We are proposing a regularized reconstruction strategy for the detection of bone lesions in 18F-fluoride whole body PET images obtained with 1 min/bed using the anatomical information provided by co-registered CT images. Bones are recognized on CT images and then transposed into the PET volume framework. During PET reconstruction, two different priors are used for bone and non-bone voxels: the relative difference prior in bone and the P-Gaussian prior in non-bone. After a tuning of the priors' parameters, the reconstruction strategy has been tested on 6 18F-fluoride PET/CT studies, on a total of 67 lesions. Regularized images provided results comparable to the standard 3 min/bed images, in terms image quality, lesion activity, noise level and noise correlation. The proposed strategy therefore appears to be a useful tool to reduce the acquisition time or the injected dose in 18F-fluoride PET studies.
Regularized ML reconstruction for time/dose reduction in 18F-fluoride PET/CT studies.
Maria Carla Gilardi;
2015
Abstract
We are proposing a regularized reconstruction strategy for the detection of bone lesions in 18F-fluoride whole body PET images obtained with 1 min/bed using the anatomical information provided by co-registered CT images. Bones are recognized on CT images and then transposed into the PET volume framework. During PET reconstruction, two different priors are used for bone and non-bone voxels: the relative difference prior in bone and the P-Gaussian prior in non-bone. After a tuning of the priors' parameters, the reconstruction strategy has been tested on 6 18F-fluoride PET/CT studies, on a total of 67 lesions. Regularized images provided results comparable to the standard 3 min/bed images, in terms image quality, lesion activity, noise level and noise correlation. The proposed strategy therefore appears to be a useful tool to reduce the acquisition time or the injected dose in 18F-fluoride PET studies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


