Evaluation of contrast reproduction method based on the anatomical guidance of the cerebral images reconstruction in positron emission tomography

Positron emission tomography is a medical imaging modality providing in-vivo volumetric images of functional processes of the human body, which is used for the diagnosis and the following of neuro degenerative diseases. PET efficiency is however limited by its poor spatial resolution, which generates a decrease of the image local contrast and leads to an under-estimation of small cerebral structures involved in the degenerative mechanism of those diseases. This so-called partial volume effect degradation is usually corrected in a post-reconstruction processing framework through the use of anatomical information, whose spatial resolution allows a better discrimination between functional tissues. However, this kind of method has the major drawback of being very sensitive to the residual mismatches on the anatomical information processing. We developed in this thesis an alternative methodology to compensate for the degradation, by incorporating in the reconstruction process both a model of the system impulse response and an anatomically-based image prior constraint. This methodology was validated by comparison with a post-reconstruction correction strategy, using data from an anthropomorphic phantom acquisition and then we evaluated its robustness to the residual mismatches through a realistic Monte Carlo simulation corresponding to a cerebral exam. The proposed algorithm was finally applied to clinical data reconstruction. (author)