TEmporal Differences (TED) Compressed Sensing is a method developed for accelerating thermal monitoring of prostate MRgHIFU. TED combines k-space subsampling, parallel imaging, and the proposed Compressed Sensing reconstruction framework. The method is described in a manuscript that was submitted to JMRI.
This Matlab toolbox contains the TED code and two temperature reconstruction demos:
- Gel phantom data, acquiredw with a GE scanner.
- Agar phantom data, acquired with a Philips scanner.
In both cases, fully sampled data was acquired in-vitro and then retrospectively subsampled offline. A practical 1D variable-density subsampling scheme was used.
Clone or download the CORE-PI code.
A liscence for Matlab is required. The code was tested with Matlab2017R.
Open the "main.m" function in Matlab, choose one example from the following list, set the desired reduction factor (R), and run the code.
The agar phantom data is courtesy of Prof. William Grissom, Vanderbilt University, TA, USA. The gel phantom data is courtesy of Insightec Ltd., Tirat HaCarmel, Israel.