Co-Registering Attenuation Data and Emission Data in Combined Magnetic Resonance/Positron Emission Tomography (MR/PET) Imaging Apparatus

A system for improving for co-registering attenuation data of MR coils in a MR/PET imaging system with PET emission data, comprising:

• a MR/PET scanner, wherein the MR/PET scanner includes RF coils;
• and
• a processor programmed to (a) compute a likelihood of PET emission data on a grid in a parameter space based on an algorithm, wherein the algorithm defines L(λ, μbody, μcoils{p}) as a log-likelihood of measured PET data, where λ is an emitter distribution (image), μbody is a known linear attenuation coefficient (LAC) distribution of a patient from MR, μcoils is a LAC map of said MR coils, and {p} is a set of parameters governing the position of each coil;
• (b) assume a μcoils{p};
• (c) reconstruct λ, and forward project λ based on an assumed μcoils{p}, and compute L based on said reconstruction and forward projection;
• (d) adjust position parameters of {p} assumed in step (b);
• and (e) repeat steps (c) and (d) until the likelihood of emission data based on the computed L is maximized.

A computer-readable storage medium, having stored thereon computer-executable instructions for co-registering attenuation data of MR coils in a MR/PET imaging system with PET emission data, said computer-executable instructions comprising:

• (a) computing a likelihood of PET emission data on a grid in a parameter space based on an algorithm, wherein the algorithm defines L(λ, μbody, μcoils{p}) as a log-likelihood of measured PET data, where λ is an emitter distribution (image), μbody is a known linear attenuation coefficient (LAC) distribution of a patient from MR, μcoils is a LAC map of said MR coils, and {p} is a set of parameters governing the position of each coil;
• (b) assuming a μcoils {p};
• (c) reconstructing λ, and forward projecting λ based on an assumed μcoils{p} and computing L based on said reconstruction and forward projection;
• (d) adjusting position parameters of {p} assumed in step (b);
• and
• (e) repeating steps (c) and (d) until the likelihood of emission data based on the computed L is maximized.