Source-assisted attenuation correction for emission computed tomography

A method of ML-EM image reconstruction for use in connection with a diagnostic imaging apparatus that generates projection data comprising:

• (a) collecting projection data including measured emission projection data;
• (b) assuming an initial emission map;
• (c) assuming an initial attenuation map;
• (d) iteratively updating the emission map and the attenuation map;
• (e) with each iteration, recalculating the emission map by taking a previous emission map and adjusting it based upon:
• (i) the measured emission projection data;
• (ii) a reprojection of the previous emission map which is carried out with a multi-dimensional projection model;
• and, (iii) a reprojection of the attenuation map;
• and,
• (f) with each iteration, recalculating the attenuation map by taking a previous attenuation map and adjusting it based upon:
• (i) the measured emission projection data;
• and, (ii) the reprojection of the previous emission map which is carried out with the multi-dimensional projection model, wherein the adjustment to the attenuation map in the recalculating step is not based upon measured transmission projection data.

A medical diagnostic imaging apparatus for reconstructing image representations of a subject being examined therewith comprising:

• an emission memory which stores measured emission projection data from the subject;
• an image memory which stores emission maps;
• an attenuation map memory which stores attenuation maps;
• a first projector which generates emission map projections via forward projection of the emission maps from the image memory, said projector using a first multi-dimensional projection model;
• a second projector which generates attenuation map projections via forward projection of the attenuation maps from the attenuation map memory, said projector using a second multi-dimensional projection model;
• a first data processor which samples the emission memory, and the first projector, and in accordance therewith updates the attenuation maps stored in the attenuation map memory;
• a second data processor which samples the emission memory, the first projector, and the second projector, and in accordance therewith updates the emission maps stored in the image memory;
• and,
• a human-viewable display which renders reconstructed images representations of the subject from the emission maps.

A method of ML-EM reconstruction for use in connection with a diagnostic imaging apparatus, the method comprising:

• (a) collecting emission projection data;
• (b) estimating an emission map;
• (c) estimating an attenuation map;
• (d) adjusting the emission map using:
• (i) the measured emission projection data;
• (ii) a reprojection of a previous emission map which is carried out with a multi-dimensional projection model;
• and
• (iii) a reprojection of the attenuation map;
• (e) adjusting the attenuation map using:
• (i) the measured emission projection data;
• and
• (ii) a reprojection of a previous emission map which is carried out with a multi-dimensional projection model;
• (f) iteratively repeating steps (d) and (e) until an emission map and attenuation map are reconstructed which optimize a likelihood probability function.

A method of ML-EM reconstruction for use in connection with a diagnostic imaging apparatus, the method comprising:

• (a) collecting transmission projection data;
• (b) estimating an attenuation map;
• (c) estimating an emission map;
• (d) collecting emission projection data;
• (e) adjusting the emission map using:
• (i) the measured emission projection data;
• (ii) a reprojection of a previous emission map which is carried out with a multi-dimensional projection model;
• and
• (iii) a reprojection of the attenuation map;
• (f) adjusting the attenuation map using a combination of:
• (i) the collected emission projection data;
• and
• (ii) a reprojection of a previous emission map which is carried out with a multi-dimensional projection model;
• (g) iteratively repeating steps (e) and (f) until an emission map and attenuation map are reconstructed which optimize a likelihood probability function.

A medical diagnostic imaging apparatus for reconstructing image representations of a subject being examined therewith comprising:

• an emission memory which stores measured emission projection data from the subject;
• an image memory which stores emission maps;
• an attenuation map memory which stores attenuation maps;
• a first projector which generates emission map projections via forward projection of the emission maps from the image memory, said projector using a first multi-dimensional projection model;
• a second projector which generates attenuation map projections via forward projection of the attenuation maps from the attenuation map memory, said projector using a second multi-dimensional projection model;
• a first data processor which samples the emission memory, and the first projector, and in accordance therewith updates the attenuation maps stored in the attenuation map memory, wherein the updates are not made based upon measured transmission projection data;
• a second data processor which samples the emission memory, the first projector, and the second projector, and in accordance therewith updates the emission maps stored in the image memory;
• and,
• a human-viewable display which renders reconstructed images representations of the subject from the emission maps.

A medical diagnostic imaging apparatus for reconstructing image representations of a subject being examined therewith comprising:

• an emission memory which stores measured emission projection data from the subject;
• an image memory which stores emission maps;
• an attenuation map memory which stores attenuation maps;
• a first projector which generates emission map projections via forward projection of the emission maps from the image memory, said projector using a first multi-dimensional projection model;
• a second projector which generates attenuation map projections via forward projection of the attenuation maps from the attenuation map memory, said projector using a second multi-dimensional projection model;
• a first data processor which samples the emission memory, and the first projector, and in accordance therewith updates the attenuation maps stored in the attenuation map memory;
• a second data processor which samples the emission memory, the first projector, and the second projector, and in accordance therewith updates the emission maps stored in the image memory, wherein the updates made by the first and second data processors iteratively optimize a likelihood probability function;
• and,
• a human-viewable display which renders reconstructed images representations of the subject from the emission maps.