PET Tumor Segmentation

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Home < PET Tumor Segmentation

Key Investigators

Christian Bauer (University of Iowa)

Project Description

PET MIP with head and neck lesions segmented lesion

Objective

  • Finalize tool for tumor and lymph node segmentation in PET scans
  • Make it publicly available through Slicer Extension Manager
  • Segmentation method based on Markus van Tol (2014): A Graph-Based Method for Segmentation of Tumors and Lymph Nodes in Volumetric PET Images, The University of Iowa

Approach, Plan

  • Main functionality of the tool has already been developed
  • Write self tests
  • replace solver with Slicer-license compatible solver
  • fine-tune GUI, prepare icon, etc.
  • document and clean up source code
  • create webpage with documentation and usage tutorial
  • get module into Slicer extension management system
  • potentially: add functionality to obtain quantitative measurements immediately during segmentation process

Progress

  • wrote self tests
  • cleaned source code
  • switched to new solver and verified correct behavior
  • switched to most recent version of 3D Slicer and verified correct behavior
  • created webpage with user documentation
  • put extension onto github and submitted for integration into Slicer extensions manager

Screenshots

PET Tumor Segmentation Editor Effect Options PET Tumor Segmentation Editor Effect