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

Latest revision as of 15:45, 8 January 2016

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

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.	Exploring the Lesion-Size Toolbox algorithms for Lung Nodule detection. Configured StarCluster/AWS testing pipeline with time and cost estimates Confirmed that Slicer running in Docker container running on AWS EC2 instance can successfully host CIP algorithms. Video demonstrates running node segmentation and feature analysis running in a browser. Exploring use scenarios for radiomic analysis

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 * Configured StarCluster/AWS testing pipeline with time and cost estimates
 * 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].
+* Exploring use scenarios for radiomic analysis
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