Difference between revisions of "2016 Winter Project Week/Projects/Cluster-Driven Lung Segmentation"

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* Exploring the Lesion-Size Toolbox algorithms for Lung Nodule detection.  
 
* Exploring the Lesion-Size Toolbox algorithms for Lung Nodule detection.  
 
* Configured StarCluster/AWS testing pipeline with time and cost estimates
 
* Configured StarCluster/AWS testing pipeline with time and cost estimates
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* Confirmed that Slicer running in Docker container running on AWS EC2 instance can successfully host CIP algorithms.  [https://www.youtube.com/watch?v=tCCQ_N2m8zs Video demonstrates running node segmentation and feature analysis running in a browser].
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* Exploring use scenarios for radiomic analysis
 
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== References ==
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[https://docs.google.com/presentation/d/1miyj0_l9x2Z3oMSnpB3beoLTy12iUo0ilp7f5hhh8dk/edit#slide=id.g74ed54aa6_0_95 Slides describing initial experiments]

Latest revision as of 15:45, 8 January 2016

Home < 2016 Winter Project Week < Projects < Cluster-Driven Lung Segmentation

Key Investigators

  • Vivek Narayan (Dana Farber)
  • Raúl San José (BWH)
  • Dan Blezek (Isomics, Inc.)
  • Steve Pieper(Isomics, Inc.)
  • Chintan Parmar (Dana Farber)

Project Description

Objective Approach and Plan Progress and Next Steps
  • Consolidation of Lung Nodule detection and segmentation algorithms into pipelines.
  • Iterative parameter-space testing of pipelines in cluster-computing environments.
  • Perform evaluations against expert-contoured segmentations.
  • Explore and optimize existing Lung Nodule detection/segmentation tools.
  • Configure and launch StarCluster Nodes on AWS to run pipelines.
  • Use LIDC Data for evaluation of pipelines (~1200+ CT Images with manual contours).
  • Evaluate Segmentation pipelines against manual contours using metrics such as SimpleITK filters, Dice, Hausdorff, and Radiomics.

References

Slides describing initial experiments