2018 年 38 巻 3 号 p. 61-75
Compressed sensing (CS) is a rapidly developing technique for reducing scanning times while maintaining image contrast and quality. CS theory affirms that certain images can be recovered from highly compressed k-space data with an appropriate reconstruction algorithm. This article reviews the fundamentals of CS, its methods, pulse sequence designs, the reconstruction algorithm, and potential artifacts and their causes, which are important for implementing the CS technique in clinical practice.