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Radiation dose to patients and its management have become important considerations in modern radiographic imaging procedures, but they acquire particular significance in the imaging of children. Because of their longer life expectancy, children exposed to radiation are thought to have a significantly increased risk of radiation-related late sequelae compared to adults first exposed to radiation later in life. Therefore, current clinical thinking dictates that dose in pediatric radiography be minimized, while simultaneously ensuring sufficient diagnostic information in the image, and reducing the need for repeat exposures. Dose management obviously starts with characterization and control of the exposure technique. However, it extends farther through the imaging chain to the acquisition system, and even to the image processing techniques used to optimize acquired images for display. Further, other factors, such as quality control procedures and the ability to handle special pediatric procedures, like scoliosis exams, also come into play. The need for dose management in modern radiography systems has spawned a variety of different solutions, some of which are similar across different manufacturers, and some of which are unique. This paper covers the techniques used in Agfa Computed Radiography (CR) systems to manage dose in a pediatric environment.

A technique for automatic anatomically selective enhancement of digital chest radiographs is developed. Anatomically selective enhancement is motivated by the desire to simultaneously meet the different enhancement requirements of the lung field and the mediastinum. A recent peak detection algorithm and a set of rules are applied to the image histogram to determine automatically a gray-level threshold between the lung field and mediastinum. The gray-level threshold facilitates anatomically selective gray-scale modification and/or unsharp masking. Further, in an attempt to suppress possible white-band or black-band artifacts due to unsharp masking at sharp edges, local contrast adaptively is incorporated into anatomically selective unsharp masking by designing an anatomy-selective emphasis parameter which varies asymmetrically with positive and negative values of the local image contrast.