SMILI – The Simple Medical Imaging Library Interface

The Simple Medical Imaging Library Interface (SMILI), pronounced ‘smilie’, is an open-source, lightweight and easy-to-use medical imaging viewer and library for all major operating systems.

The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions.

It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with graphical user interfaces and/or via the command-line.

The applications are all built out of a uniform user-interface framework that provides a very high level (Qt) interface to powerful image processing and scientific visualisation algorithms from the Insight Toolkit (ITK) and Visualisation Toolkit (VTK). The framework allows one to build stand-alone medical imaging applications quickly and easily.

Features include:

  • Image Processing.
  • Surface/Model Processing.
  • Surface/Model Visualisation.
  • n-D Image Visualisation.
  • Deformation Field Visualisation.
  • DICOM and DICOM RT Support.
  • Shape Modelling.
  • Python Scripting.
  • Polygonal Contouring.
  • Animating Surfaces.
  • Formats include:
    • Nifti (*.nii.gz *.nii) and GIPL (*.gipl).
    • Analyse (*.img *.hdr)
    • Raster multimedia formats: PNG, JPEG, BMP, TIFF, PPM.
    • DICOMs of various descriptions (*.ima *.dcm *.dicom). Support is done via the GDCM library.
    • VTK XML Image (*.vti)
    • Triangulated Surfaces or 3D Models (*.vtp *.vtk *.ply *.obj *.stl)
    • Meta Images (*.mha *.mhd)
    • Delimited Text or Comma Separated Value files (*.txt *.csv). This is mainly for plots.
    • Medical imaging formats supported by the Insight Toolkit (ITK).
    • Other formats that can be supported include (PGM, INR, DICOM RTs (Structure Sets)) with the appropriate plugins.

Website: smili-project.sourceforge.io
Support: Documentation, Mailing List
Developer: Chandra, S. S.; Dowling, J. A.; Engstrom, C.; Xia, Y.; Paproki, A.; Neubert, A.; Rivest-Hénault, D.; Salvado, O.; Crozier, S. & Fripp, J.
License: Open Source


SMILI is written in Python and C++. Learn Python with our recommended free books and free tutorials. Learn C++ with our recommended free books and free tutorials.

Return to Medical Imaging

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