From 8b2878d821c31fff837da5ebf17d0ffc64edb293 Mon Sep 17 00:00:00 2001 From: Ander Biguri Date: Fri, 22 Nov 2024 17:08:34 +0000 Subject: [PATCH] reformat list of papers --- papers_in_LION.md | 27 ++++++++++++++------------- 1 file changed, 14 insertions(+), 13 deletions(-) diff --git a/papers_in_LION.md b/papers_in_LION.md index 23f4221..38b3d7c 100644 --- a/papers_in_LION.md +++ b/papers_in_LION.md @@ -9,30 +9,30 @@ This is a list of papers implemented in the LION toolbox adn where to find the c Pelt, Daniël M., and James A. Sethian. "A mixed-scale dense convolutional neural network for image analysis." Proceedings of the National Academy of Sciences 115.2 (2018): 254-259. [https://doi.org/10.1073/pnas.1715832114](https://doi.org/10.1073/pnas.1715832114) -LION/models/CNNs/MS-D/ Submodule with the original repo -LION/models/CNNs/MSD_pytorch.py the LIONmodel to load the original code -LION/models/CNNs/MSDNet.py Our version of the MSD_pytorch model. Uses more memory +`LION/models/CNNs/MS-D/` Submodule with the original repo +`LION/models/CNNs/MSD_pytorch.py` the LIONmodel to load the original code +`LION/models/CNNs/MSDNet.py` Our version of the MSD_pytorch model. Uses more memory #### Learned Primal Dual (LPD) Adler, Jonas, and Ozan Öktem. "Learned primal-dual reconstruction." IEEE transactions on medical imaging 37.6 (2018): 1322-1332. [https://doi.org/10.1109/TMI.2018.2799231](https://doi.org/10.1109/TMI.2018.2799231) -LION/models/iterative_unrolled/LPD.py +`LION/models/iterative_unrolled/LPD.py` #### Continous Learned Primal Dual (cLPD) C. Runkel, A. Biguri and C. -B. Schönlieb, "Continuous Learned Primal Dual," 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP), London, United Kingdom, 2024, pp. 1-6, [https://doi.org/10.1109/MLSP58920.2024.10734760](https://doi.org/10.1109/MLSP58920.2024.10734760) -LION/models/iterative_unrolled/cLPD.py +`LION/models/iterative_unrolled/cLPD.py` #### Learned Gradient (LG) Adler, Jonas, and Ozan Öktem. "Solving ill-posed inverse problems using iterative deep neural networks." Inverse Problems 33.12 (2017): 124007. [https://doi.org/10.1088/1361-6420/aa9581](https://doi.org/10.1088/1361-6420/aa9581) -LION/models/iterative_unrolled/LG.py +`LION/models/iterative_unrolled/LG.py` ## Training Strategies @@ -40,21 +40,22 @@ LION/models/iterative_unrolled/LG.py This is not a paper (or perhasp many), but LION has a class to do a standard supervised training loop. -LION/optimizers/SupervisedSolver.py + +`LION/optimizers/SupervisedSolver.py` #### Noise2Inverse (self-supervised) Hendriksen, Allard Adriaan, Daniël Maria Pelt, and K. Joost Batenburg. "Noise2inverse: Self-supervised deep convolutional denoising for tomography." IEEE Transactions on Computational Imaging 6 (2020): 1320-1335. [https://doi.org/10.1109/TCI.2020.3019647](https://doi.org/10.1109/TCI.2020.3019647) -LION/optimizers/Noise2InverseSolver.py +`LION/optimizers/Noise2InverseSolver.py` #### Equivariant training (self-supervised) Chen, Dongdong, Julián Tachella, and Mike E. Davies. "Equivariant imaging: Learning beyond the range space." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2021. [https://doi.org/10.1109/ICCV48922.2021.00434](https://doi.org/10.1109/ICCV48922.2021.00434) -LION/optimizers/EquivariantSolver.py +`LION/optimizers/EquivariantSolver.py` ## Datasets @@ -64,16 +65,16 @@ LION/optimizers/EquivariantSolver.py Kiss, Maximilian B., et al. "2DeteCT-A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning." Scientific data 10.1 (2023): 576. [https://doi.org/10.1038/s41597-023-02484-6](https://doi.org/10.1038/s41597-023-02484-6) -LION/data_loaders/2deteCT/ Code to download and pre-process a LION version of the 2deteCT, made with the authors. -LION/data_loaders/deteCT.py Pytorch DataSet +`LION/data_loaders/2deteCT/` Code to download and pre-process a LION version of the 2deteCT, made with the authors. +`LION/data_loaders/deteCT.py` Pytorch DataSet #### LIDC-IDRI Armato III, Samuel G., et al. "The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans." Medical physics 38.2 (2011): 915-931. [https://doi.org/10.1118/1.3528204](https://doi.org/10.1118/1.3528204) -LION/data_loaders/LIDC_IDRI/ Code to pre-process a LION version of the dataset -LION/data_loaders/LIDC_IDRI.py Pytorch DataSet +`LION/data_loaders/LIDC_IDRI/` Code to pre-process a LION version of the dataset +`LION/data_loaders/LIDC_IDRI.py` Pytorch DataSet ## Loss functions