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Slicer On Demand
Key Investigators
  - Steve Pieper (Isomics, Inc. Cambridge MA, USA)
 
  - Curt Lisle (Knowledgevis, Maitland, Florida, USA)
 
  - Andrey Fedorov (BWH, Boston, MA, USA)
 
  - Theodore Aptekarev (Independent, Moscow, Russia)
 
Project Description
The goal is to allow people to quickly transition from viewing images to doing more complex tasks such as segmentation or registration.
Objective
  - A quick and easy way to get a functioning Slicer environment
 
  - Ability to browse data, e.g. in IDC, and load same data in cloud-hosted Slicer
 
  - Pass login credentials from web to Slicer to allow load/save of confidential data
 
Approach and Plan
  - Build on existing SlicerMachines GCP boot images
 
  - Prototype using the IDC sandbox that already supports login
 
  - Use GCP JavaScript API to launch and monitor jobs
 
Progress and Next Steps
  - Steve implemented one-click creation of a VM using the Google API to launch a GPU-enabled VM, ready to use within about 90 seconds.
 
  - Theodore created workflow icons to provide visual feedback during the launch process.
 
  - We met and discussed methods for encrypting traffic to the “pop up” Slicer-in-the-cloud using Google Cloud infrastructure options.
 
  - A use case was identified where an IDC cohort manifest could be passed to the Slicer VM and the cohort could be automatically loaded for the user.
 
  - We had a discussion with Kitware regarding the composition of the Slicer Docker containers: It would be nice to consolidate dockerfile of general use into https://github.com/Slicer/SlicerDocker
 
  - Next Steps:
    
      - Evaluate tradeoffs between simplicity of interface and exposing options
 
      - Test robustness, add more feedback about things like how much money you are spending
 
      - Configure the VM instance with tools and ML models
 
      - Improve the desktop/window managment setup to be more modern
 
    
   
Illustrations
  
    
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Background and References