2014 Summer Project Week:Pluggable Label Statistics

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Key Investigators

  • Andrey Fedorov, BWH
  • Ethan Ulrich, Univ. of Iowa
  • Steve Pieper, Isomics
  • Bradley Lowekamp, NIH

Project Description

Objective

Our aim is to develop an module for calculating various statistical measures over image ROI that expands upon the currently available capabilities of Slicer LabelStatistics module. Some of the desired features include:

  • pluggable set of "feature" calculators
  • "jump to label" feature
  • support of terminologies defining the features
  • what else?

Approach, Plan

  • determine requirements of the module
  • discuss the options for implementing pluggable list of features
    • define a category for feature calculators? or create wrappers and add them manually?
  • discuss how we can pass semantical information associated with the feature sets (terminology), should this be done at the SEM level?
  • consider Landmark Registration extension for how to use extensible features
  • consider using Reporting extension
  • integrate quantitative features implemented in PET Quantitative indices extension

Progress

  • We held a breakout session and discussed the capabilities of the existing modules that calculate statistics measures over ROI
    • The module being developed by Vivek and Jay includes a lot of nice features, but not yet released or modularized, some of the measures implemented overlap with existing functionality in ITK
  • Identified the groups of statistics filters available in ITK and SimpleITK that can be reused
  • Will work on a generalized python API to reuse currently available features and add them to Reporting module

Label statistics related tools/modules