2018 年 38 巻 3 号 p. 87-92
Compressed sensing (CS) MR has been introduced as an innovative sparse recovery framework that supports k-space undersampling for accelerated image acquisition. CS is expected to achieve higher k-space undersampling by exploiting the underlying sparsity in an appropriate transform domain. Clinical applications of CS in neuroradiology are presented and discussed in this review.