Biliary atresia is the most frequent cause of chronic cholestasis in infants. When left untreated, this condition leads to death from liver insufficiencywithin the first 2 yr of life. The modern therapeutic approach consists of a sequential strategy with Kasai portoenterostomy as a first step and, in case of failure, liver transplantation. After portoenterostomy, no more than 20% to 30% of patients w i l l live jaundice-free into adulthood. Illness in another third will be palliated, and these patients have extended survival, delaying liver transplantation to later childhood (2 to 15 yr). The remaining 30% to 40% will not benefit from the Kasai operation and will die of liver failure in infancy. The annual need of liver transplantation for biliary atresia is one case per million people. This indication represents 35% to 67% of the reported series of pediatric liver transplantation and between 5% and 10% of the indications for liver transplantation, all ages included. Approximately four of five children transplanted for biliary atresia will become long-term survivors with good physical and mental development; recurrence of the disease after transplantation has not been observed. Because most candidates are young children

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Medical information is evolving towards more complex multimedia data representation, as new imaging modalities are made available by sophisticated devices. Features such as segmented lesions can now be extracted through analysis techniques and need to be integrated into clinical patient data. The management of structured information extracted from multimedia has been addressed in knowledge based annotation systems providing methods to attach interpretative semantics to multimedia content. Building on these methods, we develop a new clinical imaging annotation system for computer aided breast cancer screening. The proposed system aims at more consistent, efficient and standardised data mark-up of digital and digitalised radiology images. The objective is to provide detailed characterisation of abnormalities as an aid in the diagnostic task through integrated annotation management. The system combines imaging analysis results and radiologist diagnostic information about suspicious findings by mapping well-established visual and low-level descriptors into pathology specific profiles. The versatile characterisation allows differentiating annotation descriptors for different types of findings. Our approach of semi-automatic integrated annotations supports increased quality assurance in screening practice. This is achieved through detailed and objective patient imaging information while providing user-friendly means for their manipulation that is oriented to relieving the radiologist's workload.

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