MRF Agent Based Segmentation: Application to

anonymous 1 anonymous, 2 anonymous, 3 anonymous Abstract. The Markov Random Field (MRF) probabilistic framework is classically introduced for a robust segmentation of Magnetic Resonance Imaging (MRI) brain scans. Most MRF approaches handle tissues segmentation via global model estimation. Structure segmentation is then carried out as a separate task. We propose in this paper to consider MRF segmentation of tissues and structures as two local and cooperative procedures immersed in a multiagent framework. Tissue segmentation is performed by partitionning the volume in subvolumes where agents estimate local MRF models in cooperation with their neighbours to ensure consistency of local models. These models better reflect local intensity distributions. Structure segmentation is performed via dynamically localized agents that integrate anatomical spatial constraints provided by an a priori fuzzy description of brain anatomy. Structure segmentation is not reduced to a postprocessing step: rather, structure agents cooperate with tissue agents to render models gradually more accurate. We report several experiments that illustrate the working of our multiagent framework. The evaluation was performed using both phantoms and real 3T brain scans and showed a robustness to nonuniformity and noise together with a low computational time. This MRF agent based approach appears as a very promising new tool for complex image segmentation.

A non-invasive approach to study lifetime exposure and bioaccumulation of PCBs in protected marine mammals: PBPK modeling in harbor porpoises

In the last decade, physiologically based pharmacokinetic (PBPK) models have increasingly been developed to explain the kinetics of environmental pollutants in wildlife. For marine mammals specifically, these models provide a new, non-destructive tool that enables the integration of biomonitoring activities and in vitro studies. The goals of the present study were firstly to develop PBPK models for several environmental relevant PCB congeners in harbor porpoises (Phocoena phocoena), a species that is sensitive to pollution because of its limited metabolic capacity for pollutant transformation. These models were tested using tissue data of porpoises from the Black Sea. Secondly, the predictive power of the models was investigated for time trends in the PCB concentrations in North Sea harbor porpoises between 1990 and 2008. Thirdly, attempts were made to assess metabolic capacities of harbor porpoises for the investigated PCBs. In general, results show that parameter values from other species (rodents, humans) are not always suitable in marine mammal models, most probably due to differences in physiology and exposure. The PCB 149 levels decrease the fastest in male harbor porpoises from the North Sea in a time period of 18†years, whereas the PCB 101 levels decrease the slowest. According to the models, metabolic breakdown of PCB 118 is probably of lesser importance compared to other elimination pathways. For PCB 101 and 149 however, the presence of their metabolites can be attributed to bioaccumulation of metabolites from the prey and to metabolic breakdown of the parent compounds in the harbor porpoises