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Table 1 Software characteristics

From: MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging – design, implementation and application on the example of DCE-MRI

  MITK- ModelFit UMM Perfusion Rocketship DCEMRI.jl PMI DATforDCEMRI 3DSlicer PkModeling
Operating system Linux, Mac OS, Windows Mac OS Linux, Mac OS, Windows Linux, Mac OS, Windows Windows Linux, Mac OS, Windows Linux, Mac OS, Windows
Language C++ C Matlab Julia IDL R C++
License BSD BSD GNUGPL MIT GNU GPL Creative Commons Slicer (BSD like)
Advanced extensibility Yes Yes No No No No Yes
Fitting domain Time, Frequency, anya Time Time Time Time Time Time
Eco-system Yes (MITK) Yes (OsiriX) No No Yes (PMI) No Yes (3DSlicer)
Models Tofts, Extended Tofts, 2CXM, 1TCM, 2TCM, Brix, Three-step linear (3SL), Semi-quantitative metrics (BAT, TTP, AUC, Cmax, Wash-in/Wash-out Slope, final uptake, mean residence time) Extended Tofts, 1CP, 2CXM, 2C uptake model, two compartment filtration model (2FM) Tofts, Extended Tofts, Fast Exchange Regime, 2CXM, Tissue uptake, Nested-model selection, Patlak, Semi-quantitative metrics (AUC) Tofts, Extended Tofts, Plasma Only Uptake models, Steady-state, Patlak, Model-free deconvolution, Tofts, Extended Tofts, 2CXM, 2C filtration model for kidney, Dual-inlet models for Liver, Semi-quantitative metrics (Slope/Signal enhancement) Tofts, Semi-quantitative metrics (AUC, MRT - mean residence time) Tofts, Semi-quantitative metrics (AUC, slope)
Input / Output DICOM, Analyze, NIFTI, NRRD, VTK, Raw data DICOM DICOM, Analyze, NIFTI, Raw data, Matlab data Matlab data DICOM, Raw data R readable data formats DICOM, Analyze, NIFTI, NRRD, VTK, Raw data
GUI Yes Yes Yes No Yes No Yes
Fit exploration Yes Yes Yes No Yes No Yesb
PACS Support Yes Yes No No No No Yes
Automatization Yes Partiallyc Yes Yes Yes Yes Yes
  1. aPossibility to extend framework to support other fitting domains
  2. bPossibility to generate a 3D+t image that encode the voxel-wise model signal and to explore the image with the MultiVolumeExplorer
  3. cPossibility to loop over all models and selected tissue ROIs for the loaded Data in the UMMPerfusion user interface
  4. The selection of solutions represents well-known or relative similar solutions compared to our work in order to clarify the differences. The selection does not claim to be exhaustive. Commercial solutions are not included. Further R or Matlab are only included in context of concrete tools (DATforDCEMRI and Rocketship) and not as generic fitting environments on their own. The later would be a categorical error. R as well as Matlab can handle generic fitting problems or allow GUIs but by implementing an application from scratch and not by just using it of the shelf or extending an existing one. The following characteristics are assessed in the table: Operating system; Language (Programming language of the software); License (needed to regard if software is used/extended); Advanced extensibility (Indicates if software was designed to easily be extended with new models without the need to change the basis application or its programming logic; implies a advanced level of abstraction and decoupling); Fitting domain (Indicates which domains are supported for the fitting); Eco-system (indicates if software is embedded into image processing eco-system); Image modalities (medical image modalities that are supported be model and fitting techniques); Models (included pharmacokinetic models); Input / Output (most relevant data formats supported by the software); GUI (indicates if software offers a graphical user interface); Fit exploration (indicates if the software allows to interactively investigate the fit and signal curve per voxel/ROI); PACS Support (indicates if the software allows to use DICOM Q/R or receive data via DICOM Send); Automatization (indicates if the software can be used to automatize the analysis with no user interaction); Source (Link to the source codes or developer’s site)