Name
Title | ||
|---|---|---|
Quantitative Evaluation of Temporal Regularizers in Compressed Sensing Dynamic Contrast Enhanced MRI of the Breast |
Abstract | ||
|---|---|---|
Abstract Purpose. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS) theory makes it possible to recover MR images from randomly undersampled k-space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast. Methods. We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT), Haar wavelet transform (WT), total variation (TV), second-order total generalized variation (TGVα2), and nuclear norm (NN). We measured the signal-to-error ratio (SER) of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs) of the derived pharmacokinetic parameters Ktrans (volume transfer constant) and ve (extravascular-extracellular volume fraction) across a population of random sampling schemes. Results. NN produced the lowest image error (SER: 29.1), while TV/TGVα2 produced the most accurate Ktrans (CCC: 0.974/0.974) and ve (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate Ktrans (CCC: 0.842) and ve (CCC: 0.799). Conclusion. TV/TGVα2 should be used as temporal constraints for CS DCE-MRI of the breast. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1155/2017/7835749 | Periodicals |
Field | DocType | Volume |
Computer vision,Population,Contrast-enhanced Magnetic Resonance Imaging,Pattern recognition,Computer science,Matrix norm,Fourier transform,Correlation,Artificial intelligence,Haar wavelet,Dynamic contrast-enhanced MRI,Compressed sensing | Journal | 2017 |
Issue | ISSN | Citations |
1 | 1687-4188 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dong Wang | 1 | 21 | 4.12 |
| Lori R. Arlinghaus | 2 | 11 | 3.35 |
| Thomas E. Yankeelov | 3 | 20 | 7.14 |
| Xiaoping Yang | 4 | 11 | 5.00 |
| David S. Smith | 5 | 50 | 5.85 |