The clinical pharmacology of morphine is complicated by its active metabolite, morphine-6-β-glucuronide (M6G). M6G is a potent μ-opioid agonist that has been recognized to play an important role in the clinical effects of morphine. However, M6G probably crosses the blood brain barrier with difficulties, and is of importance for the effects of morphine only during long-term morphine administration because only then M6G may reach high enough CNS concentrations. Since M6G is eliminated from the body via the kidney, it may cause severe opioid side effects with insidious onset and long persistence when renal function is impaired. This time dependent participation of M6G at the clinical effects of morphine makes it difficult to predict the effect of morphine in an individual patient. The problem may be solved using a PK/PD modeling approach to the clinical pharmacology of morphine that takes the delayed action of M6G into consideration.

In this study, we investigate the application of the fuzzy clustering to the anatomical localization and quantitation of brain lesions in Positron Emission Tomography (PET) images. The method is based on the Fuzzy C-Means (FCM) algorithm. The algorithm segments the PET image data points into a given number of clusters. Each cluster is an homogeneous region of the brain (e.g. tumor). A feature vector is assigned to a cluster which has the highest membership degree. Having the label affected by the FCM algorthm to a cluster, one may easily compute the corresponding spatial localization, area and perimeter. Studies concerning the evolution of a tumor after different treatments in two patients are presented.

Region growing is a very useful technique for image segmentation. Its efficiency mainly depends on its aggregation criterion. In the present paper, a new algorithm is proposed with a homogeneity criterion based on an adequate tuning between spatial neighbourhood and histogram neighbourhood. It differs from other techniques by reconsidering the pixel (or voxel) assignments on each step by a process which minimizes variance through special dilations. Thus, the region created by an initial seed can be non-connected and possibly does not contain this seed. Examples are given in dental surgery for 2D X-Ray images (and their associated 3D block) and for 3D images acquired by the Morphometre, the new 3D scanner constructed by GEMSE (General Electric Medical Systems).