Difference between revisions of "Slicer3:UIDesign:WorkingProblems:BCAnalysis:Dynamic"

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== First experiment ==
 
== First experiment ==
  
Below is a screenshot of first perfusion dataset. The dataset contains upward of 900 volumes. Loading the original DICOM images took a very long time; Junichi converted these images to nrrd format, but the loading still takes prohibitively long, and interacting is also very slow. Perhaps for a first demo we can use a smaller dataset?
+
Below is a screenshot of first perfusion dataset. The dataset contains upward of 900 volumes. Loading the original DICOM images took a very long time; Junichi converted these images to nrrd format, but the loading still takes prohibitively long, and interacting is also very slow.  
 +
 
 +
=== ideas: ====
 +
* can we create a VOI and apply to each volume in the timeseries?
 +
* Alternatively, for a first demo we can use a smaller dataset?
  
 
[[image:BCAnalysis_Perfusion1.png]]
 
[[image:BCAnalysis_Perfusion1.png]]
  
Also, I'm having a lot of challenges to compile the 4DImage analysis package... working on this, and will ask Junichi for his input.
+
Also, I'm having difficulty building the 4DImage analysis package (seems numpy includes not found)... will ask Junichi for his input.

Revision as of 13:29, 17 August 2009

Home < Slicer3:UIDesign:WorkingProblems:BCAnalysis:Dynamic

Back to Project Overview

Perfusion Analysis for Breast Cancer

Goal

Goal is to accommodate basic RECIST assessment for breast cancer (Response Evaluation Criteria In Solid Tumors). (RECIST is a set of published rules that define when cancer patients improve ("respond"), stay the same ("stable") or worsen ("progression") during treatments).

  • Determine features that currently exist in Slicer
  • Develop features that don't
  • Provide a framework that knits features together in a comfortable workflow.

Perfusion Analysis Workflow

  • Visualize the dataset dynamically
  • Specify an ROI that includes tumor and apply to all timepoints Question: ROI or VOI? (either -- if slice, must be same slice)
  • Plot contrast dilution curve
    • show time to peak in tumor
  • Specify an ROI that includes blood pool and apply to all timepoints Question: again, ROI or VOI?
  • Plot contrast dilution curve for this (on same graph)
    • show time to peak in blood pool
  • show transit time (distance between peaks in each plot)
  • save out timepoints ( Intensity(t) for each ROI -- include multiple tumors if desired)

First experiment

Below is a screenshot of first perfusion dataset. The dataset contains upward of 900 volumes. Loading the original DICOM images took a very long time; Junichi converted these images to nrrd format, but the loading still takes prohibitively long, and interacting is also very slow.

ideas: =

  • can we create a VOI and apply to each volume in the timeseries?
  • Alternatively, for a first demo we can use a smaller dataset?

BCAnalysis Perfusion1.png

Also, I'm having difficulty building the 4DImage analysis package (seems numpy includes not found)... will ask Junichi for his input.