Image reconstruction using compressed sensing for individual and collective coil methods

摘要: Introduction: Compressed Sensing (CS) has been recently proposed for accelerated MR image reconstruction from highly under-sampled data. A necessary condition CS is the sparsity of itself in a transform domain. Theory: Sparse data helps to achieve incoherent artifacts, whichcan be removed easily using various iterative algorithms (for e.g. non-linear Conjugate Gradient) as part CS. The should reconstructed by algorithm that enforces both representation and consistency with acquired samples. Methods: This work presents results obtained applying on non-Cartesian k-space Radial Spiral schemes. performed Individual Coil Method (ICM) Collective (CCM). ICM approach considers each coil individually whereas CCM coils collectively images. Results Conclusion: Artifact Power (AP) SNR are used quantifying parameters compare quality show radial trajectory suitable choice MRI. In terms method compatibility,ICM shows promising results.