# tinycs

**Repository Path**: ethan996/tinycs

## Basic Information

- **Project Name**: tinycs
- **Description**: minimal MATLAB-based compressed sensing MRI toolkit
- **Primary Language**: Unknown
- **License**: GPL-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-05-11
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


# tinycs

*tinycs* is a minimal compressed sensing (CS) toolkit designed
to allow MR imaging scientists to design undersampled
acquisitions and reconstruct the resulting data with CS without
needing to be a CS expert.

Currently, TinyCS supports Cartesian geometries with a total
variation constrained reconstruction only.  If there is
sufficient interest, I can add additional acquisition designs
and sparsity constraints.

The Cartesian reconstruction is based on the split Bregman
code written by Tom Goldstein, originally available here:
<http://tag7.web.rice.edu/Split_Bregman.html>

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