{"id":19479526,"url":"https://github.com/jtschwar/tomo_tv","last_synced_at":"2025-04-25T15:31:16.042Z","repository":{"id":54815005,"uuid":"185291820","full_name":"jtschwar/tomo_TV","owner":"jtschwar","description":"C++ library for Regularized 2D and 3D Tomography Reconstructions. 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Specifically, this repository provides a selection of various data models and regularizers for simple python development. Tomo_TV also contains supports experiments where data is 'dynamically' collected to facilitate real-time analysis of tomograms. \n\n## Features\n\n2D and 3D reconstruction algorithms implemented purely in C++ wrapped in Python functions.  These scripts can either perform simulations (sim) or reconstruct experimental (exp) projections. Available algorithms include:\n* Filtered Backprojection (FBP)\n* Simultaneous Iterative/Algebraic Reconstruction Technique (SIRT/SART)\n* Conjugate Gradient - Least Squares (CGLS)\n* KL-Divergence / Expectation Maximization for Poisson Limited Datasets\n* FISTA [doi: 10.1137/080716542](https://epubs.siam.org/doi/10.1137/080716542)\n* ASD - POCS [doi: 10.1088/0031-9155/53/17/021](https://iopscience.iop.org/article/10.1088/0031-9155/53/17/021)\n* (TODO: OGM and FASTA )\n\nWe provide a sample jupyter notebook ([demo.ipynb](demo.ipynb)) which outlines the reconstruction process for all these algorithms both with simulated and experimental datasets. \n\n## Installation\n\nTo clone the repositiory and all the core dependencies run the following line in the terminal: \n\n` git clone --recursive https://github.com/jtschwar/tomo_TV.git`\n\nFor GPU accelerated reconstruction algorithms, we recomend using a Linux operating system. C++ accelerated operations is available on all three operating systems (Windows, macOS, and Linux). \n\nInstructructions for building can be found in [BUILDING.MD](BUILDING.md).\n\n## Multi-GPU Capabilities\ntomo_TV can be used by running in parallel across multiple GPU devices on a personal computer or compute nodes in a high-performance computing cluster. In order to initiate a parallel run on multiple GPUs, MPI needs to be available. \n\n## References\nIf you use tomo_TV for your research, we would appreciate it if you cite to the following papers:\n\n- [Real-time 3D analysis during electron tomography using tomviz](https://www.nature.com/articles/s41467-022-32046-0)\n- [Imaging 3D Chemistry at 1 nm resolution with fused multi-modal electron tomography](https://www.nature.com/articles/s41467-024-47558-0)\n     \n## Contribute\n\nIssue Tracker:  https://github.com/jtschwar/tomo_TV/issues\n\nFeel free to open an issue if you have any comments or concerns. \n    \n## Contact\n\nemail: [jtschw@umich.edu](jtschw@umich.edu)\nwebsite: [https://jtschwar.github.io](https://jtschwar.github.io)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjtschwar%2Ftomo_tv","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjtschwar%2Ftomo_tv","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjtschwar%2Ftomo_tv/lists"}