MITK

  1. Description of the platform/product:

  2. Description of the relevant features of the platform:

    • are both single and multiple segments supported? yes
    • how are the overlapping segments handled? With semi-transparent color overlay and the active label is contoured (see screenshots)

|

  • do you support both BINARY and FRACTIONAL segmentation types?
  • do you render the segment using the color specified in the DICOM object? yes
  • how do you communicate segment semantics to the user? semantic codes are stored as property for each label, so the user can not easily get the information
  • how do you support the user in defining the semantics of the object at the time segmentation is created? The user can select from a pre-defined list of organs, structures,... when adding a new label to the segmentation. The selection is mapped to segmentation category/type and color internally
  1. Read task: load each of the DICOM SEG datasets that accompany the imaging series into your platform

Test dataset #1

Test dataset Result of rendering
3D Slicer
AIMonClearCanvas
ePAD
syngo.via

Test dataset #2

Test dataset Result of rendering
3D Slicer

Test dataset #3

Test dataset Result of rendering
3D Slicer

Test dataset #4

TODO:

Test dataset Result of rendering
3D Slicer
  1. Write task
    • segment the lung lesion using any method available in your platform; save the result as DICOM SEG; please include in the series description the name of your tool to simplify comparison tasks!
    • results are uploaded
    • run dciodvfy DICOM validator; iterate on resolving the identified issues as necessary
    • no errors, only warnings from dciodvfy

results matching ""

    No results matching ""