We would like to use the 3D unet that is shown to be a great architecture for biomedical image segmentation.