On the shape of convolution kernels in MRI reconstruction: Rectangles versus ellipsoids

• Published in: Magnetic resonance in medicine Vol. 87; no. 6; pp. 2989 - 2996
• Main Authors: Lobos, Rodrigo A., Haldar, Justin P.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.06.2022
• Subjects: Algorithms; Artificial neural networks; Convolution; Ellipsoids; Image Processing, Computer-Assisted - methods; Image reconstruction; kernel shape; Kernels; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Mathematical models; MRI reconstruction; Neural networks; Neural Networks, Computer; Parameters; Rectangles; Retrospective Studies; Spatial discrimination; Spatial resolution; kernel shape; convolution; MRI reconstruction

Purpose Many MRI reconstruction methods (including GRAPPA, SPIRiT, ESPIRiT, LORAKS, and convolutional neural network [CNN] methods) involve shift‐invariant convolution models. Rectangular convolution kernel shapes are often chosen by default, although ellipsoidal kernel shapes have potentially appea...