Ct-free attenuation correction for spect using deep learning with imaging and non-imaging information

A system based upon artificial neural networks to generate attenuation-corrected SPECT from non-attenuation-corrected SPECT (single photon emission computed tomography) data, comprising:

• a SPECT scanner;
• and
• a machine learning system including a 3D Dual Squeeze-and-Excitation Residual Dense Network for directly generating attenuation-corrected SPECT from non-attenuation-corrected SPECT or generating an intermediate step of attenuation map estimation, wherein images from photopeak window with or without one or more scatter windows of the SPECT scanner are fed to the 3D Dual Squeeze-and-Excitation Residual Dense Network to generate attenuation-corrected SPECT.

A method based upon artificial neural networks to directly generate attenuation-corrected SPECT from non-attenuation-corrected SPECT (single photon emission computed tomography), comprising:

• generating images from a photopeak window with or without one or more scatter windows of a SPECT scanner, and
• applying a machine learning system including a 3D Dual Squeeze-and-Excitation Residual Dense Network for directly generating attenuation-corrected SPECT from non-attenuation-corrected SPECT or generating an intermediate step of attenuation map estimation, wherein images from photopeak window with or without and one or more scatter windows of the SPECT scanner are fed to the 3D Dual Squeeze-and-Excitation Residual Dense Network to generate attenuation-corrected SPECT.