Meeting Banner
Abstract #1158

Deep Learning-Based Receiver Coil Sensitivity Map Estimation for SENSE Reconstruction using Transfer Learning

Madiha Arshad1, Mahmood Qureshi1, Omair Inam1, and Hammad Omer1
1Medical Image Processing Research Group (MIPRG), Dept. of Elect. & Comp. Engineering, COMSATS University, Islamabad, Pakistan


Many Parallel MRI algorithms (e.g. Sensitivity Encoding (SENSE)) require knowledge of the receiver coil sensitivity maps. Magnetic field strength is an important factor in defining the sensitivity maps of the receiver coils in MRI. This paper presents a method to estimate the receiver coil sensitivity maps of a higher magnetic field strength scanner utilizing a deep learning network (denoted as ResU-Net-34), initially trained on the receiver coil sensitivity maps of a lower field strength scanner using transfer learning. SENSE reconstruction results show a successful domain transfer between the receiver coil sensitivities of different magnetic field strengths with the proposed method.

This abstract and the presentation materials are available to members only; a login is required.

Join Here