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				Convolutional Robust Principal Component  Analysis   (CORONA)
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** Contents

1. Overview
2. Requirements
3. Installation and basic operation
4. Copyright
5. Warranty
6. History
7. Download
8. Trademarks

** Publishers

Oren Solomon				[email protected]
Regev Cohen                 [email protected]
	
Department of Electrical Engineering
Technion - Israel Institute of Technology
Haifa, 32000, Israel

1. Overview

   We present the codes for Convolutional Robust Principal Component Analysis (CORONA) CORONA is a deep learning based robust PCA network. CORONA's architecture is based on unfolding an iterative algorithm for obtaining a sum of low-rank and sparse matrices representation of the input data. The iterative algorithm is a modified version of th fast iterative soft-shrinkage/thresholding algorithm (FISTA), by Beck and Teboulle, SIIMS, 2009. CORONA is able to achieve exteremly fast convergence compared with FISTA. In the attached codes, CORONA was applied to the separation of contrast signal from hte cluttering tissue in contrast enhanced ultrasound imaging.

   Descriptions for running the codes are located in the Documentation folder. However, this code comes without any warranty or any additional explanations. Some modifications to file paths' and locations should be made prior to running the code.

   This code is for academic purposes only.

   If you are using this code, please cite:

   1. Solomon, Oren, et al. "Deep Unfolded Robust PCA with Application to Clutter Suppression in Ultrasound", Arxiv.

2. Requirements

   • MATLAB R2016a or newer (previous versions require modifications). • Python 3.5.2, using the PyTorch 0.4.1 package. • A solid GPU for training the network • At least 8GB RAM; 64GB or more is recommended.

3. Installation and basic operation

   To Install:

   1. Simply run the codes from the relevant directories. More descriptions are inside the Documentation folder.

4. Copyright

   Copyright © 2018 Oren Solomon, Regev Cohen and Yi Zhang, Department of Electrical Engineering, Technion - Israel Institute of Technology, Haifa, 32000, Israel

   This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

   This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

   You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

   This code is for academic purposes only.

5. Warranty

   Any warranty is strictly refused and you cannot anticipate any financial or technical support in case of malfunction or damage; see the copyright notice.

   Feedback and comments are welcome. We will try to track reported problems and fix bugs.

   Bugs are encouraged to be reported to [email protected] or [email protected]

6. History

• January 18, 2019 Version 1.0 released under GNU GPL version 3.

7. Download

   The code is available on GitHub: https://github.com/KrakenLeaf/CORONA

8. Trademarks

   MATLAB is a registered trademark of The MathWorks. Other product or brand names are trademarks or registered trademarks of their respective holders.

   All third party software and code packages are disctributed under the GNU license as well. The authors claim no responsibility for this software and code.