MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration

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HeMIS: Hetero-Modal Image Segmentation (2016, background): “In medical imaging, a number of approaches have been proposed, some of which require to re-train a speciﬁc model with the missing modalities or to synthesize them [9].”
Toward Implementing an MRI-Based PET Attenuation-Correction Method for Neurologic Studies on the MR-PET Brain Prototype (2010, methodology): “Assuming that bone–air segmentation can be performed (using either the DUTE sequences proposed later or an atlas-based method (16)), LACs have to be assigned to all tissue classes identified.”
MRI-Based Attenuation Correction for PET/MRI Using Ultrashort Echo Time Sequences (2010, methodology): “Recently, a new method has been proposed that uses a combination of pattern recognition and atlas registration to predict the attenuation map from the MR image and a set of aligned MRI and CT datasets (10).”
Attenuation Correction Synthesis for Hybrid PET-MR Scanners: Application to Brain Studies (2014, methodology): “method [16], local information derived from a pattern recognition technique and global information obtained by an atlas registration are combined to predict a pseudo-CT image from a given MRI image.”