DICOM4MICCAI Hands-on
  • Introduction
  • Prerequisites
    • If you are attending the tutorial in-person
    • If you are following on your own
  • Using DICOM to store your analysis results
    • Using 3D Slicer to convert non-DICOM segmentation results
    • DICOM Structured Reporting for radiomics
    • Using 3D Slicer for storing analysis results in DICOM
      • Step 0: 3D Slicer interface basics
      • Step 1: Import DICOM data
      • Step 2: Load DICOM image
      • Step 3: Segment lesions
      • Step 3.1:QuantitativeReporting interface overview
      • Step 3.2: Create and initialize a new segment
      • Step 3.3: Segment the lesions
      • Step 4: Explore and store the analysis results in DICOM
      • Step 5: Reload the analysis results from DICOM
      • Exporting DICOM data from 3D Slicer
    • Using MITK Workbench for storing segmentation results in DICOM
      • Step 0: MITK interface basics
      • Step 1: Import DICOM data
      • Step 2: Load DICOM image
      • Step 3: Segment lesions
      • Step 4: Explore and store the segmentations in DICOM
      • Step 5: Reload the segmentations from DICOM
  • DICOM data wrangling
  • Further reading
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  1. Using DICOM to store your analysis results

DICOM Structured Reporting for radiomics

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Last updated 6 years ago

Hands-on demo notes

  • - background, demo

  • typical inputs of pyradiomics: introduce

  • examine the output CSV or JSON file produced by pyradiomics

  • pyradiomics-dcm.py demo (scripts used in this tutorial are )

  • discuss the organization of the resulting object

    • reference to the TID 1500 template

  • load the resulting object into Slicer, discuss connection with dcmqi

  • discuss connection with (feature codes added in v7 of the document)

pyradiomics
dcm2niix
here
IBSI