Compressed Sensing for Active Feedback Contrast-Enhanced in Vivo Tumor Imaging

Luan Vu¹, Jon Furuyama¹, Thomas Goldstein², Stanley Osher², Yung-Ya Lin¹

The ability to successfully reconstruct images without having to collect the entire k-space is valuable for parameter optimization and can lead to a higher success rate for the detection of early tumors. Other k-space trajectories can be used to further improve the performance of the algorithm, such as concentrating the kept data points towards the center of k-space, while deleting more points around the edges (results not shown). As a result, strategic k-space sampling (beyond purely random) can be employed to further accelerate data acquisition.