Super-resolution in respiratory synchronized positron emission tomography

Daphné Wallach, Frédéric Lamare, G. Kontaxakis, D. Visvikis
IEEE Trans. Med. Imaging. 2012-02-01; 31(2): 438-448
DOI: 10.1109/TMI.2011.2171358

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1. IEEE Trans Med Imaging. 2012 Feb;31(2):438-48. doi: 10.1109/TMI.2011.2171358.
Epub 2011 Oct 13.

Super-resolution in respiratory synchronized positron emission tomography.

Wallach D(1), Lamare F, Kontaxakis G, Visvikis D.

Author information:
(1)INSERM, U650, LaTIM, CHU Morvan, Brest F-29200, France.

Respiratory motion is a major source of reduced quality in positron emission
tomography (PET). In order to minimize its effects, the use of respiratory
synchronized acquisitions, leading to gated frames, has been suggested. Such
frames, however, are of low signal-to-noise ratio (SNR) as they contain reduced
statistics. Super-resolution (SR) techniques make use of the motion in a sequence
of images in order to improve their quality. They aim at enhancing a
low-resolution image belonging to a sequence of images representing different
views of the same scene. In this work, a maximum a posteriori (MAP)
super-resolution algorithm has been implemented and applied to respiratory gated
PET images for motion compensation. An edge preserving Huber regularization term
was used to ensure convergence. Motion fields were recovered using a B-spline
based elastic registration algorithm. The performance of the SR algorithm was
evaluated through the use of both simulated and clinical datasets by assessing
image SNR, as well as the contrast, position and extent of the different lesions.
Results were compared to summing the registered synchronized frames on both
simulated and clinical datasets. The super-resolution image had higher SNR (by a
factor of over 4 on average) and lesion contrast (by a factor of 2) than the
single respiratory synchronized frame using the same reconstruction matrix size.
In comparison to the motion corrected or the motion free images a similar SNR was
obtained, while improvements of up to 20% in the recovered lesion size and
contrast were measured. Finally, the recovered lesion locations on the SR images
were systematically closer to the true simulated lesion positions. These
observations concerning the SNR, lesion contrast and size were confirmed on two
clinical datasets included in the study. In conclusion, the use of SR techniques
applied to respiratory motion synchronized images lead to motion compensation
combined with improved image SNR and contrast, without any increase in the
overall acquisition times.

DOI: 10.1109/TMI.2011.2171358
PMID: 21997249 [Indexed for MEDLINE]

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