Application
The library provides most state-of-the-art deep learning-based (and non-deep learning) reconstruction algorithms for image reconstruction, together with modeling of multiple imaging operators in medical imaging and other domains as well.
Contributors
Julián Tachella¹, Matthieu Terris², Samuel Hurault³, Andrew Wang⁴, Dongdong Chen⁵, Minh-Hai Nguyen⁶, Maxime Song⁷,
Thomas Davies⁴˒⁵, Leo Davy¹, Jonathan Dong⁸, Paul Escande⁹, Johannes Hertrich¹⁰, Zhiyuan Hu⁸, Tobías I. Liaudat¹¹,
Nils Laurent¹², Brett Levac¹³, Mathurin Massias¹⁴, Thomas Moreau², Thibaut Modrzyk¹⁵, Brayan Monroy¹²,
Sebastian Neumayer¹⁶, Jérémy Scanvic¹, Florian Sarron⁶, Victor Sechaud¹, Georg Schramm¹⁷, Romain Vo¹, Pierre Weiss⁶
Estimated cost
Total price (material costs)
Progress
Software: released
DeepInverse is an open-source PyTorch-based library for solving imaging inverse problems with deep learning. deepinv accelerates deep learning research across imaging domains, enhances research reproducibility via a common modular framework of problems and algorithms, and lowers the entrance bar to new practitioners.
Get started: Read the documentation at deepinv.github.io.
Check out the 5-minute Quickstart Tutorial, comprehensive examples, or User Guide to begin exploring.
Deepinv features:
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A large framework of predefined imaging operators
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Many state-of-the-art deep neural networks, including pretrained, out-of-the-box reconstruction models and denoisers
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Comprehensive frameworks for plug-and-play restoration, optimization, and unfolded architectures
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Training losses for inverse problems
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Sampling algorithms and diffusion models for uncertainty quantification
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A framework for building datasets for inverse problems
Publications
Affiliations
¹ CNRS, ENS de Lyon, France
² Université Paris-Saclay, Inria, CEA, Palaiseau, France
³ CNRS, ENS Paris, PSL, France
⁴ University of Edinburgh, UK
⁵ Heriot-Watt University, Edinburgh, UK
⁶ IRIT, CBI, CNRS, Université de Toulouse, France
⁷ CNRS UAR 851, Université Paris-Saclay, Orsay, France
⁸ EPFL, Lausanne, Switzerland
⁹ IMT, CNRS, Université de Toulouse, France
¹⁰ Université Paris Dauphine – PSL, Paris, France
¹¹ IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
¹² Universidad Industrial de Santander, Bucaramanga, Colombia
¹³ University of Texas at Austin, USA
¹⁴ Inria, ENS de Lyon, France
¹⁵ INSA de Lyon, France
¹⁶ Chemnitz University of Technology, Chemnitz, Germany
¹⁷ Department of Imaging and Pathology, KU Leuven, Belgium