Combined Correction and Reconstruction Methods - Correction Techniques in Emission Tomography - page 200

construction/correction methods used for different applications. An obvious
question arises: Are there any cases that require a combination of both ap-
proaches and is it even possible to do this?
Let us again consider the case of brain imaging. It was shown that mo-
tion affects the quantitative evaluation of dynamic PET studies whereas the
amount of the quantication error depends on the magnitude of the patient's
head movement. As mentioned before this kind of motion is not as complex
as in case of heart imaging, but there still is the need for correction. First
approaches were based on correcting each time frame independently which
clearly reminds us of the first steps performed prior to the fully 4D parameter
identification approaches, where all frames were reconstructed indepedently
followed by a parameter estimation on the image series [20, 5]. When ne-
glecting motion while performing the new fully 4D strategies the resulting
parameter estimations may be even worse. One can imagine that motion in a
single time frame leads to artifacts in all other time frames as well.
Recently, Verhaeghe et al. [58] proposed a 4D PET reconstruction algo-
rithm for parameter identification including motion compensation. For this
new approach, the 4D framework of the same group was extended for motion
correction using PET data supersets [59]. It was shown that motion correction
in 4D applications is necessary to incorporate into the reconstruction process
on the one hand and that it can be computed on the other hand.
Although 5D reconstruction methods are rarely used in present applica-
tions they will be in focus in the next years following the trend to include as
much information as possible in the reconstruction algorithms.
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