Portal de Periódicos da CAPES

Sparse Reconstruction Techniques in Magnetic Resonance Imaging

2016; Lippincott Williams & Wilkins; Volume: 51; Issue: 6 Linguagem: Inglês

10.1097/rli.0000000000000274

1536-0210

Alice C. Yang, Madison Kretzler, Sonja Sudarski, Vikas Gulani, Nicole Seiberlich,

Sparse and Compressive Sensing Techniques

The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.