Digital Radiographic Image Quality Using the Fluorospot Compact

Digital Radiographic Image Quality Using the Fluorospot Compact By the end of this course, you will be able to: Adjust image density using mAs, kV, and amplification. Adjust image contrast using grids and lookup tables (LUT) Explain the advantages of using DiamondView and Edge Enhancement Density Contrast Resolution mA/mAs SID Filtration Grids kV kV Grids Software LUTs DiamondView Spatial Resolution Focal Spot Geometry SID/TOD Image Receptor Contrast Resolution Density kV Grids Filtration Mostly controlled by mAs Also controlled by SID Can be influenced by kV Now controlled electronically Controlled by the Fluorospot Compact Configurable in the organ program Customized by body part and/or user preference Controlled by mAs Influenced by kV Adjusted by Amplification LUT’s, or Look Up Tables, are used to transform the input data into a more desirable output format.  Simply put, it allows us to apply a different grayscale to an image simply by selecting a “table” or palette. Siemens LUT’s are body-part-specific and numbered 1-17, with 1 and 2 for Service use only. DiamondView An intelligent image processing algorithm that achieves high detail contrast and resolution for localized areas by de-constructing the image and individually enhancing the image contrast. The image is separated into “layers” of frequencies.  Each layer has the Diamondview algorithm applied to it, and the image is then “re-constructed” for final display. Deconstructs Original Image Processing Sub-images Recombined Without DiamondView With DiamondView Radiographically, contrast influenced mostly by kV Also influenced by grids Software enhances contrast LUT’s Diamondview Defined by the image receptor Pixel size Influenced by image geometry Tube angulation, OFD, SID, etc. TFT Bias Line Data Line Gate Line Photo Diode Spatial Resolution is fixed and is determined by the pixel size of the image receptor Siemens DR plates have a pixel size of 140-160 microns (one micron = 1/10,000 inch) The smaller the pixel size, the better the spatial resolution Mathematically determined by the Nyquist limit Resolution can have its appearance altered by a change in image contrast Images with higher contrast have what appears to be increased resolution – also called “visibility of detail” These changes can also be made with software Edge Enhancement Gain – the degree to which the change will be applied Kernel Size – defined the extension of the differences Harmonization Similar gain and kernel size applies Spatial resolution defined by pixel size Contrast resolution influenced by Edge Enhancement You should now be able to: Adjust image density using mAs, kV, and amplification Adjust image contrast using grids and lookup tables (LUTs) Explain the advantages of using DiamondView and Edge Enhancement