Design and Optimization of Low-field MRI Coils for Enhanced Signal-to-noise Ratios and Image Quality: Literature Review

Magnetic resonance imaging (MRI) is a vital tool in medical diagnostics, providing non-invasive, high-resolution images of internal body structures. In recent years, the global interest in the development of cost-effective, portable, and accurate MRI solutions has led to the development of low-field MRI systems. Nonetheless, low-field MRI is burdened by low image resolution and Signal-to-Noise Ratio (SNR), which limits their application. This article looks at the current state of low-field MRI, focusing on design and optimization of coils to increase SNR and image quality. Looking at coils (volume, surface, and phased array) used in low-field MRI, volume coils reveal homogenous signal reception but the absence of deep tissue sensation. Surface coils have larger SNR in superficial tissues and significantly lower SNR in deeper structures. The phased array coils are characterized by high SNR and can also be used for parallel imaging; however, the issue of mutual coupling between coil elements remains challenging. The SNR in low-field MRI can be enhanced by optimizing the shape of the coils through the use of high conductivity noise reduction and the machine learning algorithm. This work lays down the groundwork that would be used in subsequent studies on other developments and concerning issues pertaining low-field MRI coil design and optimization.