Correction Strategies for Breathing Induced Motion in PET Images

Abstract

Breathing induced motion highly impacts the quality of PET images. Motion blur impacts important parameters such as standardised uptake value (SUV) and lesion volume. To be able to stage lung cancer correctly, and provide correct treatment, the impact of motion needs to be reduced.

There exists techniques to combat the breathing motion, such as elastic motion correction and gating strategies. The aim of this thesis is to compare these three methods, and develop new methods involving dynamic frame reconstruction of PET images. The new strategies are not dependent on external equipments, and can be applied directly to attenuation corrected dynamic frames.

The results show that elastic motion correction is far better then most gating techniques. Gating techniques are shown to be dependent on which parameters is chosen in reconstruction. Elastic motion correction does not involve choosing parameters, and is easy for the operator to perform. Dynamic frame based motion correction shows some improvement in volume estimation, but is far from as good as the existing techniques, however, some improvements can be done to this technique. Dynamic frame based gating shows promising results in both volume estimation and activity measurements, however, more experimentation needs to be conducted to further verify the effectiveness of the technique.