src.original.fitting.OGC_AUMC_IVIMNET package

Submodules

src.original.fitting.OGC_AUMC_IVIMNET.Example_1_simple_map module

src.original.fitting.OGC_AUMC_IVIMNET.Example_2_simulations module

src.original.fitting.OGC_AUMC_IVIMNET.Example_3_volunteer module

src.original.fitting.OGC_AUMC_IVIMNET.hyperparams module

September 2020 by Oliver Gurney-Champion oliver.gurney.champion@gmail.com / o.j.gurney-champion@amsterdamumc.nl https://www.github.com/ochampion

Code is uploaded as part of our publication in MRM (Kaandorp et al. Improved unsupervised physics-informed deep learning for intravoxel-incoherent motion modeling and evaluation in pancreatic cancer patients. MRM 2021)

requirements: numpy torch tqdm matplotlib scipy joblib

class src.original.fitting.OGC_AUMC_IVIMNET.hyperparams.hyperparams[source]: Bases: object

class src.original.fitting.OGC_AUMC_IVIMNET.hyperparams.lsqfit[source]: Bases: object

class src.original.fitting.OGC_AUMC_IVIMNET.hyperparams.net_pars(nets)[source]: Bases: object

class src.original.fitting.OGC_AUMC_IVIMNET.hyperparams.sim[source]: Bases: object

class src.original.fitting.OGC_AUMC_IVIMNET.hyperparams.train_pars(nets)[source]: Bases: object

Module contents