Coder Social home page Coder Social logo

data-driven_nonsmooth_optimization's Introduction

Data-drive nonsmooth optimization

This repository contains the code for the article "Data-driven nonsmooth optimization" by S. Banert, A. Ringh, J. Adler, J. Karlsson, and O. Öktem. An arxiv version of the article can be found here.

Contents

The code contains the following

  • Files used for training the algorithm.
  • Files used for validation, both generate one slice/reconstruction and objective function values on a batch of data.
  • Files for generalization to deconvolution.

Note that the Mayo Clinic data used in the training do not belong to the authors and must therefore be obtained separately, see here.

Installing and running the code

Clone this repository, and the ODL repository. Install ODL from source, e.g., by following the ODL installation instructions. Also install numpy, scipy, and ASTRA (version 1.8.3). If you are using conda, the latter can be installed with the following command

  • $ conda install -c astra-toolbox astra-toolbox=1.8.3

After this, the scripts can be run using, e.g., spyder. Training has been done using ODL commit 0ab389f, and validation one done using ODL commit eff7129.

Contact

Sebastian Banert, Postdoc
Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden
[email protected]

Axel Ringh, PhD student
Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden
[email protected]

Jonas Adler, PhD student
Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden
Elekta Instrument AB, Stockholm, Sweden
[email protected]

Johan Karlsson, Associate Professor
Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden
[email protected]

Ozan Öktem, Associate Professor
Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden
[email protected]

Funding

We acknowledge Swedish Foundation of Strategic Research grants AM13-0049 and ID14-0055, Swedish Research Council grant 2014-5870 and support from Elekta.

The authors thank Dr. Cynthia McCollough, the Mayo Clinic, and the American Association of Physicists in Medicine for providing the data necessary for performing comparison using a human phantom.

data-driven_nonsmooth_optimization's People

Contributors

aringh avatar

Stargazers

 avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

Forkers

vishalbelsare

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.