2016 Winter Project Week/Projects/ChestImagingPlatformWorkflows

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Home < 2016 Winter Project Week < Projects < ChestImagingPlatformWorkflows

Key Investigators

  • James Ross
  • Raúl San José

Project Description

The Chest Imaging Platform (CIP) is a collection of C++ libraries, command-line executables, and python modules for segmenting, registering, processing, and quantitatively evaluating medical images of the chest; it is developed with large-scale, batch processing of high-resolution computed tomography (CT) images in mind. Many of the high-level workflows involve executing multiple CIP command-line tools and/or python modules, which imposes a barrier to entry for new users. Nipype is an open-soure, python-based software package that provides the ability to package multiple execution steps into a single workflow. In this project, I will be creating nipype-based workflows of commonly used, high-level tasks in order to make CIP functionality more accessible to new users.

Objective Approach and Plan Progress and Next Steps
  • Implement Nipype workflows for commonly used chest image analysis tasks
  • Focus on automatic lobe segmentation pipeline
  • Workflows exist for particle deployment and parenchyma phenotype computation
  • End-to-end workflow created for automatic lobe segmentation
  • A few extra nodes to add
  • Include in next CIP release