In this paper, we review the results of BIOINFOMED, a study funded by the European Commission (EC) with the purpose to analyse the different issues and challenges in the area where Medical Informatics and Bioinformatics meet. Traditionally, Medical Informatics has been focused on the intersection between computer science and clinical medicine, whereas Bioinformatics have been predominantly centered on the intersection between computer science and biological research. Although researchers from both areas have occasionally collaborated, their training, objectives and interests have been quite different. The results of the Human Genome and related projects have attracted the interest of many professionals, and introduced new challenges that will transform biomedical research and health care. A characteristic of the 'post genomic' era will be to correlate essential genotypic information with expressed phenotypic information. In this context, Biomedical Informatics (BMI) has emerged to describe the technology that brings both disciplines (BI and MI) together to support genomic medicine. In recognition of the dynamic nature of BMI, institutions such as the EC have launched several initiatives in support of a research agenda, including the BIOINFOMED study.

This contribution discusses a selection of today's techniques and futurc concepts for digital x-ray imaging in medicine. Advantages of digital imaging over conventional analog methods include the possibility to archive and transmit images in digital intormation systems as well as to digitally process pictures before display, for example, to enhance low contrast details. After reviewing two digital x-ray radiography systems for the capture of süll x-ray images, we examine the real time acquisition of dynamic x-ray images (x-ray fluoroscopy). Here, particular attention is paid to the implications of introducing charge-coupled device cameras. We then present a new unified radiography/fluoroscopy solid-state detector concept. As digital image quality is predominantly determined by the relation of signal and noise, aspects of signal transfer, noise, and noise-related quality measures like detective quantum efficiency feature prominently in our discussions. Finally, we descibe a digital image processing algorithm for the reduction of noise in images acquired with low x-ray dose. @ 19ss SptE and tS&T. [s1 01 7-e909(99)00401-8]

No abstract

No abstract

No abstract