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Merge pull request #119 from OSIPI/algorithm_csv
Algorithm csv
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‎doc/code_contributions_record.csv‎

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Technique,Category,Subcategory,notes,subfolder,Link to source code,Authors,Institution,function/module,DOI,Tester,test status,Wrapped
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IVIM,Fitting,LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_least_squares/fit_least_squares_array,,tbd,,
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IVIM,Fitting,segmented LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_segmented/fit_segmented_array,,tbd,,OGC_AmsterdamUMC_biexp
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Tri-exponential,Fitting,LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_least_squares_tri_exp/fit_least_squares_array_tri_exp,,tbd,,
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Tri-exponential,Fitting,Segmented LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_segmented_tri_exp/fit_segmented_array_tri_exp,https://doi.org/10.3389/fphys.2022.942495,tbd,,OGC_AmsterdamUMC_biexp_segmented
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IVIM,Fitting,Bayesian,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion/Sebastiano Barbieri,Amsterdam UMC,fit_bayesian_array,https://doi.org/10.1002/mrm.28852,tbd,,OGC_AmsterdamUMC_Bayesian_biexp
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IVIM,Fitting,two-step segmented fit approach,also includes ADC calculation as a separate function,PvH_KB_NKI,TF2.4_IVIM-MRI_CodeCollection/src/original/PvH_KB_NKI/,Petra van Houdt/Stefan Zijlema/Koen Baas,the Netherlands Cancer Institute,DWI_functions_standalone.py,https://doi.org/10.3389/fonc.2021.705964,tbd,,PvH_KB_NKI_IVIMfit
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IVIM,Fitting,two-step (segmented) LSQ fitting, cut-off chosen for brain data; option to fit IVIM with inversion recovery or without IR,PV_MUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/PV_MUMC/,Paulien Voorter,Maastricht University Medical Center,two_step_IVIM_fit.py,,tbd,,PV_MUMC_biexp
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IVIM,Fitting,bi-exponential NLLS,Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_biexp.py,Ivan A. Rashid,Lund University,IvimModelBiexp,tba,tbd,,IAR_LU_biexp
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IVIM,Fitting,2-step segmented NLLS,First estimates and fixes D before a bi-exponential NLLS fit. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_segmented_2step.py,Ivan A. Rashid,Lund University,IvimModelSegmented2Step,tba,tbd,,IAR_LU_segmented_2step
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IVIM,Fitting,3-step segmented NLLS,First estimates and fixes D followed by an estimate of D* followed by a bi-exponential NLLS fit. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_segmented_3step.py,Ivan A. Rashid,Lund University,IvimModelSegmented3Step,tba,tbd,,IAR_LU_segmented_3step
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IVIM,Fitting,2-step segmented NLLS,First estimates and fixes D. Subtracts the diffusion signal and estimated D*. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_subtracted.py,Ivan A. Rashid,Lund University,IvimModelSubtracted,tba,tbd,,IAR_LU_subtracted
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IVIM,Fitting,Variable projection,See referenced article. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_mix.py,Farooq et al. Modified by Ivan A. Rashid,Lund University,IvimModelVP,https://doi.org/10.1038/srep38927,tbd,,IAR_LU_modified_mix
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IVIM,Fitting,Variable projection,See referenced article. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_topopro.py,Fadnavis et al. Modified by Ivan A. Rashid,Lund University,IvimModelTopoPro,https://doi.org/10.3389/fnins.2021.779025,tbd,,IAR_LU_modified_topopro
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IVIM,Fitting,Linear fit,Linear fit for D with extrapolation for f. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_linear.py,Modified by Ivan A. Rashid,Lund University,IvimModelLinear,tba,tbd,,
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IVIM,Fitting,sIVIM fit,NLLS of the simplified IVIM model (sIVIM). Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_sivim.py,Modified by Ivan A. Rashid,Lund University,IvimModelsIVIM,tba,tbd,,
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IVIM,Fitting,Segmented NLLS fitting,MATLAB code,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,IVIM_seg,https://doi.org/10.1007/s10334-018-0697-5,tbd,,OJ_GU_seg
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IVIM,Fitting,Bayesian,MATLAB code,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,IVIM_bayes,https://doi.org/10.1002/mrm.26783,tbd,,
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IVIM,Fitting,Segmented NLLS fitting,Specifically tailored algorithm for NLLS segmented fitting,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,seg,https://doi.org/10.1007/s10334-018-0697-5,tbd,,
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IVIM,Fitting,Linear fit,Linear fit for D and D* and f. Intended to be extremely fast but not always accurate,ETP_SRI,TF2.4_IVIM-MRI_CodeCollection/src/original/ETP_SRI/LinearFitting.py,Eric Peterson,SRI International,,,tbd,,ETP_SRI_LinearFitting
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Technique,Category,Subcategory,notes,subfolder,Link to source code,Authors,Institution,function/module,DOI,Wrapped
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IVIM,Fitting,LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_least_squares/fit_least_squares,https://doi.org/10.1002/mrm.28852,OGC_AmsterdamUMC_biexp
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IVIM,Fitting,segmented LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_segmented/fit_segmented,https://doi.org/10.1002/mrm.28852,OGC_AmsterdamUMC_biexp_segmented
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Tri-exponential,Fitting,LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_least_squares_tri_exp/fit_least_squares_tri_exp,https://doi.org/10.3389/fphys.2022.942495,
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Tri-exponential,Fitting,Segmented LSQ fitting,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion,Amsterdam UMC,fit_segmented_tri_exp/fit_segmented_tri_exp,https://doi.org/10.3389/fphys.2022.942495,
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IVIM,Fitting,Bayesian,,OGC_AmsterdamUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AmsterdamUMC/,Oliver Gurney-Champion/Sebastiano Barbieri,Amsterdam UMC,fit_bayesian_array,https://doi.org/10.1002/mrm.28852,OGC_AmsterdamUMC_Bayesian_biexp
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IVIM,Fitting,Neural network,Self-supervised neural network,OGC_AUMC_IVIMNET,TF2.4_IVIM-MRI_CodeCollection/src/original/OGC_AUMC_IVIMNET/,Oliver Gurney-Champion,Amsterdam UMC,predict_IVIM,https://doi.org/10.1002/mrm.28852,IVIM_NEToptim
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IVIM,Fitting,two-step segmented fit approach,also includes ADC calculation as a separate function,PvH_KB_NKI,TF2.4_IVIM-MRI_CodeCollection/src/original/PvH_KB_NKI/,Petra van Houdt/Stefan Zijlema/Koen Baas,the Netherlands Cancer Institute,DWI_functions_standalone.py,https://doi.org/10.3389/fonc.2021.705964,PvH_KB_NKI_IVIMfit
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IVIM,Fitting,two-step (segmented) LSQ fitting,cut-off chosen for brain data; option to fit IVIM with inversion recovery or without IR,PV_MUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/PV_MUMC/,Paulien Voorter,Maastricht University Medical Center,two_step_IVIM_fit.py,tba,PV_MUMC_biexp
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Tri-exponential,Fitting,LSQ fitting,Triexponential fitting with non-linear least squares,PV_MUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/PV_MUMC/,Paulien Voorter,Maastricht University Medical Center,triexp_fitting_algorithms/fit_least_squares_tri_exp,https://doi.org/10.1002/mrm.29753,
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Tri-exponential,Fitting,NNLS,Triexponential fitting with non-negative least squares,PV_MUMC,TF2.4_IVIM-MRI_CodeCollection/src/original/PV_MUMC/,Paulien Voorter,Maastricht University Medical Center,triexp_fitting_algorithms/fit_NNLS,https://doi.org/10.1002/mrm.29753,
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IVIM,Fitting,bi-exponential NLLS,Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_biexp.py,Ivan A. Rashid,Lund University,IvimModelBiexp,tba,IAR_LU_biexp
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IVIM,Fitting,2-step segmented NLLS,First estimates and fixes D before a bi-exponential NLLS fit. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_segmented_2step.py,Ivan A. Rashid,Lund University,IvimModelSegmented2Step,tba,IAR_LU_segmented_2step
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IVIM,Fitting,3-step segmented NLLS,First estimates and fixes D followed by an estimate of D* followed by a bi-exponential NLLS fit. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_segmented_3step.py,Ivan A. Rashid,Lund University,IvimModelSegmented3Step,tba,IAR_LU_segmented_3step
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IVIM,Fitting,2-step segmented NLLS,First estimates and fixes D. Subtracts the diffusion signal and estimated D*. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_subtracted.py,Ivan A. Rashid,Lund University,IvimModelSubtracted,tba,IAR_LU_subtracted
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IVIM,Fitting,Variable projection,See referenced article. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_mix.py,Farooq et al. Modified by Ivan A. Rashid,Lund University,IvimModelVP,https://doi.org/10.1038/srep38927,IAR_LU_modified_mix
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IVIM,Fitting,Variable projection,See referenced article. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_topopro.py,Fadnavis et al. Modified by Ivan A. Rashid,Lund University,IvimModelTopoPro,https://doi.org/10.3389/fnins.2021.779025,IAR_LU_modified_topopro
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IVIM,Fitting,Linear fit,Linear fit for D with extrapolation for f. Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_linear.py,Modified by Ivan A. Rashid,Lund University,IvimModelLinear,tba,
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IVIM,Fitting,sIVIM fit,NLLS of the simplified IVIM model (sIVIM). Supports units in mm2/s and µm2/ms,IAR_LundUniversity,TF2.4_IVIM-MRI_CodeCollection/src/original/IAR_LundUniversity/ivim_fit_method_modified_sivim.py,Modified by Ivan A. Rashid,Lund University,IvimModelsIVIM,tba,
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IVIM,Fitting,Segmented NLLS fitting,MATLAB code,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,IVIM_seg,https://doi.org/10.1007/s10334-018-0697-5,OJ_GU_seg
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IVIM,Fitting,Bayesian,MATLAB code,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,IVIM_bayes,https://doi.org/10.1007/s10334-018-0697-5,OJ_GU_segMATLAB
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IVIM,Fitting,Segmented NLLS fitting,Specifically tailored algorithm for NLLS segmented fitting,OJ_GU,TF2.4_IVIM-MRI_CodeCollection/src/original/OJ_GU/,Oscar Jalnefjord,University of Gothenburg,seg,https://doi.org/10.1002/mrm.26783,OJ_GU_bayesMATLAB
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IVIM,Fitting,Linear fit,Linear fit for D and D* and f. Intended to be extremely fast but not always accurate,ETP_SRI,TF2.4_IVIM-MRI_CodeCollection/src/original/ETP_SRI/LinearFitting.py,Eric Peterson,SRI International,LinearFit,tba,ETP_SRI_LinearFitting
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IVIM,Fitting,LSQ fitting,MATLAB code,ASD_MemorialSloanKettering,TF2.4_IVIM-MRI_CodeCollection/src/original/ASD_MemorialSloanKettering/MRI-QAMPER_IVIM,Eve LoCastro/Ramesh Paudyal/Amita Shukla-Dave,Memorial Sloan Kettering,IVIM_standard_bcin,https://doi.org/10.3390/tomography9060161,ASD_MemorialSloanKettering_QAMPER_IVIM
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IVIM,Fitting,Neural network,Part of the SUPER-IVIM-DC python package,TCML_TechnionIIT,TF2.4_IVIM-MRI_CodeCollection/src/original/TCML_TechnionIIT/SUPER-IVIM-DC,Noam Korngut/Elad Rotman/Onur Afacan Sila Kurugol/Yael Zaffrani-Reznikov/Shira Nemirovsky-Rotman/Simon Warfield/Moti Freiman,TCML Technion IIT,super_ivim_dc.infer.infer_from_signal,https://doi.org/10.1007/978-3-031-16434-7_71,Super_IVIM_DC
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IVIM,Fitting,LSQ fitting,Part of the SUPER-IVIM-DC python package - BOBYQA lsq algorithm,TCML_TechnionIIT,TF2.4_IVIM-MRI_CodeCollection/src/original/TCML_TechnionIIT/SUPER-IVIM-DC,Noam Korngut/Elad Rotman/Onur Afacan Sila Kurugol/Yael Zaffrani-Reznikov/Shira Nemirovsky-Rotman/Simon Warfield/Moti Freiman,TCML Technion IIT,super_ivim_dc.source.Classsic_ivim_fit.fit_least_squers_BOBYQA,https://doi.org/10.1007/978-3-031-16434-7_71,TCML_TechnionIIT_lsqBOBYQA
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IVIM,Fitting,LSQ fitting,Part of the SUPER-IVIM-DC python package - Levenberg Marquart lsq algorithm,TCML_TechnionIIT,TF2.4_IVIM-MRI_CodeCollection/src/original/TCML_TechnionIIT/SUPER-IVIM-DC,Noam Korngut/Elad Rotman/Onur Afacan Sila Kurugol/Yael Zaffrani-Reznikov/Shira Nemirovsky-Rotman/Simon Warfield/Moti Freiman,TCML Technion IIT,super_ivim_dc.source.Classsic_ivim_fit.fit_least_squares_lm,https://doi.org/10.1007/978-3-031-16434-7_71,TCML_TechnionIIT_lsqlm
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IVIM,Fitting,LSQ fitting,Part of the SUPER-IVIM-DC python package - trust region lsq algorithm,TCML_TechnionIIT,TF2.4_IVIM-MRI_CodeCollection/src/original/TCML_TechnionIIT/SUPER-IVIM-DC,Noam Korngut/Elad Rotman/Onur Afacan Sila Kurugol/Yael Zaffrani-Reznikov/Shira Nemirovsky-Rotman/Simon Warfield/Moti Freiman,TCML Technion IIT,super_ivim_dc.source.Classsic_ivim_fit.fit_least_squares_trf,https://doi.org/10.1007/978-3-031-16434-7_71,TCML_TechnionIIT_lsqtrf
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IVIM,Fitting,LSQ fitting,Part of the SUPER-IVIM-DC python package - segmented algorithm,TCML_TechnionIIT,TF2.4_IVIM-MRI_CodeCollection/src/original/TCML_TechnionIIT/SUPER-IVIM-DC,Noam Korngut/Elad Rotman/Onur Afacan Sila Kurugol/Yael Zaffrani-Reznikov/Shira Nemirovsky-Rotman/Simon Warfield/Moti Freiman,TCML Technion IIT,super_ivim_dc.source.Classsic_ivim_fit.IVIM_fit_sls,https://doi.org/10.1007/978-3-031-16434-7_71,TCML_TechnionIIT_lsqSLS
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IVIM,Fitting,LSQ fitting,Part of the SUPER-IVIM-DC python package - Levenberg Marquart lsq algorithm initialized with segmented fitting,TCML_TechnionIIT,TF2.4_IVIM-MRI_CodeCollection/src/original/TCML_TechnionIIT/SUPER-IVIM-DC,Noam Korngut/Elad Rotman/Onur Afacan Sila Kurugol/Yael Zaffrani-Reznikov/Shira Nemirovsky-Rotman/Simon Warfield/Moti Freiman,TCML Technion IIT,super_ivim_dc.source.Classsic_ivim_fit.IVIM_fit_sls_lm,https://doi.org/10.1007/978-3-031-16434-7_71,TCML_TechnionIIT_lsq_sls_lm
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IVIM,Fitting,LSQ fitting,Part of the SUPER-IVIM-DC python package - trust region lsq algorithm initialized with segmented fitting,TCML_TechnionIIT,TF2.4_IVIM-MRI_CodeCollection/src/original/TCML_TechnionIIT/SUPER-IVIM-DC,Noam Korngut/Elad Rotman/Onur Afacan Sila Kurugol/Yael Zaffrani-Reznikov/Shira Nemirovsky-Rotman/Simon Warfield/Moti Freiman,TCML Technion IIT,super_ivim_dc.source.Classsic_ivim_fit.IVIM_fit_sls_trf,https://doi.org/10.1007/978-3-031-16434-7_71,TCML_TechnionIIT_lsq_sls_trf
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IVIM,Fitting,Segmented linear fitting,Consensus algorithm,TF_reference,TF2.4_IVIM-MRI_CodeCollection/src/original/TF_reference/,Ben Neijndorff/OSIPI taskforce 2.4,OSIPI,segmented_IVIMfit,tba,TF_reference_IVIMfit

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