A Mathematical Model Toward Quantitative Assessment of Parallel Imaging Reconstruction

Yu Li¹, Feng Huang¹, Wei Lin¹, Arne Reykowski¹

In this work, we propose a mathematical model that gives explicit representations for three different types of errors in parallel imaging reconstruction. These errors have different patterns in image space and affect the image quality in different fashions. This model offers a tool to extensively investigate how to quantitatively assess imaging quality beyond signal to noise ratio. Based on the proposed model, practical reconstruction techniques can be developed to suppress three types of errors to different degrees for improved overall imaging performance.